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Attitude toward the online advertising format

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Attitude toward the online advertising format a reexamination of the attitude toward the ad model in an online advertising context
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Burns, Kelli Suzanne
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Advertising campaigns ( jstor )
Advertising research ( jstor )
Advertising signs ( jstor )
Classified advertising ( jstor )
Consumer advertising ( jstor )
Entertainment ( jstor )
Internet ( jstor )
Rectangles ( jstor )
Skyscrapers ( jstor )
Television commercials ( jstor )
Dissertations, Academic -- Journalism and Communications -- UF ( lcsh )
Journalism and Communications thesis, Ph. D ( lcsh )
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non-fiction ( marcgt )

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Thesis (Ph. D.)--University of Florida, 2003.
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Includes bibliographical references.
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Printout.
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Vita.
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by Kelli Suzanne Burns.

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ATTITUDE TOWARD THE ONLINE ADVERTISING FORMAT:
A REEXAMINATION OF THE ATTITUDE TOWARD THE AD MODEL IN AN
ONLINE ADVERTISING CONTEXT

















By

KELLI SUZANNE BURNS


A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL
OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT
OF THE REQUIREMENTS FOR THE DEGREE OF
DOCTOR OF PHILOSOPHY

UNIVERSITY OF FLORIDA




ATTITUDE TOWARD THE ONLINE ADVERTISING FORMAT:
A REEXAMINATION OF THE ATTITUDE TOWARD THE AD MODEL IN AN
ONLINE ADVERTISING CONTEXT
By
KELLI SUZANNE BURNS
A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL
OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT
OF THE REQUIREMENTS FOR THE DEGREE OF
DOCTOR OF PHILOSOPHY
UNIVERSITY OF FLORIDA
2003


Copyright 2003
by
Kelli Suzanne Bums


Dedicated in loving memory to my grandmother


ACKNOWLEDGMENTS
I would like to acknowledge the dedicated professors at the University of Florida
who guided me throughout this dissertation. I would like to thank Dr. Richard Lutz, who
went above and beyond his duties as a professor in the Warrington College of Business to
supervise and cochair a dissertation for a communications student. His intellectual
contributions and financial resources were critical to the successful completion of this
dissertation and are greatly appreciated. I would like to thank my dissertation chair, Dr.
John Sutherland, who contributed to this study through his incredible facility for data
analysis and knowledge of research methods. Committee members Dr. Marilyn Roberts,
Dr. Joseph Pisani, and Dr. Bart Weitz also deserve commendation for their feedback,
support, and participation.
My appreciation extends to Dr. David Eason and Dr. Bob Wyatt for inspiring me as
a graduate student at Middle Tennessee State University and for later hiring me.
I would like to thank my husband, Corey, who believed in me and supported my
dream. I am also grateful to John and Anne Berg, who generously and warmly welcomed
me into their home and lives for two years. I would like to thank my parents for instilling
in me all the values that made this possible and for giving me so many opportunities to
lead a fulfilling life. Finally, I would like to acknowledge my son, Griffin, who arrived
during this journey and added to the adventure.
IV


TABLE OF CONTENTS
Page
ACKNOWLEDGMENTS iv
LIST OF TABLES x
LIST OF FIGURES xv
ABSTRACT xvi
CHAPTER
1 INTRODUCTION 1
The Origins of Online Advertising 2
Online Advertising Today 6
Current Online Advertising Formats 6
Demand for New Online Advertising Formats 11
Online Advertising Mix 12
Online Advertising Spending 13
Online Advertising Effectiveness 15
Statement of Puipose 18
Importance of the Study 19
Outline 20
2 LITERATURE REVIEW 21
Attitude Toward the Ad 23
Attitude Toward the Ad as a Mediator 24
Likability Studies 26
Attitude Toward the Ad Model 27
Attitudes Toward Advertising in General 31
Beliefs About Advertising in General 34
The Relationship Between Beliefs and Attitudes 35
Categorizing Beliefs About Advertising 36
Belief and Attribute Dimensions Included in Previous Studies 37
Attitudes Toward Advertising in a Specific Media Vehicle 48
Online Advertising Effectiveness 51
Effectiveness of Executional Elements 51
Online Consumer Behavior as a Measure of Effectiveness 52
Attitudes Toward Online Advertising 53
v


Proposed Model 59
Conclusion 61
3 STUDY 1 63
Purpose 63
Research Questions 63
Critique of Methodology in Previous Research 63
Method 64
Depth Interviews With Industry Experts 64
Depth Interviews With Experienced Online Users 66
Procedure for Selecting Online Advertising Formats 68
Format Selection Results 69
Perceptual Dimensions of Online Advertising Formats 74
Irritation 74
Entertainment 77
Information 78
Novelty 79
Interactivity 79
Composition 80
Discussion 82
Online Advertising Formats 82
Perceptual Dimensions 83
4 STUDY 2 86
Purpose 86
Hypotheses 89
Method 90
Sample 90
Procedure 90
Stimulus Ads 91
Measures 91
Results 94
Sample Description 94
Overall Data Structure 97
Verification of Measures 98
Test-Retest Reliability 99
Factor Analysis of Perceptual Items and Attitude Measures 100
Correlations Among Variables for Each Format 107
Predictors of Attitude Toward the Online Ad Format 113
Predictors of Attitude Toward the Ad 120
Behavioral Measures 123
Discussion 127
Overview 127
Interpretation of Results 128
Study Limitations 131
vi


Implications for Online Advertising Theory 135
Implications for Online Advertising Industry 135
Future Research 135
Conclusion 136
5 STUDY 3 137
Purpose 137
Hypotheses 137
Method 138
Sample 138
Procedure 139
Stimulus Ads 140
Measures 140
Results 142
Sample 142
Attitude Toward Online Advertising 150
Perceptions of and Attitude Toward Online Advertising Format 150
Relationships among Variables 153
Behavioral Moderators 156
Discussion 162
Overview 162
Interpretation of Results 162
Study Limitations 163
Implications for Online Advertising Theory 166
Implications for Online Advertising Industry 167
Future Research 168
6 IMPLICATIONS 170
Introduction 170
Results Overview 172
Future Research 174
Conclusion 176
APPENDIX
A INTERVIEW GUIDE FOR ONLINE ADVERTISING EXPERTS 177
Screener 177
Informed Consent 177
Interview Guide 179
B INTERVIEW GUIDE FOR EXPERIENCED WEB SURFERS 181
Screener 181
Informed Consent 182
vii


Interview Guide
183
C ONLINE SURVEYS FOR STUDY 2 189
Version A 189
Introduction 189
Informed Consent 189
Extra Credit 191
Surfing the Web 191
Advertising on the Web 191
First Online Ad 192
Second Online Ad 195
Third Online Ad 198
Demographics 201
Conclusion 202
Version B 202
Introduction 202
Informed Consent 202
Extra Credit 204
Surfing the Web 204
Advertising on the Web 204
First Online Ad 205
Second Online Ad 208
Third Online Ad 211
Demographics 215
Conclusion 216
D ONLINE SURVEY FOR STUDY 3 217
Invitation
Survey
Introduction
Informed Consent
Esearch.com ID
Advertising on the Web
Format Introduction
First Online Ad Format
Second Online Ad Format..
Third Online Ad Format
Progress Report
Fourth Online Ad Format...
Fifth Online Ad Format
Sixth Online Ad Format
Demographics
Conclusion
...217
...217
...217
...218
...219
...219
...220
221
223
225
227
227
229
231
233
235
viii


E FACTOR ANALYSES FOR PERCEPTUAL AND ATTITUDINAL MEASURES
BY ONLINE AD FORMAT 236
Analyses for Banner Ads 236
Analyses for Pop-up Ads 238
Analyses for Skyscraper Ads 241
Analyses for Large Rectangle Ads 243
Analyses for Floating Ads 246
Analyses for Interstitial Ads 248
LIST OF REFERENCES 251
BIOGRAPHICAL SKETCH 264
IX


LIST OF TABLES
Table page
3-1 Advertisers Represented in Stimulus Ads 67
3-2 Unaided Recall and Recognition of Online Ad Formats by Experienced Web
Surfers (N= 10) 70
3-3 Summary of Performance of Chosen Formats across Selection Criteria 73
3-4 Descriptors of Online Ad Formats Used by Online Advertising Experts 75
3-5 Descriptors of Online Ad Formats Used by Experienced Web Surfers 76
3-6 Summary of Dimensions and Corresponding Descriptors 81
4-1 Demographic Characteristics of Respondents 95
4-2 Internet Usage Characteristics of Respondents 96
4-3 Online Purchase Behaviors of Respondents 97
4-4 Verification of Common Attitude Measures 99
4-5 Mean Ratings for Attitude Indices for Respondents who Completed Both Versions
( = 69) 100
4-6 Summary of Factor Loadings for the Rotated Three-Factor Solution for Perceptual
Items 102
4-7 Means, Standard Deviations, and Alphas for Three-Factor Solution 103
4-8 Mean Scores for Attitude Indices (with Coefficient Alpha) for Each Online Ad
Format 104
4-9 Mean Scores for Perceptual Factor Indices (with Coefficient Alpha) for Each
Online Ad Format 105
4-10 One-Way Analyses of Variance for the Effects of Format on Attitude and
Perceptual Factor Indices 106
x


4-11 Post-Hoc Comparisons of Attitude and Perceptual Factor Means Across Format
Using LSD 107
4-12 Intercorrelations for Attitude and Perceptual Factor Indices for Banner Ads 108
4-13 Intercorrelations for Attitude and Perceptual Factor Indices for Pop-Up Ads 109
4-14 Intercorrelations for Attitude and Perceptual Factor Indices for Skyscraper Ads .110
4-15 Intercorrelations for Attitude and Perceptual Factor Indices for Large Rectangle
Ads Ill
4-16 Intercorrelations for Attitude and Perceptual Factor Indices for Floating Ads 112
4-17 Intercorrelations for Attitude and Perceptual Factor Indices for Interstitial Ads...l 13
4-18 Regression Analysis Summary for Variables Predicting Attitude Toward Banner
Ads 115
4-19 Regression Analysis Summary for Variables Predicting Attitude Toward Pop-Up
Ads 115
4-20 Regression Analysis Summary for Variables Predicting Attitude Toward
Skyscraper Ads 116
4-21 Regression Analysis Summary for Variables Predicting Attitude Toward Large
Rectangle Ads 117
4-22 Regression Analysis Summary for Variables Predicting Attitude Toward Floating
Ads 117
4-23 Regression Analysis Summary for Variables Predicting Attitude Toward Interstitial
Ads 118
4-24 Summary of Significance of Predictor Variables Across All Formats 118
4-25 Regression Analysis Summary for Variables Predicting Attitude Toward Banner
Ads 121
4-26 Regression Analysis Summary for Variables Predicting Attitude Toward Pop-Up
Ads 121
4-27 Regression Analysis Summary for Variables Predicting Attitude Toward
Skyscraper Ads 122
4-28 Regression Analysis Summary for Variables Predicting Attitude Toward Large
Rectangle Ads 122
xi


4-29
4-30
4-31
4-32
4-33
4-34
4-35
4-36
4-37
4-38
5-1
5-2
5-3
5-4
5-5
5-6
5-7
5-8
5-9
Regression Analysis Summary for Variables Predicting Attitude Toward Floating
Ads 122
Regression Analysis Summary for Variables Predicting Attitude Toward Interstitial
Ads 123
One-Way Analyses of Variance for Effects of Format Familiarity on Aforlmt 124
Post-Hoc Comparisons of Aformat Means Across Format Familiarity Using LSD .125
Group Differences for Attitude Toward Online Ad Format Between Respondents
Who Had Clicked Through on Certain Online Ad Formats and Respondents Who
Had Not Clicked Through 126
Post-Hoc Comparisons of Aformat Means Across Clickthrough Frequency Using
LSD 126
Group Differences for AfonTlat Between Respondents Who Had Later Visited Sites
Advertised Using Certain Online Ad Formats and Respondents Who Had Not Later
Visited Sites 127
Regression Analysis Summary for Attitude Toward Large Rectangle Ads for First-
Time Respondents 133
Regression Analysis Summary for Attitude Toward Large Rectangle Ads for
Second-Time Respondents 133
Post-Hoc Comparisons of Mean Familiarity Scores Across Formats Using LSD.134
Gender, Age, Race, and Marital Status of Respondents 143
Education, Income, and Employment of Respondents 146
Geographic Region of Residence of Respondents 148
Internet Usage Characteristics of Respondents 149
Online Purchase Behaviors of Respondents 150
Coefficient Alphas for Measures Across Formats 151
ANOVA for Formats on Attitude and Perceptual Item Factor Indices 152
Post-Hoc Comparisons of Attitude and Perceptual Format Means Across Formats
Using LSD 153
Regression Analysis Summary for Perceptual Factors Predicting Attitude Toward
Banner Ads 154
xii


5-10 Regression Analysis Summary for Perceptual Factors Predicting Attitude Toward
Pop-Up Ads 154
5-11 Regression Analysis Summary for Perceptual Factors Predicting Attitude Toward
Skyscraper Ads 155
5-12 Regression Analysis Summary for Perceptual Factors Predicting Attitude Toward
Large Rectangle Ads 155
5-13 Regression Analysis Summary for Perceptual Factors Predicting Attitude Toward
Floating Ads 155
5-14 Regression Analysis Summary for Perceptual Factors Predicting Attitude Toward
Interstitial Ads 156
5-15 Group Differences for Aformat Between Early and Late Internet Adopters 157
5-16 Group Differences for Afomut Between High-Speed Internet Access and Low-Speed
Internet Access Respondents 158
5-17 Group Differences for Afomla, Between Respondents Who Had Clicked Through on
Certain Online Ad Formats and Respondents Who Had Not 159
5-18 One-Way Analyses of Variance for Effects Format Familiarity on Afomiat 160
5-19 Post-Hoc Comparisons of Aformat Means Across Format Familiarity Using LSD .161
5-20 Group Differences for Aforalat Between Respondents Who Had Made an Online
Purchase and Those Who Had Not 161
E-l Rotated Component Matrix of Perceptual Items for Banner Ads 236
E-2 Means, Standard Deviations, and Alphas for Banner Ad Factors 237
E-3 Factor Analysis of Aa E-4 Factor Analysis of Aformat for Banner Ads 237
E-5 Factor Analysis of As¡te for Banner Ads 238
E-6 Rotated Component Matrix of Perceptual Items for Pop-up Ads 238
E-7 Means, Standard Deviations, and Alphas for Pop-up Ad Factors 239
E-8 Factor Analysis of Aati for Pop-Up Ads 239
E-9 Factor Analysis of Aformat for Pop-up Ads 240
E-10 Factor Analysis of As¡te for Pop-up Ads 240
xiii


E-l 1 Rotated Component Matrix of Perceptual Items for Skyscraper Ads 241
E-12 Means, Standard Deviations, and Alphas for Skyscraper Ad Factors 241
E-13 Factor Analysis of Aad for Skyscraper Ads 242
E-14 Factor Analysis of Aformat for Skyscraper Ads 242
E-l5 Factor Analysis of As¡te for Skyscraper Ads 243
E-l 6 Rotated Component Matrix of Perceptual Items for Large Rec Ads 243
E-l 7 Means, Standard Deviations, and Alphas for Large Rec Factors 244
E-18 Factor Analysis of Aad for Large Rec Ads 244
E-l9 Factor Analysis of Afornlat for Large Rec Ads 245
E-20 Factor Analysis of As¡te for Large Rec Ads 245
E-21 Rotated Component Matrix of Perceptual Items for Floating Ads 246
E-22 Means, Standard Deviations, and Alphas for Floating Ad Factors 247
E-23 Factor Analysis of Aad for Floating Ads 247
E-24 Factor Analysis of Aformat for Floating Ads 247
E-25 Factor Analysis of As¡,e for Floating Ads 248
E-26 Rotated Component Matrix of Perceptual Items for Interstitial Ads 248
E-27 Means, Standard Deviations, and Alphas for Interstitial Ad Factors 249
E-28 Factor Analysis of Aad for Interstitial Ads 249
E-29 Factor Analysis of Aformat for Interstitial Ads 250
xiv


LIST OF FIGURES
Figure page
2-1 Modified Structural Model of Aad Formation 28
2-2 Proposed Structural Model of Aad Formation (showing two antecedents) in an
Online Advertising Context 60
4-1 Modified Attitude-Toward-the-Ad Model for Testing Relationships in the
Online Context 89
4-2 Modified Attitude-Toward-the-Ad Model for the Online Context Using Shading to
Indicate the First Set of Relationships to be Tested 114
4-3 Modified Attitude-Toward-the-Ad Model for the Online Context Using Shading to
Indicate the Second Set of Relationships to be Tested 120
4-4 Significant Relationships in the Modified Attitude-Toward-the-Ad Model for the
Online Context 131
5-1 Comparison of Formats Across Perceptual Descriptors 164
xv


Abstract of Dissertation Presented to the Graduate School
of the University of Florida in Partial Fulfillment of the
Requirements for the Degree of Doctor of Philosophy
ATTITUDE TOWARD THE ONLINE ADVERTISING FORMAT:
A REEXAMINATION OF THE ATTITUDE TOWARD THE AD MODEL IN AN
ONLINE ADVERTISING CONTEXT
By
Kelli Suzanne Burns
August 2003
Chair: John C. Sutherland
Cochair: Richard J. Lutz
Major Department: Journalism and Communications
This dissertation introduced a new constructattitude toward the online
advertising format (Aformat)and demonstrated its relevance in the attitude-toward-the-ad
(Aa(j) model.
As the online advertising environment becomes more cluttered, technological
possibilities expand, and expenditures show improvement, an understanding of
consumers attitudes toward the various online advertising formats is critical.
In Study 1, depth interviews with Web surfers and online advertising experts
identified 15 perceptions of online advertising formats. The interviews also determined
six online advertising formats for future study including banners, pop-ups, skyscrapers,
large rectangles, floating ads, and interstitials.
xvi


In Study 2, a survey with a student sample was used to determine the influence of
Aformat on Aad and the ability of the perceptions identified in the first study and other
variables to predict Aformat-
The regression equation revealed that while Aformat was a significant predictor of
Aad, attitude toward online advertising was not. The influence of Aformat on Aad is
particularly important given that Aa(¡ is a documented precursor of brand attitude, brand
choice, and purchase intentions.
Online ad perceptions were found to be related to Afommt for all six online ad
formats tested. The formats differed in terms of the specific perceptions that were
significantly correlated with attitude toward each format. The other hypothesized
predictors of At-ormat (i.e., attitude toward online advertising, attitude toward the Web site,
and attitude toward the Internet) were found to be either significantly correlated with only
certain formats or not significantly correlated at all.
Study 3 produced descriptive data on Aformat using a national survey of 1,075 adults.
This study also determined how each format was rated on the perceptual dimensions and
tested the ability of perceptions to predict Aformat.
The data supported the three hypotheses of this study. Web users possess
significantly different attitudes across formats. Users also hold a varied combination of
perceptions about each format. Furthermore, the three perceptions of entertainment,
annoyance, and information have a significant impact on Aformat-
XVII


CHAPTER 1
INTRODUCTION
If you don't get noticed, you don't have anything. You just have to be noticed, but
the art is in getting noticed naturally, without screaming or without tricks.
-Leo Burnett, The Art of Writing Advertising
In 2001, the notoriously ubiquitous online ads for X10 wireless cameras garnered
much attention in trade publications and caused frustration and annoyance for many Web
users. Using an ad contained within its own window that popped under the users
browser window, X10 Wireless Technologies was successful in achieving mass reach
online (32.8% of the Webs entire audience between January 2001 and May 2001) and a
total of 28 million unique visitors by the end of May 2001 (Jupiter Media Metrix, 2001b).
According to Nielsen//NetRatings, 388,000 unique visitors entered the XI0 Web site the
month prior to the campaign launch (Mediapost, 2001). By May 2001, the number of
unique visitors for the month had climbed to 3.5 million (Mediapost, 2001). However, the
company experienced a steep decline in traffic with 73% of unique visitors leaving the
site or closing the window within 20 seconds (Jupiter Media Metrix, 2001b). Only 4.2%
of visitors spent more than three minutes on the site (Jupiter Media Metrix, 2001b).
While this campaign was successful in increasing the number of unique visitors to
the site, several indicators suggest it failed to enhance the companys image. These ads
generated negative publicity for the company and were met with disapproving reactions
by consumers (Olsen, 2001). In addition, chat rooms discussions focused on how to
disengage these ads and many articles were written describing how to restrain XIOs
efforts (Mediapost, 2001). Downloads of the ad-blocking software AdSubtract have been
1


2
on the rise since the launch of this campaign (Taylor, 2001) and were predicted to reach 2
million users by the end of 2001 (Lefton, 2001a).
Yet, X10 Wireless Technologies remained undeterred in its advertising approach.
One year later, the company was the leading pop-up advertiser with over one billion pop
up impressions in the first seven months of the year (Martin & P.yan, 2002).
The XI0 example suggests the possibility of a relationship between the online
advertising format and consumer attitude toward that ad itself. However, before this
relationship can be explored, it is important to consider the specific dimensions or
perceptions of online ads that contribute to the attitude a consumer has about an ad
format. The intrusiveness of the pop-under ad, for example, may constitute a dimension
that shapes consumer attitudes toward pop-under ads.
Pop-under ads are just one of many online advertising formats. A review of the
origins of online advertising will illustrate how the efforts of a few advertisers, content
providers, and programmers set into motion what is today a multi-billion dollar industry
teeming with a variety of advertising formats.
The Origins of Online Advertising
The Internet is a product of ARPANET, which was launched by the Advanced
Research Projects Agency of the U.S. government in 1969 to connect research computers
at universities (Public Broadcasting Service [PBS], 1997). By 1971, ARPANET grew to
23 hosts, up from the original group of four host universities (PBS, 1997). In the 1980s,
Vint Cerf, known as the Father of the Internet, and Bob Kahn created TCP/IP, which is
the language shared by Internet computers, and soon after, the ARPANET computers
began to be referred to as the Internet (PBS, 1997). The explosion of the personal
computer industry in the 1980s helped spur the use of the Internet in corporate America


3
(PBS, 1997). Today, the Internet consists of a worldwide system of networked computers
accessible to hundreds of millions of people.
The World Wide Web1 was invented in 1991 by Tim Berners-Lee while he was
working for CERN, the European Particle Physics Laboratory, in Switzerland (PBS,
1997). The code he posted in a newsgroup allowed users to combine text, images, and
sound on Web pages and easily publish information on the Internet (PBS, 1997).
The development of Mosaic, a user-friendly, graphical interface browser, by Marc
Andreessen and others at the University of Illinois in 1993 helped move a mass audience
online. Mosaic incorporated the new programming language Hypertext Markup
Language (HTML). When Mosaic was released, Internet traffic increased at an annual
growth rate of 341,634% (PBS, 1997). The emergence of several national commercial
Internet service providers in the early 1990s (i.e., America Online, CompuServe, and
Prodigy) also contributed to the astronomical growth rate. As more and more consumers
went to the Web, this medium became even more enticing to advertisers.
Some early browsers only supported a text-based interface, containing no graphics,
while browsers with graphical interfaces were not always used with a high-speed modem.
Although advertisers dreamed of sending television commercials over the Internet, the
necessary bandwidth was not available at the time (Koprowski, 1999), and graphical
interfaces were not widely used by consumers. Under these constraints, online
advertising naturally evolved into a form of advertising similar to that of print media.
While often used interchangeably, the Internet and World Wide Web are not the same. The World Wide
Web is the term used to describe the collection of documents that are linked to one another through the use
of Hypertext Markup Language (HTML) and are hosted by computers connected to the Internet.


4
Online advertising emerged during the summer of 1994 when Coors Brewing
Company and Modem Media launched the first national consumer brand Web site for
Zima beer (Koprowski, 1999). Around the same time, McDonalds sponsored an online
chat on America Online (Koprowski, 1999).
Wired magazines online magazine HotWired drew serious attention from the
advertising community (Koprowski, 1999). As the first online magazine supported by
advertising, HotWired was introduced in 1994 with 12 advertisers paying $30,000 for 12
weeks (Koprowski, 1999). Advertisers included AT&T, Sprint, MCI, and Volvo
(DiBlasi, 1997). While HotWired has often been credited for offering the first banner
advertisement, the first online banner ad may have been hosted by Prodigy and its origin
may be further traced back to previous videotext and teletext services (Dolley, 1998;
Elwell, 1998; Williamson, 1998).
Also launched in 1994 was Time Warners Pathfinder site, which included access
to magazines and featured test ads from AT&T (DiBlasi, 1997). Ziff Davis launched
ZDNet the same year. Both sites acquired their first advertisers a year later.
The spring of 1995 saw the explosion of Web sites for major national brands from
Maytag to United Airlines to Ragu. These advertisers used banner ads to lure customers
to their sites (Koprowski, 1999). Also in 1995, the Procter & Gamble online advertising
account was awarded to Grey Interactive and Modem Media acquired the AT&T account
(DiBlasi, 1997).
About the same time, Oldsmobile developed commercial chat rooms to provide a
showcase for the Oldsmobile brand using celebrities to attract consumer attention. Again,
banner ads were used to publicize the chat rooms (Koprowski, 1999). Also in 1995,


5
America Online changed its anti-advertising policy and became more receptive to online
advertising. The company began to accept ads from advertisers such as DL¡direct,
General Motors, and 1-800-FLOWERS on sponsored sites (Koprowski, 1999).
Introduced in 1995, the Java computer language provided advertisers with the
technology for creating more elaborate graphics, audio, and animation (Koprowski,
1999). AT&T used this technology in 1996 to create animated banner ads (DiBlasi,
1997).
The dominance of banner advertising and lack of consistency in banner ad sizes led
the Interactive Advertising Bureau (IAB), formerly the Internet Advertising Bureau, a
nonprofit trade association founded in 1996, to adopt standards for online banner sizes
(LAB, 1996). This development ensured advertisers would not have to redesign their
banner ads to meet the specifications of individual sites.
While banners were receiving attention from advertisers and the IAB, consumer
interest in clicking through banner ads dropped significantly, from a 40% clickthrough
rate in 1995 and 1996 to less than 1% in 1997 (Koprowski, 1999). In 1996, Yahoo!
agreed to allow Procter & Gamble to pay for advertising space on the basis of
clickthrough rates rather than ad impressions (Williamson, 1996). The decline in
clickthrough rates on banner ads certainly challenged advertising agencies to rethink the
purpose and format of online advertising.
In recent years, faster modem speeds have enabled the application of new
technologies to online graphics, audio, and animation. The online interface can now have
the same look and feel as television. Subsequently, online advertising has evolved to
incorporate formats analogous to television commercials.


6
Online Advertising Today
Ads seem to be popping up and under everywhere online. Some of the more recent
and creative online advertising formats include floating ads (often referred to by the
trademarked name Shoshkele ads), which resemble cartoons floating over text, and
Webmercials, which feature animation or streaming media to transmit an advertisement
that uses video and audio. Another recent online innovation is the use of large rectangle
shaped advertisements wrapped by text. Sliding billboards are also being used by Web
sites such as USAToday.com (Elkin, 2002c). These ads appear as a large square when
first accessing a Web page and then slide up into a smaller banner ad. Another new
format is the full-screen ad introduced in 2003 by Unicast.
Current Online Advertising Formats
Below is an alphabetical list of current online advertising formats derived from
articles on online advertising, the Interactive Advertising Bureaus (2001c) Glossary of
Interactive Advertising Terms, and personal experience.
Banners are rectangular-shaped graphical elements often found at the top of Web
pages. The IAB guidelines are 468 x 60 pixels for a standard banner and 234 x 60 pixels
for a half banner (IAB, 2001a). Banners can be static or employ animated graphics to
capture the users attention. Clicking on a banner directs the user to another Web page.
Buttons are clickable graphics that are similar to banners, but are smaller, often
shaped as a square, and placed anywhere on a page. The IAB guidelines are 125 x 125
pixels for a square button and 120 x 90 or 120 x 60 pixels for rectangular buttons (IAB,
2001a). At a size of 88 x 31 pixels, microbars can also be placed in this category (IAB,
n.d.)
Chat room advertising provides advertisers with access to chat room participants.


7
Classified ads are well-suited to the interactive environment. Users input their
requests and are presented with the appropriate listings to match their criteria.
Contest sponsorships are provided by content providers to allow advertisers to
sponsor and promote a contest.
Contextual advertising highlights words within the text of a Web page that are
hyperlinks to an advertiser. Toptext, developed by Ezula, is one of the technologies used
to highlight and provide the links. This program is unknowingly downloaded by the user
when downloading other software. Other programs for delivering contextual advertising
include SurfPlus and AdPointer.
Daughter window ads open in a separate browser window at the same time a
banner is displayed on the Web page of the primary browser window.
E-mail can be ad-supported by selling advertisements on the e-mail reader or home
page. The service then provides a free e-mail system to users. Two examples of free e-
rnail services are Hotmail and Juno. Advertisers may also send direct e-mail to
consumers. Direct e-mail marketing is classified as either permission marketing, whereby
the recipient has provided permission to receive e-mail, or spam, which is unsolicited e-
mail. The e-mails are often formatted to resemble a letter, a newsletter, or a version of the
marketers Web site. Rich media can also be incorporated in e-mails.
Expandable banners increase in size from 468 x 60 to as large as 468 x 200 when
the user clicks or moves the cursor over the banner. The user has the option to read the
ad, click through to the advertisers Web site, or send the ad away by rolling the mouse to
another area on the page (Balian, 2001). One of the leading companies in this format is
PointRoll, which offers Point*Roll technology. PoinfrRoll produces additional messages


above, below, or to the side of the original ad when the user rolls over the ad. The
message disappears when the cursor is moved away to another part of the page.
Floating ads use a combination of Flash and Dynamic Hypertext Markup Language
(DHTML), which is an extended set of HTML commands. These ads create a translucent
or shaded layer over the content and then execute an animated ad within this layer using
Flash technology. The ads load after the parent page content has loaded and do not
require user initiation. United Virtualities and Eyeblaster are the two leading companies
using this technology to develop online ads. United Virtualities patent-pending ad
technology creates Shoshkele ads.
Full-screen overlays, introduced by Unicast in 2003 and also offered by Eyeblaster,
occupy the entire screen for 15 seconds (Elkin, 2003c).
Half-page units, used by the New York Times Digital, take up one side of the
screen and two of the sites four columns (Elkin, 2003a).
Interstitials are contained within the current browser window and are automatically
presented to a viewer when moving between two content pages. Once the requested page
loads, the interstitial fades away to the requested page. Interstitials are also referred to as
transition ads, intermercial ads, splash pages, and Flash pages (IAB, 2001b).
Large rectangle ads are large ads placed within the copy where an editorial photo or
graphic would normally go. The editorial copy either wraps around the side of the ad or
appears above and below the ad. Large rectangles provide advertisers with more space
than traditional banner ads. The space can feature rich media animation, interactive
product information, or e-commerce opportunities. Users can often click within the ad or
click through to the advertisers site. The IAB guidelines for large rectangles are 336 x


9
280 pixels (IAB, 2001a). Other rectangle sizes include the vertical rectangle (240 x 400
pixels), the medium rectangle (300 x 250 pixels), and the rectangle (180 x 150 pixels)
(IAB, 2001a).
Leaderboards are giant banners with the dimensions of 728 x 90 pixels (IAB, n.d.).
Nonlinking advertisements are name recognition builders. They are typically fixed
logos on a Web site that do not allow the user to click through to the advertisers site.
Paid listings are available to feature advertisers listings prominently on the results
pages of many search engines. Paid listings are also called search engine listings or key
word listings.
Pop-under ads open underneath the users browser and usually are discovered when
the user has closed or minimized the browser. The user is forced to close the pop-under
ad separately.
Pop-up ads interrupt the user by opening another window over the users browser.
The user must close or minimize the window to remove it from the screen. A pop-up ad
may appear while the user is on a Web page or while transitioning between two Web
pages. This ad format is similar to a daughter window but is not served with an associated
banner ad. The IAB guidelines for pop-up ads are 250 x 250 pixels (IAB, 2001a).
Portals reside in a tool bar. For example, CNET.com uses text portals for its
featured advertisers.
Sliding billboards appear as a large advertising unit when first accessing a Web
page and then slide up into a smaller banner unit.
Skyscrapers are similar to banners, but rather than being located at the top of a Web
page, these tall, thin ads are situated along the side of a Web page. The IAB guidelines


10
for skyscrapers are 160 x 600 and 120 x 600 pixels (IAB, 2001a). A tower ad, also called
a vertical banner, is a shorter version of a skyscraper.
Sponsored electronic mailing lists are e-mails distributed to subscribers of the
service. Many niche markets are available to advertisers through these lists. By
sponsoring an electronic mailing list, advertisers can distribute their content to a group of
people interested in the topic.
A sponsorship is an association with a Web site that provides more visibility for the
advertiser than run-of-site advertising (IAB, 2001b). With sponsorships, advertisers hope
users will favorably associate the content with the advertiser. ESPN Sportszones Injury
Report is an example of sponsored content. Microsofts $200,000 sponsorship of the
Superbowl Web site and Toyota and Chemical Banks $120,000-per-year sponsorship of
the New York Times Digital were some of the earliest examples of online sponsorship
advertising (DiBlasi, 1997).
Superstitials, developed by Unicast, load into temporary memory while a user is
viewing a Web page and instantly appear when the user clicks to another page on the
same site. Superstitials range from the size of a postage stamp to 550 x 480 pixels
(about two thirds of the screen). Superstitials typically feature full animation, sound, and
graphics and can run as long as 30 seconds.
Surround sessions, first launched by the New York Times Digital, provide a user
with banners, large rectangles, skyscrapers, and buttons from a single advertiser during a
visit to the site (Saunders, 2001b).
Web sites are the most common format of advertising on ihe Internet. The site can
be structured as a destination site, whereby information and entertainment are used to


11
attract users to the site, or as a microsite (also called a jump page), which uses small
clusters of pages hosted by a content site or network. Although the most prevalent type of
online advertising, a Web site is similar in purpose to a physical store, or even a customer
service information hotline, and Web site hosting costs are not included in estimates of
online advertising expenditures.
Webmercials (also called intermercials or Webformercials) feature animation or
streaming video and audio and require a downloadable plug-in to be viewed or heard.
Webmercials are often launched through either the use of an interstitial or a hypertext
link. While a Webmercial may be the same commercial that runs on television, the image
is smaller and not as sharp. BMW and Jaguar are two companies that have used this type
of advertising.
Viral marketing is used to quickly spread information online and is typically
accomplished through the use of e-mail. For example, Hotmail tags a logo to all outgoing
e-mail messages to promote its free e-mail. Some sites allow users to e-mail content by
clicking on e-mail this to a friend. Other sites encourage users to tell friends about the
site through e-mail. Viral marketing can also be used in newsgroups and chat rooms.
Advertisers can spread news about their company or products using this method.
Demand for New Online Advertising Fonnats
New online advertising formats have emerged as a result of the demands of
advertisers and their agencies and the economic situation of many online content
providers. For advertisers disappointed with the low clickthrough rates of banner ads,
more technologically innovative forms of online advertising evolved to supplement the
use of banner ads. Advertising agencies also recognize these more sophisticated formats
of ads as a way to increase their profit margins for online advertising (Black, 2001).


12
A sagging economy and the failure of many dot-com companies have slowed
revenue growth for the online advertising industry (Heim, 2001). As a result, online
content providers have been desperate to sell advertising space and are willing to allow
their advertisers to try more daring advertising concepts to attract the attention of the user
(Mediapost, 2001).
At the same time, marketers and advertisers are also recognizing the value of
permission marketing, whereby the consumer grants permission to receive e-mail
solicitations. Research firm eMarketer estimated 226 billion permission-based e-mails
will be distributed by the end of 2003 (eMarketer, 2001b). Permission is typically
provided when a user registers at a Web site and checks (or unchecks) a box indicating
his or her willingness to accept communications from the Web site or one of its partners.
Permission marketing allows users to have more control over their online advertising
experience.
As demonstrated, the Internet provides the advertiser with a medium for
transmitting advertisements in a variety of formats. The variety of online advertising
formats has evolved greatly from the original static banner ads, and variations of current
formats seem to appear almost daily.
Online Advertising Mix
The most prevalent online advertising format is still the banner, which represented
33% of online advertising elements for the week of April 28, 2003 (AdRelevance, 2003).
Including half banners increases this percentage by 4% (AdRelevance, 2003).
Skyscrapers also represented a high percentage of online advertising elements at 9% for
standard skyscrapers, 4% for wide skyscrapers, and 4% for vertical banners


13
(AdRelevance, 2003). Buttons represented 14% of elements and squares and medium
rectangles totaled 10% (AdRelevance, 2003).
A report by Nielsen//NetRatings found similar results, citing the dominance of the
banner ad (Martin & Ryan, 2003). Of the impressions for the top 100 cross-media
advertisers in the fourth quarter of 2002,29% were full banners and 10% were half
banners (Martin & Ryan, 2003). Rectangles (e.g., standard size, medium, large, and
vertical) totaled 24% of impressions and skyscrapers totaled 11% (Martin & Ryan, 2003).
Another Nielsen//NetRatings study also reported that pop-ups only represented
3.5% of all online advertising impressions for the fourth quarter of 2002 (Buchwalter &
Martin, 2003). Interestingly, pop-ups garnered over 11.3 billion ad impressions in the
first seven months of 2002 and 80% of the pop-up ads were used by only 63 advertisers
(Martin & Ryan, 2002). The remaining 20% of pop-up ads were distributed among 2,145
advertisers (Martin & Ryan, 2002). Over 9% of advertisers during these seven months
used a pop-up ad (Martin & Ryan, 2002).
In the two-year period before the fourth quarter of 2002, the average number of
online ad formats supported by Web sites more than doubled to 11 formats from 5.3
formats (Buchwalter & Martin, 2003). Almost all Web sites accepted the banner ad and
60% of advertisers in a Nielsen//NetRatings study were found to use banner ads
(Buchwalter & Martin, 2003). Only 10% of advertisers used the skyscraper format, while
70% of sites accepted the format, and less than 10% of advertisers used pop-ups, which
were also accepted by a high percentage of sites (Buchwalter & Martin, 2003).
Online Advertising Spending
Online advertising represented only a $0.2 billion industry in the U.S. in 1996
(Jackson, 2001a). In 1998, online advertising revenue reached $1.92 billion, passing


14
outdoor advertising revenue for the first time (Koprowski, 1999). For 2000,
PricewaterhouseCoopers reported that online spending by U.S. advertisers totaled $8.2
billion (Black, 2001).
U.S. online advertising revenue was down 12% in 2001 from the
PricewaterhouseCoopers estimate, resulting in expenditures of $7.2 billion for the year
(Jackson, 2001a). In 2002, online advertising spending totaled $5.95 billion (IAB, 2003).
The fourth quarter of 2002 showed the first consecutive quarterly increase in online
advertising revenue since the second quarter of 2000 (IAB, 2003).
Jupiter Research predicted a 10% growth rate for 2003 and $14 billion in
expenditures by 2007 (Jupiter Research, 2002). Worldwide online advertising
expenditures are expected to reach $42 billion in 2005 (Forrester Research, 2001).
Analysts at Jupiter Research anticipated that much of this growth will be fueled by
the rise in online classified ad spending (i.e., paid search engine listings) and the increase
in spending by traditional advertisers (Jupiter Research, 2002). Publishers are now
catering to traditional advertisers with better service, improved tools for measuring
results, and new technology for more creative ad format options (Green, 2003). In
addition, online ad prices have fallen dramatically and lowered the cost per thousand ad
impressions (Green, 2003).
In March 2001, a study by NieIsen//NetRatings reported that online advertising
spending by traditional advertisers surpassed spending by dot-coms for the first time
(Saunders, 2001a). In addition, of the top 100 online advertisers, more than half were
traditional advertisers. This trend has been attributed more to the increase in offline
advertisers moving online than to the recent failures in the dot-com industry (Saunders,


15
2001a). A Nielsen//NetRatings report cited a number of the top ten cross-media
advertisers that increased their online presence in 2002, namely DaimlerChrysler with a
407% increase over 2001 online advertising expenditures, Verizon Communications with
an 88% increase, Johnson & Johnson with a 39% increase, Ford Motor Company with a
34% increase, and Walt Disney and AOL Time Warner, both with a 28% increase over
2001 expenditures (Martin & Ryan, 2003).
Online Advertising Effectiveness
Clickthrough rates, an early measure of advertising effectiveness, have been
dropping fast (Khermouch & Lowry, 2001). The increase in the sheer number of online
advertisements may provide some explanation for this decline (Song, 2001). Because
clickthrough rates are calculated by dividing clicks by impressions, it is possible that
people are not necessarily clicking less often, but that impressions have increased, driving
the clickthrough rate down.
These low clickthrough rates have made the medium less attractive to advertisers
(eMarketer, 2001a). In a 2001 study of marketers and ad agency executives by Myers
Mediaenomics, 85% of respondents cited driving traffic to the Web site as one of the
top five reasons for using online advertising (receiving a higher percentage of responses
than any other alternative), and 49% of marketers and 57% of ad agency executives
indicated that the clickthrough rates were not high enough to motivate them to increase
their online ad spending for 2001 (second only to budget limitations) (eMarketer, 2001a).
The focus on clickthrough as a measure of online advertising effectiveness has been
downplayed since the initial online advertising boom. An alternative and more popular
view is that the value of online advertising cannot be solely measured by clickthrough
rates (Briggs & Hollis, 1997).


16
One problem with the use of clickthough rates as a measure of effectiveness is they
do not fully represent the totality of banner ad conversions. Data from Engage (2001)
suggested only 25% of sale or lead conversions by consumers who were exposed to an
online advertising campaign result from clickthroughs on an ad itself and slightly less
than half of all conversions occur one or more days after being exposed to a banner ad for
the site.
A study by ad agency Avenue A found that 20% of consumers who made a
purchase on a travel site clicked through on a banner ad, while 80% had previously seen
the ad and later went directly to the site to make a purchase (Gilliam, 2000). In addition,
consumers who saw ads accounted for 10% more sales and traffic than those who did not
(Gilliam, 2000).
Research has supported the idea that mere exposure to the banner ad itself (even
without a clickthrough) can have a positive effect on the brand. The 1996 HotWired Ad
Effectiveness Study (Briggs & Hollis, 1997) found banners have a brand building effect.
The 1997 IAB Online Advertising Effectiveness Study conducted by Millward Brown
(LAB, 1997) found a single exposure to a banner ad was enough to generate lifts in ad
awareness, brand awareness, purchase intent, and product attribute communication.
Using a survey of 18,000 respondents covering multiple product categories, Dynamic
Logic reported the average brand awareness lift for banner advertising to be 6%
(Dynamic Logic, 2000a). The same organization conducted a study for Travelocity and
saw a 16% lift in aided brand awareness, a percentage that increased to 44% for
respondents who saw the ad four or more times (Dynamic Logic, 2000b). A report by
Morgan Stanley Dean Witter (2001) concluded that consumers are 27% more likely to


17
recall a brand after seeing an Internet ad, representing a recall level higher than that for
magazines (26%), newspapers (23%), and television (17%). A study by Dynamic Logic
of advertisers in a program by Forbes.com that guaranteed brand improvement results
found the online campaigns of 12 participating marketers increased message association
by 28%, purchase consideration by 14%, aided awareness by 11%, and brand favorability
by 6% (Elkin, 2003b).
Research by Millward Brown Interactive has also confirmed that various online
advertising formats, including interstitials, Superstitial ads, rich media, adaptable
cursors, and streaming media, have a positive effect on brand awareness, brand
perceptions, and intent to purchase (Briggs & Stipp, 1999). A study by Morgan Stanley
found banner ads using streaming media were five times as effective in generating brand
recall than traditional banner ads (Morgan Stanley, 2001).
As these studies have shown, online advertising is capable of impacting brand
image, and therefore, clickthrough rates are certainly not the only measure of
effectiveness. Brand awareness, image, and intent-to-purchase measures may be better
indicators of long-term advertising effectiveness. Advertisers and marketers are
recognizing the implications of these studies and have been changing the way they
measure advertising effects. A report by Jupiter Media Metrix (2001a) found only 15% of
marketers measured online branding effects, while many chose to use direct response
metrics such as clickthrough rate (60%) and cost per conversion (75%). By 2002, the
percentage of marketers who measured long-term metrics, such as branding, had risen to
35% (Jupiter Research, 2002).


18
Marketers may also want to consider measuring offline sales resulting from online
advertisements. A joint study by Procter & Gamble and Information Resources, Inc.
found offline sales for an impulse food product to be 19% higher for the test group with
three online ad exposures than the control group with none (Welch & Krishnamoorthy,
2000).
As the advertising industry moves away from measuring the effectiveness of online
advertising through direct response metrics, such as clickthrough rates, traditional
measures of effectiveness, including brand awareness and intent-to-purchase, are being
embraced. A natural extension of these measures is attitude toward a specific
advertisement, which may be predicted, in part, by attitude toward the online advertising
format.
Statement of Purpose
The cluttered online advertising environment, the expanding options for online
advertising, and the estimates for future growth in online advertising expenditures all
suggest the need for the advertising industry to be concerned about consumers attitudes
toward online advertising and attitudes toward individual online ad formats.
The current study hypothesizes that attitude toward the online ad format plays a
critical role in determining attitude toward the ad. As Dynamic Logic director of client
services Jeffrey Graham wrote in his company newsletter column, You cant expect
people to separate the medium (pop-ups) from the message (bad advertising) (Graham,
2001). The oft-quoted medium is the message pronouncement by Marshall McLuhan
(1964, p. 7) further suggests a way to think about online advertising formats as these
formats themselves communicate a message.


19
Identifying the specific perceptions of online advertising that may raise or lower
attitudes toward an online advertising format was the first purpose of this study. This
study also collected descriptive data on attitudes toward different formats of online
advertisements and developed and tested a model of online advertising attitudes that
specified the antecedents of attitudes toward these new advertising formats and the effect
of attitudes toward online ad formats on attitude toward the ad (Aa<¡).
Importance of the Study
This study has a number of potential implications for advertisers and advertising
agencies. First, a greater awareness of attitudes toward online advertising formats should
influence the use of online advertising in general and choice of online advertising by
advertisers and their agencies. Second, the findings from this study identified the specific
perceptions that raise or lower attitudes toward a particular online ad format. These
results will be useful during the creation of an individual ad.
This research also makes an original contribution to the flourishing body of
literature in the area of attitudes toward advertising in general, attitudes toward
advertising in a specific media vehicle, and attitude toward the ad. This research will also
be directly useful in future studies of online advertising effectiveness and attitude toward
the online ad.
While deriving and testing dimensions of attitudes toward current online
advertising formats has both practical and theoretical significance, these findings also
have implications for emerging online ad formats, further strengthening the importance of
this study. This research can help guide the development of new online advertising
formats.


20
Outline
Chapter 2 reviews the research on the attitude-toward-the-ad model, which
incorporates, as an antecedent of Aad, the concept of attitude toward advertising in
general. The research streams on attitude toward advertising in general and attitude
toward advertising in a specific media vehicle are then reviewed, with particular
emphasis on attitude toward online advertising. The literature review concludes with a
discussion of the hypothesized model guiding the present study, illustrating the proposed
role of attitude toward the online advertising format in a modified attitude-toward-the-ad
model.
This research utilized a multi-method approach, using qualitative methods in the
first study and surveys in two additional studies. Chapter 3 describes the first study,
which used a qualitative approach. Chapter 4 discusses the second study, which tested the
hypothesized model using a student sample. Chapter 5 describes the third study, which
used an online survey to gather descriptive data from a nationwide sample of adults. In
Chapter 6, the implications of the findings of these studies are addressed in relation to the
future of the online advertising industry and theory.


CHAPTER 2
LITERATURE REVIEW
This study introduces a new constructattitude toward the online advertising
format (Aformat)and proposes to demonstrate both its determinants and its relevance in
the attitude-toward-the-ad model. According to Rodgers and Thorson (2000, para. 85),
Attitude toward the ad.. .is a response easily applied to interactive advertising.
Paralleling the definition of attitude toward the ad (Lutz, 1985, p. 46; MacKenzie & Lutz,
1989, p. 49), attitude toward the online advertising format is defined as a predisposition
to respond in a consistently favorable or unfavorable manner toward an online
advertising format.
Ad format has been simply defined as the manner in which [an ad] appears
(Rodgers & Thorson, 2000, para. 47). For example, television advertising can be
categorized in terms of the length of the commercial (e.g., 30 seconds), while magazine
advertising can be classified according to size (e.g., full page) (Rodgers & Thorson,
2000). The need to consider the ad format variable in a study of online advertising stems
from the proliferation of various online advertising formats, from banner ads to the more
television-like Webmercials. While research on attitudes toward advertising in general
has been extended to analyses of attitudes toward advertising in specific media vehicles,
it has barely addressed the existence of multiple formats of advertising within one
medium.
Research has demonstrated that consumers possess different beliefs about
advertising in various media. When comparing beliefs about advertising, several studies
21


22
have found that consumers perceive newspaper and magazine advertisements to be the
most informative (Mittal, 1994), with consumers significantly more satisfied with the
informational value of magazine advertising than with television advertising (Soley &
Reid, 1983). Bauer and Greyser (1968) found television advertising to contain the highest
proportion of ads classified as annoying, while print advertising was more likely to be
categorized as informative and enjoyable. Similarly, in another study, newspaper and
magazine advertisements have been classified as less irritating and annoying than
television advertising (Mittal, 1994). These studies demonstrate that consumers have
different beliefs about advertising in various media and suggest the possibility that
consumers may also have unique beliefs about each online advertising format. These
belief sets are expected to lead to different attitudes toward each online ad format.
Academic studies in the area of attitudes toward online advertising are theoretically
and methodologically grounded in the tradition of research on attitudes toward
advertising in general, an area that has evolved to include a focus on attitudes toward
advertising in a specific media vehicle. The emphasis in both the trade and academic
literature on understanding attitudes toward advertising may be attributable to the
documented relationship between general attitudes toward advertising and attitude toward
a specific advertisement, i.e., the attitude-toward-the-ad construct (Bauer & Greyser,
1968; Lutz, 1985; MacKenzie & Lutz, 1989; Mehta, 2000). In turn, considerable research
has demonstrated a positive association between Aad and brand attitude, brand choices, or
purchase intention (Drdge, 1989; Gardner, 1985; Homer, 1990; MacKenzie & Lutz,
1989; MacKenzie, Lutz, & Belch, 1986; Miniard, Bhatla, & Rose, 1990; Mitchell &
Olson, 1981; see discussion in Shimp, 1981; see Brown & Stayman, 1992, for a


23
comprehensive review). In addition, the Advertising Research Foundation Copy Research
Validity Project identified likability of an advertisement as the single best discriminator
of advertising effectiveness (Haley, 1990).
The following literature review will first detail the Aa(j model, describing relevant
studies in this area and illustrating the antecedents of Aa(i. This review will then describe
the research on attitudes toward advertising in general in more detail. Recent trends in
research on attitudes toward advertising will also be addressed, including the emphasis on
understanding attitudes toward advertising in a specific media vehicle and attitudes
toward online advertising. Finally, this review will describe how the proposed concept
attitude toward online advertising formatis hypothesized to fit into the existing model.
Attitude Toward the Ad
Attitude toward the ad is defined as a predisposition to respond in a consistently
favorable or unfavorable manner to a particular advertising stimulus during a particular
exposure situation (Lutz, 1985, p. 46). Early research focusing on the origins of Aa(j
incorporated a cognitive processing approach, in much the fashion of the central route to
persuasion in Petty & Cacioppos elaboration likelihood model (ELM) (1981; see Lutz,
1985). The idea that cognitions about an ad (as opposed to cognitions about the
advertised brand) could have an influence on attitude toward the ad was extrapolated
from the findings of previous studies confirming the link between brand-related
cognitions and brand attitude (Mitchell & Olson, 1981) and the relationship between
cognitive responses to an advertising message and attitudinal message acceptance
(Wright, 1973). Subsequently, the relationship between ad-related cognitions and attitude
toward the ad has been documented (Lutz, MacKenzie, & Belch, 1983).


24
Aad represents an affective response to an advertisement and the validity of such a
response is further bolstered by persuasion theories from social cognition, which
recognize the influence of not only cognitive, but also affective responses on message
effectiveness. Petty and Cacioppos (1981) ELM, which describes two routes to
persuasion, posits a central route to persuasion occurring through diligent processing of
message content and a peripheral route to persuasion resulting from more casual
processing of the message source or other contextual factors. The level of involvement
determines which path to persuasion dominates.
Attitude Toward the Ad as a Mediator
Introduced by Mitchell and Olson (1981) and Shimp (1981), Aa<¡ has been found to
be a mediator of brand attitude (A¡,), brand choice, and purchase intentions (Gardner,
1985; Homer, 1990; MacKenzie & Lutz, 1989; MacKenzie, Lutz, & Belch, 1986;
Miniard, Bhatla, & Rose, 1990; Mitchell & Olson, 1981). A meta-analysis by Brown and
Stayman (1992) of 47 samples confirmed a significant relationship between Aa brand attitudes, brand-related cognitions, and purchase intention. The significance of
brand attitude is its documented link to purchase intentions (Brown & Stayman, 1992).
MacKenzie, Lutz, and Belch (1986) applied the concepts of ELM to two of their
four structural specifications of the mediating role of Aad. In the affect transfer
hypothesis, the central route to persuasion explains the direct relationship between brand
cognitions and attitudes toward the brand, while the peripheral route serves to explain the
path from attitudes toward the ad to brand attitudes. In situations of high message
involvement (the cognitive effort directed toward processing message content) and low
ad execution involvement (the effort focused on processing non-content properties), the
central processing mechanism dominates persuasion and brand cognitions lead to brand


25
attitudes (MacKenzie & Lutz, 1989). As Droge noted, Aad appears to be a peripheral cue
that has little or no impact when central processing predominates (1989, p. 202). In
contrast, in situations of low ad message involvement, regardless of the level of ad
execution involvement, the peripheral route provides a framework for understanding how
attitudes toward the ad are directly related to brand attitude (MacKenzie & Lutz, 1989).
While Petty and Cacioppos (1981) theory can be applied in situations of low
message involvement to explain how peripheral processes operate to allow a peripheral
cue such as attitude toward the ad to have persuasion abilities, it does not explain how
attitude toward the ad may serve as a peripheral cue to influence the central route to
persuasion (MacKenzie, Lutz, & Belch, 1986). Within this dual-mediation model,
attitude toward the ad is directly related to brand attitude and also indirectly related to
brand attitude by influencing the degree to which the audience incorporates message
content into its brand cognitions (MacKenzie & Lutz, 1989). Extending this line of
research, Miniard, Bhatla, and Rose (1990) determined that the Aaci-brand attitude
relationship can be viewed as the result of not only peripheral processing, but that the two
constructs can be related even when persuasion follows the central route.
While MacKenzie, Lutz, and Belch (1986) found the relationship between A^ and
Ab to be stronger than any other relationship in the four models tested, they recognized
that shared method variance may have heightened this effect. MacKenzie and Lutz
(1989) also found Aad to have a strong effect on Ab, while cognitions about the brand did
not influence Ab as strongly as expected.
Brown and Staymans (1992) meta-analysis demonstrated that while some path-
analytic studies did not find a significant relationship between brand cognitions and brand


26
attitude (e.g., MacKenzie & Lutz, 1989), others found a significant path (e.g., Homer,
1990). Based on aggregated study data, Brown and Stayman (1992) suggested that brand
cognitions do significantly affect brand attitudes, but that this relationship is the weakest
in the model. Furthermore, the meta-analysis supports the indirect effect of attitude
toward the ad on brand attitude through brand cognitions (Brown & Stayman, 1992). In
addition, while most studies found a substantial and significant direct relationship
between Aa<¡ and brand attitude (e.g., MacKenzie, Lutz, & Belch, 1986), Brown and
Staymans (1992) meta-analysis found this relationship to be weaker than these studies
suggest.
Other studies have documented the circumstances under which Aad has strong
effects (Droge, 1989; Gardner, 1985; Park & Young, 1986). Droge (1989) found Aad to
be a significant predictor of Ab only for noncomparative, rather than comparative, ads.
Gardner (1985) found that a positive and significant relationship existed between Aad and
attitude toward the brand for both brand and nonbrand processing set conditions. Park
and Young (1986) differentiated cognitive, affective, or low involvement and found that
Aad influenced brand attitude only in situations of affective or low involvement.
Likabilitv Studies
A number of studies have addressed liking of an advertisement, a concept virtually
identical to Aad (Haley, 1990; Walker & Dubitsky, 1994). Advertisement liking has been
linked to product liking, as positive feelings toward the ad are transferred to the brand
(see review by Thorson, 1991). Liking has also been found to increase the chance that a
viewer will pay attention to an advertisement and leam its message, thereby enhancing
the advertisements effectiveness (Walker & Dubitsky, 1994). The ARF Copy Research


27
Validity Project (Haley, 1990) found liking of a commercial to be the strongest predictor
of the sales differences due to advertising for the cases evaluated.
Attitude Toward the Ad Model
While studies have demonstrated how Aa(i is predicted through cognitive responses
to the execution elements and the perception of advertiser credibility (Lutz, MacKenzie,
& Belch, 1983), Aad may also be the result of a peripheral processing mechanism (Lutz,
1985). Affective reactions to the advertiser and advertising in general, as well as the
mood of the consumer, may operate through peripheral processing to influence Aaj (Lutz,
1985).
Lutz (1985) developed a structural model of five cognitive and affective
antecedents of Aad and MacKenzie and Lutz (1989) further refined Lutzs (1985) original
model. The five antecedents include ad credibility, ad perceptions, attitude toward
advertiser, attitude toward advertising in general, and mood. The model also incorporates
second-order determinants, which directly influence the five antecedents of Aad and
indirectly impact Aad through the first-order antecedents. Figure 2-1 summarizes the
modified structural model (MacKenzie & Lutz, 1989). Descriptions of each antecedent as
defined by Lutz (1985) and MacKenzie and Lutz (1989) are also provided.
Ad credibility. The assessment of ad credibility, defined as the extent to which the
audience perceives claims made about the brand in the ad to be truthful and believable
(Lutz, 1985, p. 49), is a cognitive process requiring a central processing model. Ads
perceived to be credible receive more favorable responses by consumers.


28
Figure 2-1. Modified Structural Model of Aa(j Formation. From An Empirical
Examination of the Structural Antecedents of Attitude Toward the Ad in an
Advertising Pretesting Context, by S. B. MacKenzie and R. J. Lutz, 1989,
Journal of Marketing, 53, p. 53. Copyright 1989 by Scott B. MacKenzie and
Richard J. Lutz. Reprinted with permission.
Ad credibility results from three second-order determinants: perceived ad claim
discrepancy, advertiser credibility, and advertising credibility. Ad claim discrepancy is
the gap between the advertisements claims about the brand and the consumers
perceived performance of the brand, a perception influenced by past experience,
information about the advertised brand, and the content of the message. Advertiser
credibility reflects the consumers perceived truthfulness of the ads sponsor.
Furthermore, past experience and information about the advertiser directly influence


29
advertiser credibility. Advertiser credibility also serves as a component of the second-
order determinant of the multidimensional advertiser perceptions.
Advertising credibility, the perception of the believability of advertising in general,
also influences ad credibility. As with advertiser credibility, advertising credibility is one
component of advertising perceptions. Advertising credibility has also been modeled to
influence ad credibility indirectly through the more specific construct of advertiser
credibility (MacKenzie & Lutz, 1989).
While MacKenzie and Lutz (1989) established a significant relationship between ad
credibility and Aad, they could not find support for their hypothesis that advertising
credibility affects ad credibility. The findings did support a significant relationship
between ad credibility and another second-order determinant: advertiser credibility
(MacKenzie & Lutz, 1989).
Ad perceptions. As one of many perceptual responses to an ad, ad credibility is
actually a special case of ad perceptions, the second major antecedent to Aaj. Because of
the amount of research in the area of ad credibility, a separate classification for this
variable was warranted (Lutz, 1985).
Like ad credibility, ad perceptions also entail some degree of central processing.
This construct incorporates only consumer perceptions of the advertising stimulus and
not perceptions of the advertised brand.
As a mediating variable, ad execution characteristics have been found to have a
strong positive relationship with Aad through ad perceptions (Lutz, MacKenzie, & Belch,
1983). Attitude toward advertising and attitude toward the advertiser are modeled to


30
impact ad perceptions, demonstrating the possible influence of affect on a perceptual
process (Fazio & Zanna, 1981).
Under ad pretest conditions, MacKenzie and Lutz (1989) found advertiser attitude
to have a strong positive relationship with ad perceptions, while the relationship between
attitude toward advertising and ad perceptions could not be cross-validated. Ad
perceptions were found to exhibit a strong positive correlation with Aa(¡ (MacKenzie &
Lutz, 1989).
Attitude toward the advertiser. Defined as a learned predisposition to respond in a
consistently favorable or unfavorable manner to the sponsoring organization (Lutz,
1985, p. 53), attitude toward the advertiser represents a more affective response to an
advertisement. Perceptions of the advertiser, including advertiser credibility, are expected
to influence attitude toward the advertiser. Perceptions emanate from consumers past
experience and information about the company. Advertiser attitude was found to have a
strong positive correlation with Aad under ad pretest conditions (MacKenzie & Lutz,
1989).
Attitudes toward advertising. Attitude toward advertising represents a learned
predisposition to respond in a consistently favorable or unfavorable manner toward
advertising in general (Lutz, 1985, p. 53; MacKenzie & Lutz, 1989, p. 53-54). This
concept reflects consumers general attitudes toward advertising, rather than attitudes
toward a specific advertisement or about advertising in a specific medium.
The study of the relationship between consumers attitudes toward advertising in
general and ratings of specific ads dates back to Bauer and Greysers (1968) classic study
described in Advertising in America: The Consumer View. Bauer and Greyser (1968, p.


31
121) suggested a relationship between overall attitudes toward advertising and the
proportion of ads classified as either favorable or unfavorable. In addition, the data
revealed a relationship between attitudes toward advertising and the perception of certain
ads as informative (Bauer & Greyser, 1968, p. 136).
The model of Aad formation proposes that attitudes toward advertising resulting
from perceptions of advertising have a direct impact on Aalj. MacKenzie and Lutz (1989)
could not confirm a relationship between attitude toward advertising and Aaj in a study
under ad pretest conditions; however, they suggested that in focusing attention on the
evaluation of a specific ad, subjects were less likely to base Aad assessments on general
constructs, such as attitude toward advertising, than on specific constructs. MacKenzie
and Lutz (1989) suggested that in a natural setting, as opposed to a forced exposure
situation, a stronger relationship between attitude toward advertising and Aa(j might exist.
Mood. As the most purely affective antecedent to Aa(j, mood is the consumers
affective state at the time of exposure to the ad stimulus (Lutz, 1985, p. 54). Mood is
influenced by individual differences, which are the basic predispositional tendencies of
consumers; ad execution characteristics; and reception context, comprised of the nature
of the exposure, the amount of ad clutter, and the program or editorial context.
Attitudes Toward Advertising in General
A more thorough discussion of attitudes toward advertising is provided below and
will be followed by a discussion of attitudes toward advertising in a media vehicle and
attitudes toward online advertising. This review is provided to demonstrate how the
construct of attitude toward the online ad format emerges as a natural extension of this
body of research.


32
Researchers and industry practitioners have long been interested in attitudes toward
advertising (see Mittal, 1994; ODonohoe, 1995; Pollay & Mittal, 1993; Zanot, 1981,
1984 for reviews), a construct found to influence attitudes toward specific advertisements
(Bauer & Greyser, 1968). The earliest studies in this area date back to 1939 and are
characterized by consumers generally favorable attitudes toward advertising (Bauer &
Greyser, 1968). A 1942 survey by the Association of National Advertisers found more
than 80% of respondents to be supportive of advertising during the war (as cited in Bauer
& Greyser, 1968).
In the 1950s, attitudes toward advertising remained favorable as indicated by a
1951 survey by Mcfadden Publications (as cited in Bauer & Greyser, 1968) in which
90% of respondents agreed that advertising has played an important role in raising the
standard of living in the U.S. In the late 1950s, a Redbook magazine survey conducted by
the Gallup Organization, Inc. (1959, as cited in Bauer & Greyser, 1968) determined that
more than 80% of the over 1,600 respondents believed advertising helped raise
nationwide prosperity. In addition, 75% reported that they liked advertising and the most
frequently cited reason for liking advertising was its informational value.
General attitudes toward advertising have been on the decline since these early
studies. The percentage of Americans holding a generally favorable view of advertising
dropped to 54% in 1960 (Universal Marketing Research, 1961, as cited in Bauer &
Greyser, 1968). Bauer and Greyser (1968) found the percentage of respondents with a
favorable attitude toward advertising to be 41% by 1964. Although a majority of
respondents in this study believed advertising to be misleading and capable of persuading


33
people to buy products they should not buy, they still considered advertising to be
essential.
Zanots (1981) review of 38 public opinion polls from the early 1930s to the 1970s
revealed that attitudes toward advertising became increasingly more unfavorable during
that time. According to Zanots analysis:
The number of surveys conducted.. .during the 1970s increased dramatically; 20
are presented here.. .they reflect a decidedly negative public opinion toward
advertising. In almost every instance where a study was replicated, the later one
shows more negative attitudes. (1981, p. 146)
Research in recent years has focused more on attitudes toward advertising in a
specific medium than attitudes toward advertising in general (Alwitt & Prabhaker, 1992;
Mittal, 1994). One exception is a 1998 study of 1,000 adult consumers current attitudes
toward and confidence in advertising (Shavitt, Lowrey, & Haefiter, 1998). This study
revealed more favorable public attitudes than suggested by previous studies. Only one
fourth of respondents in this study indicated that they disliked advertising.
Another focus in recent years has been an attempt to understand the structure of
advertising attitudes. Because these studies have tended to use smaller and less nationally
representative samples, results are not generalizable to the American public (e.g., Alwitt
& Prabhaker, 1992; Andrews, 1989; Mittal, 1994; Muehling, 1987; Pollay & Mittal,
1993; Reid & Soley, 1982; Sandage & Leckenby, 1980).
Other studies have tested the relationship between general attitudes toward
advertising and advertising effectiveness. Research has demonstrated that attitudes
toward advertising in general are related to ad recall and buying interest (Donthu,
Cherian, & Bhargava, 1993; Mehta, 2000).


34
A study of outdoor advertising found that consumers with positive attitudes toward
advertising in general exhibited greater recall of outdoor advertisements than those with
negative attitudes (Donthu, Cherian, & Bhargava, 1993). Mehta (2000) found that
respondents who reported that they like advertising, feel that it provides useful
information, and view it as not being manipulative were more likely than those who did
not feel this way to notice and recall advertisements. In addition, buying interest was
found to be positively related to almost all of the advertising belief statements tested in
the study (Mehta, 2000).
Another study examined the influence of attitudes toward advertising in general on
involvement with specific advertisements, operationalized as the amount of time spent
looking at the advertisement (James & Kover, 1992). The group of subjects that believed
advertising to be manipulative and the group that found advertising to be irritating were
both more involved in the advertisements.
Beliefs About Advertising in General
While early studies often measured favorability or unfavorability toward
advertising, later studies focused on beliefs about certain aspects of advertising (Mittal,
1994). Referred to as consequences of advertising in some studies (Mittal, 1994) and
functions in others (Alwitt & Prabhaker, 1992), these statements generally reflect
beliefs about advertising.
Beliefs represent descriptive statements about the attributes an object possesses,
creating a link between an object and an attribute. Beliefs are generally considered to
contribute to the formation of attitude (Ajzen & Fishbein, 1980). As noted by Fishbein
and Ajzen, a persons attitude is a function of his salient beliefs at a given point in time
(1975, p. 222). Attitudes are summary evaluations of the perception that an object


35
possesses certain attributes and the desirability of those attributes (Ajzen & Fishbein,
1980). While an attitude is a general and enduring positive and negative feeling about
some person, object, or issue, a belief can be described as information that a person has
about other people, objects, and issues and this information may have positive,
negative, or no evaluative implications for the target of the information (Petty &
Cacioppo, 1981, p. 7). Therefore, the feeling or attitude that people hold about online
advertising formats should be derived from what people think, know, or believe about
online advertising formats.
The Relationship Between Beliefs and Attitudes
Studies in the area of attitudes toward advertising often fail to draw a distinction
between attitudes and beliefs, often measuring beliefs in an attempt to measure attitudes
(Muehling, 1987). Other studies have examined perceptual dimensions without directly
relating them to advertising attitudes (Muehling, 1987).
Other studies have examined this correlation between beliefs and attitudes toward
advertising. According to Lutz (1985), attitude toward advertising in general is
determined in part by consumer beliefs about advertising in general. A number of studies
in the area of attitudes toward advertising have measured and then correlated attitudes
toward advertising and consumer perceptions of the evaluative attributes, or beliefs, that
form those attitudes (Aaker & Stayman, 1990; Alwitt & Prabhaker, 1992,1994; Biel &
Bridgwater, 1990; Cho, 1999; Mittal, 1994; Schlosser, Shavitt, & Kanfer, 1999; Shavitt,
Lowrey, & Haefiier, 1998). Generally speaking, these studies have found a positive
correlation between attitudes and perceptions, but there are exceptions (see Mittal, 1994).
Mittal (1994) found ratings on ten evaluative items about product-specific
commercials to be congruent with overall likeability of the commercial, but this was not


36
always the case. More specifically, some commercials were rated as enjoyable but were
not liked. As Mittal concluded, The merits and demerits of product specific commercials
do individually register on the consumer mind despite overall favorable or unfavorable
predispositions (1994, p. 47). Applying this perspective to online advertising provides a
possible explanation for why a user may not like a pop-up ad, even though it is perceived
to be entertaining. Similarly, a user may rate a banner ad as informative, but because it is
associated with all online advertising, the user may not have a favorable attitude toward
this format.
Categorizing Beliefs About Advertising
The strong emphasis on belief dimensions is attributable to Bauer and Greysers
(1968) influential study. In this study, Bauer & Greyser (1968, p. 124) demonstrated how
beliefs about advertising in general influence attitudes toward advertising in general.
Bauer and Greysers (1968) study categorized eight beliefs about advertising as either
economic effects (e.g., raises standard of living or results in better products) or social
effects (e.g., persuades you to buy what you dont need or insults the intelligence of
an average consumer). Others have adopted this approach to examining advertising
beliefs as classifiable under these two factors (Reid & Soley, 1982), and subsequent
factor analyses supported this distinction (Anderson, Engledow, & Becker, 1978;
Andrews, 1989).
While Bauer and Greyser (1968) found consumers to have a generally favorable
view of the economic role of advertising, they also found consumers to hold an
unfavorable view of the social role. Other studies have confirmed Bauer and Greysers
(1968) finding that consumers feel more favorable toward the economic role of
advertising than the social role (Andrews, 1989; Greyser & Reece, 1971). A study by


37
Anderson et al. (1978) of Consumer Reports subscribers found that attitudes became less
favorable from 1970 to 1976 on both the economic and social factors of advertising.
Beliefs have been studied in terms of generalized and personalized levels (Reid &
Soley, 1982). Personalized belief items tap the influence of advertising on a persons own
behavior (e.g., advertising misleads me (Reid & Soley, 1982)), while generalized belief
items focus on how advertising affects the behavior of other people (e.g., advertising
misleads people (Reid & Soley, 1982)). Researchers have demonstrated a significant
difference in attitudes toward advertisings social and economic effects depending on
whether personalized or generalized beliefs are used (Reid & Soley, 1982).
Distinctions have also been made between the informational value of advertising
and its persuasive effects. Research has demonstrated that consumers tend to have
positive reactions toward advertising for its informational value and negative reactions
toward advertising as a result of any perceived manipulation, intrusion, or deceit (Mehta,
2000; Shavitt, Lowrey, & Haefher, 1998).
Sandage and Leckenby (1980) divided advertising attitudes into attitude toward the
institution and the instrument of advertising. While institution reflects the purpose and
effects of advertising, instrument refers to advertisings executional properties. Mittal
(1994) used this distinction in a study of attitudes toward television advertising.
Muehling (1987) examined the belief items that comprise these dimensions.
Belief and Attribute Dimensions Included in Previous Studies
Studies measuring attitudes toward the institution of advertising often incorporate
belief statements to tap underlying dimensions. These statements often reflect the effects
and consequences of advertising or the value of advertising. For example, Mittal (1994)
used belief statements to determine whether television advertising offers useful social-


38
image information, is a valuable source of information about local sales, and is
sometimes more entertaining than the programs.
Muehling (1987) measured the influence of 20 beliefs about advertising in general
on attitudes toward the institution and instrument of advertising and found five of these
beliefs to be significant and explain over 57% of the variance in attitudes toward
advertising in general. The significant beliefs included whether advertising insults the
intelligence of consumers, presents a true depiction of the advertised products, or wastes
natural resources by creating desires for necessary goods. Whether a limit should be
placed on the amount of money a company can spend on advertising and whether todays
standards for advertising are higher than 10 years ago were two additional significant
predictors of attitudes toward advertising in general. Muehling (1987) concluded that the
set of beliefs that influence attitudes toward advertising was smaller than expected and
that beliefs about both institutional and instrument aspects of advertising influenced
attitudes. However, attitudes toward the institution of advertising were higher than
attitudes toward the instrument, which was consistent with the findings of Sandage and
Leckenby (1980).
Measures of the advertising instrument often involve the use of attributes, as in the
earlier Reaction Profile studies (Wells, 1964). In these studies, respondents are asked to
indicate the extent to which attributes describe advertising or the percentage of
advertising that can be described by the attributes.
For example, Mittal (1994) used ten evaluative attributes (borrowed mainly from
Santos, 1976) and asked respondents to assess the proportion of television advertisements
that possesses each attribute. The list included such attributes as informative, honest,


39
enjoyable, boring, annoying, and silly. Mittal (1994) further categorized these attributes
under the headings of information/disinformation, enjoyment/annoyance, and silliness.
While information/disinformation was found to contribute the most to overall attitude
toward advertising, silliness was found to contribute the least (Mittal, 1994).
A number of belief dimensions have been identified by applying the Uses and
Gratifications approach to the understanding of advertising, particularly for
understanding the uses and gratifications of television commercials (Plummer, 1971;
Schlinger, 1979). Using a factor analysis of adjectives and descriptive statements,
Plummer (1971) found the viewer rewards of television to fall into seven categories
including entertainment or stimulation, irritation, familiarity, empathy or gratifying
involvement, confusion, informativeness or personal relevance, and brand reinforcement.
Schlinger (1979) had similar findings in a related study of 49 adjectives and descriptive
statements. The dimensions determined by this study included entertainment, confusion,
relevant news, brand reinforcement, empathy, familiarity, and alienation or irritation. In
both of these studies, confusion was described by items referring to the clarity of
expression and organization of commercials. Familiarity refers to the uniqueness or
novelty of an advertisement.
The Uses and Gratifications approach has been used to understand motivations for
and benefits of surfing the Web and the characteristics a Web site should exhibit to be
successful (Eighmey & McCord, 1997). Eighmey and McCord (1997) identified six
factors that discriminate between the best and worst Web sites and labeled these factors
marketing perceptions (referring to the business relationship between the site and users),
entertainment value, informational value, ease of use, credibility, and interactivity.


40
The purpose of the following review is to understand the dimensions that have been
established in previous studies. The current study will then derive its own dimensions for
quantitative research. The dimensions presented in this section are for later comparison
purposes and can be used as a benchmark for the dimensions derived in the current study.
These dimensions also provide a preview of the dimensions expected to be derived in this
study.
Studies on attitudes toward advertising, particularly attitudes toward online
advertising, also suggest dimensions relevant to this research. The three belief
dimensions that appear to be most relevant to the understanding of attitude toward online
advertising format date back to the 1968 study by Bauer and Greyser and were used in a
more recent study by Ducoffe (1996). Ducoffe (1996) found the informational,
entertainment, and irritation dimensions of advertising to be significant predictors of
attitudes toward advertising. Buying confidence will be addressed as a subcategory of the
informative dimension. Finally, offensiveness of advertising and other dimensions will be
discussed.
Information. Bauer and Greyser defined informative ads as follows:
These are ads that you learn something from that you are glad to know or know
about. They may tell you about a new product or service or they may tell you
something new about a product or service you were already familiar with. The main
thing is that they help you in one way or another because of the information they
provide. (1968, p. 182)
Bauer and Greysers (1968) finding that attitude toward advertising is positively
related to information-related reasons for liking advertisements possibly motivated the
inclusion of the informational value of advertising in a number of subsequent advertising
belief taxonomies (Alwitt & Prabhaker, 1992, 1994; Ducoffe, 1996; Lee & Lumpkin,


41
1992; Mehta, 2000; Mittal, 1994; Muehling, 1987; Pollay & Mittal, 1993; Schlosser,
Shavitt, & Kanfer, 1999; Shavitt, Lowrey, & Haefher, 1998).
The idea that advertising provides information to consumers is grounded in
information theory (Gardner, 1983). The informational role of advertising has often been
regarded as its foremost legitimizing function (Rotzoll, Haefher, & Sandage, 1989) and
the ability of advertising to provide information was found to be the primary reason for
consumer approval (Bauer & Greyser, 1968). Stiglers (1961) classic study was the first
to demonstrate how advertising is an important source of product information. Product
information provided in advertisements is perceived to result in better decision-making
by consumers (Alwitt & Prabhaker, 1992). Furthermore, advertising has been found to
stimulate competition, promote new product or brand entry, and simplify consumer
shopping (Albion & Farris, 1981).
Resnik and Stem (1977) defined informative advertising as that which provides
relevant informational cues to help a consumer make an intelligent choice among
alternatives. Some of these cues include price, performance, quality, packaging, and
special offers (Resnik & Stem, 1977). Resnik and Stem (1977) found that over 49% of
the television ads sampled were informative. A replication of the Resnik and Stem study
found no significant differences in the overall proportion of informative ads in 1977 and
1991, but did find significant differences in the use of various types of informational cues
(Stem & Resnik, 1991).
In contrast, Aaker and Norris (1982) found just over 18% of a sample of 524
prime-time television ads to be perceived by respondents as informative. In a more recent


42
study, Mittal (1994) found that almost three fourths of respondents described only 25% or
less of television advertising as informative and helpful.
Other studies of magazine advertising found 92% (Laczniak, 1979) and 86%
(Stem, Krugman, & Resnik, 1981) of the sampled consumer ads to be informative. Soley
and Reid (1983) found consumers to be more satisfied with the informational value of
magazine advertising than television advertising, although consumers were neither highly
satisfied nor dissatisfied with the informational value of the advertising in either medium.
More recent studies have examined the relationship between the informational
value of advertising and advertising attitudes. Mittal (1994) determined that of 10
perceptions considered, perceptions of the informational value of advertising explained
the most variance in overall attitude toward television advertising. Pollay and Mittal
(1993) found product information to be a significant predictor of attitudes toward
advertising. Lee and Lumpkin (1992) found that the informational dimension of attitudes
toward television advertising differentiates between those who rarely skip commercials
on pre-recorded television programs and those who skip commercials sometimes or
almost always.
Informativeness has been positively related to Internet advertising attitudes
(Schlosser, Shavitt, & Kanfer, 1999), overall advertising attitudes (Shavitt, Lowrey, &
Haefner, 1998), perceptions of advertising value (Ducoffe, 1996), and recall and buying
interest (Mehta, 2000). In contrast to studies that found a positive relationship between
perceptions of the informativeness of advertising and attitudes toward advertising, Alwitt
and Prabhaker (1992) found beliefs about the informational value of television
advertising to have little influence on attitudes toward television advertising. An


43
explanation provided by Alwitt and Prabhaker (1992) for this result is the high
intercorrelations among the four functions of knowledge, hedonic, social learning, and
affirmation of value with only the hedonic function emerging as a significant variable in
the multiple regression model.
Related to informativeness is the concept of buying confidence, which has been
addressed in a number of studies (see Mittal, 1994; Schlosser, Shavitt, & Kanfer, 1999).
Mittal (1994) found no significant relationship between perceptions of buying confidence
instilled by advertising and attitudes toward television advertising. In contrast, Schlosser,
Shavitt, and Kanfer (1999) found that the use of online advertising to make a purchase
decision contributes to Internet advertising attitudes.
Eniovment/Entertainment. Bauer and Greyser defined enjoyable ads as follows:
These are ads that give you a pleasant feeling for any reason whatsoever. They may
be entertaining, amusing, especially attractive or well done. You might enjoy them
whether or not you are interested in what is advertised. The main thing is that you
like them and are pleased you saw or heard them. (1968, p. 182)
Perceptions of the entertainment value of advertising has been considered in a
number of previous studies (Alwitt & Prabhaker, 1992, 1994; Bauer & Greyser, 1968;
Ducoffe, 1996; Lee & Katz, 1993; Mehta, 2000; Mittal, 1994; Pollay & Mittal, 1993;
Schlosser, Shavitt, & Kanfer, 1999; Shavitt, Lowrey, & Haefner, 1998). Mayer (1991)
found that purchase behavior is based on not only the consumers assessment of the
product itself, but also the entertainment value of its advertising.
Alwitt and Prabhaker (1992) found beliefs about advertisings hedonic function
contributed significantly to attitudes toward television advertising. Ducoffe (1996) found
entertainment to be significantly correlated with perceived advertising value. The
enjoyment of advertising has been shown to be the strongest predictor of attitudes toward


44
Internet advertising (Schlosser, Shavitt, & Kanfer, 1999) and attitudes toward advertising
(Shavitt, Lowrey, & Haefner, 1998). Pollay and Mittal (1993) found the dimension of
hedonic/pleasure to be significantly and positively related to advertising attitudes. Mehta
(2000) found that subjects who indicated that they enjoy looking at advertisements
exhibited higher recall and stronger buying interest than those who do not enjoy looking
at ads. Lee and Katz (1993) found over three fourths of their sample of video store
patrons disagreed that commercials on a videotape are fun to watch. In contrast, Mittal
(1994) did not find a relationship between entertainment value and attitudes toward
television advertising, but did find the group of evaluative dimensions labeled
enjoyment/annoyance to contribute significantly to variance in attitude toward
advertising.
Annovance/lrritation. Bauer and Greyser defined annoying ads as follows:
These are ads that irritate you. They may be annoying because of what they say or
how they say it. They may annoy you because they are around so much, or because
of when and where they appear. There may be other reasons for ads to be
annoyingthe main thing is that they bother or irritate you. (1968, p. 182)
The idea that advertising is defined by or can be described by its level of irritation
or annoyance is consistent with the foundations of Uses and Gratifications research
(Eighmey & McCord, 1998; Plummer, 1971; Schlinger 1979) and attitude toward
advertising studies (see Bauer & Greyser, 1968; Ducoffe, 1995, 1996; James & Kover,
1992; Mehta, 2000). Irritation is such a pervasive issue in advertising that this
characteristic has also merited a body of research about a common cause of irritation:
advertising clutter (Elliott & Speck, 1998; Ha, 1997).
Aaker and Bruzzone (1985) found irritation to be a reason for disliking advertising.
James and Kovers (1992) factor analysis of belief dimensions of attitudes toward


45
advertising resulted in just two factors, with one referring to the irritation experienced
from advertising. Ducoffe (1996) found irritation to be significantly related to perceptions
of advertising value. Mehta (2000) did not find a relationship between the belief that
advertising is annoying and either recall or buying interest.
As mentioned earlier, irritation may result from the advertising clutter (Elliott &
Speck, 1998; Ha, 1997). Ha (1997) defined perceived ad clutter as resulting from three
communication problems: hindered search, distraction, and disruption. Hindered search
hampers a persons ability to read or see the media content, while disruption is a
diversion from the media use experience and distraction is merely a lesser form of
disruption. Alwitt and Prabhaker (1994) found that respondents were more likely to
dislike television advertising when they believed that the same ads were shown too
frequently.
Other beliefs and attributes. A number of studies have examined the offensive
aspects of advertising (Alwitt & Prabhaker, 1992, 1994; Bauer & Greyser, 1968;
Schlosser, Shavitt, & Kanfer, 1999) or more specifically, poor taste and sex in advertising
(Larkin, 1977). While Bauer and Greyser (1968) contended that an offensive ad may be
considered annoying, they differentiated between these two dimensions by limiting
offensiveness to the moral aspects of the product or advertisement or the effect on
children.
Bauer and Greyser defined offensive ads as follows:
These are ads that are vulgar or morally bad in your opinion. They may be
dishonest, or untrue. They may be ads for something you dont think should be sold
or used. They may be offensive because of the way in which they were done, and
you may think that such ads should not be allowed. The main thing is that you feel
strongly that such ads are wrong. (1968, p. 182)


46
As defined by Bauer and Greyser (1968), advertising may be considered offensive
as a result of its use of deception. The deceptive nature of advertising has been examined
as a distinct belief dimension of attitudes toward advertising (Alwitt & Prabhaker, 1992;
Bauer & Greyser, 1968; Durand & Lambert, 1985; Larkin, 1977; Mehta, 2000; Muehling,
1987; Pollay & Mittal, 1993; Schlosser, Shavitt, & Kanfer, 1999; Shavitt, Lowrey, &
Haefner, 1998).
Alwitt and Prabhaker (1992) found that beliefs about the offensive aspects of
advertising have little influence on attitudes toward television advertising. Schlosser,
Shavitt, and Kanfer (1999) found that beliefs about the indignity of advertising (i.e.,
insulting intelligence and offensiveness) were not related to Internet advertising attitudes.
In contrast, Shavitt, Lowrey, and Haefner (1998) found perceptions of the indignity of
advertising (together with the entertainment value) to have the strongest effect on
predicting advertising attitudes. Alwitt and Prabhaker (1994) found a significant and
positive correlation between dislike of television advertising and the perception of the
offensiveness of the advertising.
While Pollay and Mittal (1993) found the perceived falsity of advertising to
influence attitudes, Alwitt and Prabhaker (1992) determined that the deceptive nature of
advertising has little influence on attitudes toward television advertising. Mehta (2000)
found perceptions of truth in advertising to influence buying interest. While Schlosser,
Shavitt, and Kanfer (1999) found that trust of online advertising did not contribute
significantly to Internet advertising attitudes, Shavitt, Lowrey, and Haefner (1998) found
perceptions of the trustworthiness of advertising to have a sizable effect on overall
advertising attitudes.


47
Other studies have focused on the belief that advertising promotes materialism
(Durand & Lambert, 1985; Larkin, 1977; Lee & Lumpkin, 1992; Mittal, 1994; Pollay &
Mittal, 1993). Both Mittal (1994) and Pollay and Mittal (1993) found perceptions of
materialism fostered by advertising to have a significant and negative relationship with
attitudes toward television advertising. Lee and Lumpkin (1992) did not find that
perceptions that advertising leads to wasteful buying discriminate between those who
rarely skip commercials on recorded programs and those who skip commercials
sometimes or always.
A significant and positive relationship has been established between the perception
that advertising is good for the economy and attitudes toward television advertising
(Mittal, 1994; Pollay & Mittal, 1993). The perception that advertising totally or partially
subsidizes the cost of media was also found to be a positive and significant contributor to
attitudes toward television advertising (Mittal, 1994).
Another belief perception in studies of attitudes toward advertising is social role
and image (Mittal, 1994; Pollay & Mittal, 1993). This belief reflects the idea that
advertising often attempts to sell the consumer an image or lifestyle, rather than a product
or service. Mittal (1994) found that social image information explained a significant
amount of variance in overall attitudes toward television advertising. This construct has
also been found to have a varied impact on attitudes toward advertising (Pollay & Mittal,
1993).
Other studies have addressed the need for government regulation of advertising
(Barksdale & Darden, 1972; Durand & Lambert, 1985; Larkin, 1977; Schlosser, Shavitt,
& Kanfer, 1999; Shavitt, Lowrey, & Haeftier, 1998). Schlosser, Shavitt, and Kanfer


48
(1999) found beliefs about government regulation of advertising to be unrelated to
Internet advertising attitudes. Similarly, Shavitt, Lowrey, and Haefner (1998) found
perceptions of advertising regulation and effects of advertising on prices to account for an
insignificant amount of variance in overall advertising attitudes.
Other beliefs examined in previous studies that were found to be unrelated to
advertising attitudes include manipulation (Mittal, 1994), social learning (i.e., using
advertising to learn how to behave in social situations) (Alwitt & Prabhaker, 1992), and
value affirmation and corruption (Alwitt & Prabhaker, 1992; Pollay & Mittal, 1993).
Any inconsistencies in the findings of the studies reported above may be
attributable to differences in the operationalizations of the dimensions, the sample, or the
focus of the study (whether examining attitudes toward advertising in general or in a
specific medium).
Attitudes Toward Advertising in a Specific Media Vehicle
Since Bauer and Greyser (1968) noted the moderating effects of the advertising
medium on attitudes toward advertising in general, research has focused on attitudes
toward advertising in a specific media vehicle. In these studies, researchers have used
belief dimensions from studies of attitudes toward advertising in general to understand
attitudes toward advertising in specific media vehicles. These studies, however, rarely
distinguish between different formats of advertisements within the same medium.
While studies in this area have traditionally focused on television advertising
(Alwitt & Prabhaker, 1992; Mittal, 1994), advertising in other media vehicles has also
been studied. For example, Korgaonkar, Karson, and Akaah (1997) found that general
advertising attitude scales are adaptable to direct mail advertising and that beliefs toward
advertising in general are similar to beliefs toward direct mail advertising (Korgaonkar,


49
Karson, & Akaah, 1997). This study found that while respondents had negative beliefs
toward certain aspects of direct mail advertising, overall, beliefs were generally positive.
The study also concluded that respondents who spent more money as a result of direct
mail advertising and ordered more frequently had significantly more favorable beliefs
toward direct mail advertising (Korgaonkar, Karson, & Akaah, 1997).
Donthu, Cherian, and Bhargava (1993) examined the relationship between attitudes
toward advertising and ad recall in an outdoor advertising context and found that
consumers with a positive attitude toward advertising in general were more likely to
recall outdoor advertisements than those with a negative attitude. Using a sample of video
store patrons, Lee and Katz (1993) concluded that respondents had generally negative
feelings toward advertising on videocassettes.
Historically, overall attitudes toward television advertising have been negative
(Alwitt & Prabhaker, 1992; Bauer & Greyser, 1968; Bartos & Dunn, 1974; Mittal, 1994).
Bauer and Greyser (1968) found that consumers perceive television advertising to be
more annoying than advertising in other media. Alwitt and Prabhaker (1992) found
perceptions of television advertising to be more negative than perceptions of advertising
in general from two earlier Ogilvy and Mather studies (1974, 1985, as cited in Alwitt &
Prabhaker, 1992). Mittal (1994) found nearly half of his respondents reported that they do
not like television advertising and only one fourth reported liking it somewhat. More
recent studies have suggested that attitudes about television advertising may be becoming
more favorable (Shavitt, Lowrey, & Haefher, 1999).
Specific issues with regard to television advertising include a general mistrust of
advertising and feelings of insult. For example, Alwitt and Prabhaker (1992) found that


50
about 16% of respondents believed advertising presents advertised products accurately
and 66% felt that advertised products do not perform as claimed. Mittal (1994) found the
majority of respondents to consider less than one fourth of television commercials to be
honest and believable.
In contrast, research points to some favorable attitudes toward certain aspects of
television advertising. For example, Alwitt and Prabhaker (1992) found that slightly more
than half of their respondents considered television advertising to be funny or clever.
Similarly, Mittal (1994) found that almost half of his respondents believed that television
commercials are sometimes more enjoyable than the programs.
Recently, researchers have begun to explore attitudes toward Web sites, which
serve as both advertising and a vehicle for advertising (Bruner & Kumar, 2000; Chen &
Wells, 1999; Stevenson, Bruner, & Kumar, 2000). Chen and Wells (1999) developed a
scale to measure attitude toward the Web site, a construct that may be antecedent to the
effectiveness of online advertising on that site. A study by Stevenson, Bruner, and Kumar
(2000) found that as liking of a Web site increases, key variables in the advertising
hierarchy-of-effects, namely attitude toward the ad, attitude toward the brand, and
purchase intention, are improved.
An Online Publishers Association study of 5,000 Internet users classified
respondents into high-affinity and low-affinity users whereby affinity referred to the
users connection to and engagement with a site (Elkin, 2002b). High-affinity users were
less likely than low-affinity users to feel that ads interfered with their surfing experience
and more likely than low-affinity users to believe the advertised brands are relevant, to


51
notice ads more, and to believe the sites carry advertising for high-quality products and
services (Elkin, 2002b).
Online Advertising Effectiveness
The popularity of the World Wide Web and the subsequent rise of online
advertising spending have led to studies of advertising in this medium.
Effectiveness of Executional Elements
A review of the literature reveals an emphasis on the impact of executional
elements of Internet advertising design (Bezjian-Avery, Calder, & Iacobucci, 1998;
Bruner & Kumar, 2000; Chen & Wells, 1999; Dreze & Zufryden, 1997; Li & Bukovac,
1999; Stevenson, Bruner, & Kumar, 2000). Li and Bukovac (1999) found that animated
banner ads result in a faster response and higher recall than non-animated ads. In
addition, respondents were more likely to respond to and have higher comprehension of
larger, rather than smaller, banner ads.
Bruner and Kumar (2000) and Stevenson, Bruner, and Kumar (2000) examined the
influence of background complexity on the advertising hierarchy-of-effects. In addition,
Bruner and Kumar (2000) also considered the effects of dynamic content (e.g., animated
graphics and commercials) on attitudes. Bruner and Kumar (2000) found that dynamic
content had both a direct negative effect on attitudes toward the Web site and a positive
indirect effect. Dynamic content was found to result in less favorable attitudes toward the
site, which was attributed to the annoyance caused by this type of content. In contrast,
dynamic content makes the site more interesting and thus, it is positively related to
attitude toward the site. Stevenson, Bruner, and Kumar (2000) found that simpler
backgrounds on Web sites had a more positive influence on the advertising hierarchy-of-
effects, including attitude toward the ad, attitude toward the brand, purchase intentions,


52
and attitude toward the Web site. Bruner and Kumar (2000) could not confirm this
relationship is their study.
Dreze and Zufryden (1997) found a relationship between a number of executional
elements (i.e., background, image size, sound file display, celebrity endorsement, use of
java and frames, and operating system) and the dependent variables of number of pages
accessed and time spent on a Web site. Chen and Wells (1999) determined that the
informativeness, entertainment, and organization of a Web site influence consumer
response to the site.
Bezjian-Avery, Calder, and Iacobucci (1998) found the interactivity of online
advertising may hamper persuasion under certain conditions as indicated by decreases in
purchase intention and time spent viewing advertisements when compared to the more
linear advertising format of traditional ads. The authors suggested that the best
combination appeared to be when the system properties (i.e., whether predominately
visual or verbal) matched the individual processing needs (i.e., preferring information
presented in a visual or verbal manner).
Online Consumer Behavior as a Measure of Effectiveness
Consumer behavior has been the focus of much of the online advertising
effectiveness literature (see Hoffman, Kalsbeek, & Novak, 1996, for a review). In
counting clicks and hits, researchers have attempted to quantify consumers use of Web
sites and advertising (Berthon, Pitt, & Watson, 1996). While these techniques have
intuitive appeal and the data may appear more valid than that for other media,
measurement of consumer behavior produces an incomplete picture of the effectiveness
of Internet advertising.


53
Measures of online behavior have proven to be problematic, both overestimating
and underestimating actual effectiveness (Internet Advertising Bureau, 1997; Riphagen &
Kanfer, 1997). For example, the number of "hits (i.e., a page view or impression) often
overestimates effectiveness because the user may not have attended to the message
content or the page may not have loaded properly. Clickthroughs on banner ads tend to
underestimate effectiveness, since exposure to the banner ad alone may impact consumer
attitude or future behavior (Briggs & Hollis, 1997). Another reason consumer behavior
should not be used exclusively as a measure of effectiveness is that simply observing
behavior (e.g., clickthroughs on online advertisements such as banner ads) does not
reveal the attitudes behind that behavior (Berthon, Pitt, & Watson, 1996).
Attitudes Toward Online Advertising
A review of the literature reveals a dearth of studies directly measuring attitudes
toward online advertising. The few published studies in this area of research have built a
solid foundation for continued study of attitudes toward online advertising by applying
methodological and theoretical approaches from studies of attitudes toward advertising in
general or attitudes toward advertising in a specific medium, such as television.
One focus of recent Internet advertising studies is attitudes toward Internet
advertising in general. Schlosser, Shavitt, and Kanfer (1999) found that overall attitudes
toward Internet advertising were mixed, with approximately one third of the sample
feeling positive, one third feeling negative, and the remaining one third feeling neutral.
When compared to a demographically-similar samples perceptions about advertising in
general, fewer respondents felt positive toward Internet advertising than advertising in
general (Schlosser, Shavitt, & Kanfer, 1999). Previte (1998) found that 54% of


54
respondents agreed that online advertising was a good thing, 47% disagreed that their
opinion of online advertising was unfavorable, and 38% liked online advertising.
Some studies have incorporated belief dimensions from previous studies of
attitudes toward advertising in general. For example, Schlosser, Shavitt, and Kanfer
(1999) examined five dimensions of attitudes toward Internet advertising including
utility, indignity, trust, price perceptions, and regulation. They concluded that utility
(comprised of the traits of informative, entertaining, and useful for making decisions)
explained 43% of the variance in overall attitudes toward Internet advertising.
Ducoffe (1996) used a scale with the dimensions of informativeness, entertainment,
and irritation to determine perceived online advertising value. While the correlations
between these three dimensions and perceived value were all significant, the relationship
between informativeness and perceived value was the strongest. Furthermore, Ducoffe
(1996) found a positive and significant correlation between advertising value and attitude
toward online advertising.
Another focus of these studies is the relationship between attitudes toward online
advertising and attitude toward the ad. Cho (1999) found that subjects with more
favorable attitudes toward Web advertising overall had a more favorable attitude toward a
specific banner ad.
Advertising attitudes and clicking behavior have been examined as well (Brill,
1999; Cho, 1999). Cho (1999) studied the relationship between attitudes toward online
advertising in general and clicking behavior. He found that the three of the five belief
statements used to assess overall attitude toward Web advertising were capable of
discriminating between subjects with a high intention to click through a banner ad and


55
those with a low intention. The discriminating belief statements included the following:
Web advertising supplies valuable information, Web advertising is necessary, and Web
advertising is valuable. Brill (1999) found that consumers who had clicked on specific
banner ads had more favorable attitudes toward the banner ad and higher purchase
intentions toward the products or services advertised in the banner ad than for unclicked
banner ads.
An analysis by Briggs and Hollis (1997) focused on the influence of banner ads on
consumers attitudes and behavior. They found that for five of the six banner ads that met
the threshold on brand perception items, consumers exhibited a significant positive
change in attitudes as a result of exposure to the ads.
The above discussion illustrates a recent focus of attitudes toward advertising
literature on attitudes toward online advertising. In examining belief dimensions of online
advertising attitudes and demonstrating the relationship between attitude toward online
advertising and attitude toward the ad, researchers have expanded the applicability of the
attitudes toward advertising construct.
While several studies have examined attitudes toward Internet advertising
(Ducoffe, 1996; Mehta & Sivadas, 1995; Schlosser, Shavitt, & Kanfer, 1999), fewer have
distinguished among the various online advertising formats. Previous studies on Internet
advertising often either considered attitudes toward online advertising in general
(Ducoffe, 1996; Schlosser, Shavitt, & Kanfer, 1999) or examined one format of online
advertising (e.g., newsgroup and e-mail advertising (Mehta & Sivadas, 1995)). Others
have compared one online ad format to advertising formats in traditional media (Dynamic
Logic, 2001b) or compared two or more online ad formats (Dynamic Logic, 2001b;


56
Harris Interactive, 2001; Statistical Research, 2001). No study has attempted to
understand the range of dimensions that influence attitudes toward various online
advertising formats or the impact of attitude toward online advertising format on other
variables.
Studies of attitudes toward Internet advertising often ask respondents to respond to
survey items with all online advertising formats in mind (e.g. Ducoffe, 1996; Schlosser,
Shavitt, & Kanfer, 1999). In the studies by Ducoffe (1996) and Schlosser, Shavitt, and
Kanfer (1999), the researchers did not define the range of online advertising formats for
the respondents. In the Schlosser et al. study, Internet advertising was defined as any
form of commercial content available on the Internet that is designed by businesses to
inform consumers about a product or service (1999, p. 36). As a result, respondents
almost certainly answered with unique representations of online advertising in mind. In
addition, although these studies collected data on respondents definitions of online
advertising, no comparisons were made between these conceptualizations and overall
attitudes.
Other studies have focused on only a small subset of online ad formats. Mehta and
Sivadas (1995) concluded that consumers held unfavorable attitudes toward advertising
on newsgroups and via e-mail, regardless of the degree of relevance of the message to the
special interests of the group. Briggs and Hollis (1997) and Cho (1999) focused
specifically on banner advertising. While Briggs and Hollis (1997) considered attitude
toward a banner ad as an independent variable and studied its effect on brand attitude,
Cho (1999) studied the influence of attitude toward Web advertising in general on


57
attitude toward a banner ad and clicking intention. These findings of these studies may be
limited by the narrow focus.
A study by Statistical Research (2001; Jackson, 2001b) compared consumer
attitudes toward banner ads to attitudes toward pop-up ads. Respondents were more likely
to agree strongly or somewhat that they notice pop-up ads more than banner ads (76% vs.
69%) and that pop-up ads interfere with reading or using a Web page (84% vs. 54%).
Respondents were also more likely to disagree strongly or somewhat that companies that
use pop-up advertising are market leaders more so than companies that use banner
advertising (57% vs. 48%).
A study by Harris Interactive (2001) compared Superstitial advertising to
television advertising in terms of some classic communication research measures,
including recall, communication, and persuasion. The study found that for the three ads
tested, Superstitials communicated the copy points as well or better than television ads.
Two of the three Superstitials tested were as likable as the television commercials.
Intentions to use, buy, or consider the brand were comparable for both Superstitials and
television commercials in all three cases. Finally, brand recall for Superstitials was
slightly lower than that for television ads (81% vs. 93%).
The Interactive Advertising Bureau examined the use of the large rectangle ad
format in a study for Coca-Cola (Lefton, 2001b). The ad showed a lift in message
association by 56%, brand favorability by 7%, and purchase intent by 5% (Lefton,
2001b).
A study by Dynamic Logic (2001b) compared attitudes toward a number of online
ad formats. Over half of the respondents had a positive attitude toward banner advertising


58
(53%), followed by skyscraper ads (35%), large rectangles (17%), pop-ups (6%), and
interstitials (3%). This study also examined attitudes toward pop-up advertising and
traditional formats of advertising. Newspaper, magazine, radio, and billboard advertising
were found to be more desirable than pop-up advertising, while telemarketing, direct
mail, and television advertising were less desirable. While more comprehensive in terms
of formats than other studies, the Dynamic Logic study lacked a theoretical emphasis and
did not measure other important variables, such as Aat¡ and online ad perceptions.
Studies measuring attitudes toward online advertising in general are often too broad
to provide practical value to the advertiser. Because each online ad format possesses
distinctive features, attitudes toward online advertising could differ depending on the
users perception of what constitutes online advertising. Furthermore, the findings of
studies that focus on only one online ad format are not generalizable to other online ad
formats. As demonstrated, a review of the literature reveals no comprehensive study of
attitudes toward specific online advertising formats within a theoretical model of
advertising.
Although such a study has yet to be published, researchers are raising questions
about the relationship between attitude toward the online ad format and attitude toward
the ad. As previously mentioned, Rodgers and Thorson (2000) included ad formats and
attitude toward the ad in their Interactive Advertising Model, but did not test this
relationship. Schumann, Artis, and Rivera (2001) suggested a number of research
questions for future research including What negative influences on consumer
perceptions are likely to arise from interactive advertising formats? and Which
interactive media formats will best facilitate relationship management?


59
Advertising on the Internet is still evolving, manifesting itself in a variety of
formats, from banner ads to pop-ups to Webmercials. The Internet provides a more
versatile medium for advertising than traditional vehicles, and this versatility has led to
the development of the varied online advertising formats. While the Internet is an
appropriate context to study attitude toward ad format, it is also critical that attitudes
toward online formats are thoroughly examined. With the seemingly limitless
possibilities for online advertising formats, an understanding of consumer attitudes and
belief dimensions can certainly inform the future development of online advertising.
Proposed Model
The Interactive Advertising Model developed by Rodgers and Thorson (2000)
integrates the function of the Internet for consumers (i.e., consumer-controlled aspects)
and the structure of Internet ads (i.e., advertising-controlled aspects) to suggest consumer
responses, which include, among others, the formation of attitude toward the ad. One of
the advertiser-controlled Internet ad structures in the model is ad formats, such as
banners, interstitials, and sponsorships (Rodgers & Thorson, 2000). Another is ad
features, which are objective (i.e., advertiser-controlled) and subjective (i.e., consumer-
controlled) variables. The objective ad features for the Internet include color, animation,
and audio, while the subjective ad features include exciting, interesting, and boring
(Rodgers & Thorson, 2000).
This model has two implications for the current study. First, this model suggests a
relationship between ad format and attitude toward the ad. Second, this model
acknowledges the role of ad features or perceptions in attitude formation.
The foregoing discussions of the Interactive Advertising Model (Rodgers &
Thorson, 2000), the structural model of the antecedents to attitude toward the ad


60
(MacKenzie & Lutz, 1989; Lutz, 1985), and the literature of attitude toward advertising,
attitude toward advertising in a media vehicle, and attitude toward online advertising
provide a foundation for understanding how attitude toward online ad format may fit into
the existing attitude toward the ad model. Figure 2-2 illustrates the structure of a
subsection of the proposed model.
Figure 2-2. Proposed Structural Model of Aad Formation (showing two antecedents) in an
Online Advertising Context
Attitude toward online ad format is proposed as an antecedent to attitude toward the
ad. Figure 2-2 illustrates two antecedents for Aa(i: attitude toward online ad format and
attitude toward online advertising. The variable of attitude toward online advertising
serves to separate attitudes toward all advertising from those only related to online
advertising. As a relatively new form of advertising using a medium unlike other media,


61
online advertising may produce attitudes that are distinct from attitudes toward
advertising in general as found by Schlosser et al. (1999).
Underlying attitude toward online ad format are perceptions of online ad formats.
Just as attitude toward the ad is determined by ad perceptions (MacKenzie & Lutz, 1989),
attitude toward online ad format is predicted to be determined by online ad format
perceptions. Because these perceptions may parallel many of the perceptions of
advertising, a thorough discussion of these perceptions or beliefs was provided. This
research will identify other possible belief dimensions for the various online advertising
formats.
Furthermore, this model proposes that attitude toward online ad format is
influenced by attitudes toward online advertising. In addition, a users attitude toward the
Internet may influence attitude toward online advertising formats.
For advertising hosted on a Web site, attitude toward a Web site may influence
attitude toward the ad format. This relationship is suggested by previous research that
found a strong and significant correlation between an attitude toward a television
program and attitude toward television advertising, even after controlling for
demographic variables (Alwitt & Prabhaker, 1992).
Because the current interest is focused on attitude toward the online advertising
format, only a subset of the entire Aaij model was tested. The subsequent findings should
provide a framework for further research into other parts of the model.
Conclusion
This chapter presented the Aad model and then examined the research on attitudes
toward advertising in general in more detail. Recent trends in research on attitudes toward
advertising were also addressed, including the emphasis on understanding attitudes


62
toward advertising in a specific medium and attitudes toward online advertising. Finally,
this review described how the proposed conceptattitude toward online advertising
formatfits into the existing model and suggested hypotheses to be tested.
Chapter 3 discusses the first study in this research. This study used a qualitative
approach to derive perceptions of specific online advertising formats and determine
which formats should be included in a quantitative study that will test these relationships.


CHAPTER 3
STUDY 1
Purpose
The purpose of Study 1 was to use qualitative research to investigate the
determinants of attitude toward online advertising format, with special emphasis on
defining the dimensions of ad format perceptions, and to uncover online ad formats
appropriate for further study.
Research Questions
The research questions guiding this study were as follows:
1. What online advertising formats should be included in a study of attitudes toward
online ad formats?
2. What are the online ad format perceptions underlying online ad format attitudes?
Critique of Methodology in Previous Research
The perceptual dimensions underlying advertising attitudes and the items used to
measure them have often been constructed through reviews of previous studies rather
than through exploratory methods (ODonohoe, 1995). The influential study published by
Bauer and Greyser (1968) has historically been the basis for many perceptual inventories.
The use of items from previous studies offers the advantages of replication and
continuity.
While the precedent has been to adapt previous perceptual dimensions to the area
of study, the validity of the measures relevant to a particular area (e.g., online
advertising) may be improved by using exploratory research, such as focus groups or
interviews, to derive and define the appropriate dimensions (Churchill, 1979). For
63


64
example, Muehling (1987) and Pollay and Mittal (1993) incorporated thought-listing
techniques and open-ended questions to derive perceptual dimensions rather than relying
solely on previous research.
Perceptual dimensions from previous studies of attitudes toward advertising could
have been applied to a study of attitude toward online ad format. However, because
attitude toward the format is a newly-considered construct, it was important to enhance
the validity of the measures to be used by conducting preliminary qualitative research.
Method
Study 1 included depth interviews with industry experts and experienced online
users to explore online ad format perceptions. The literature review (Chapter 2) identified
perceptions of advertising in general or advertising in a specific medium. The purpose of
this review was to form a foundation of understanding advertising perceptions and for
comparison purposes following the depth interviews.
Depth Interviews With Industry Experts
Depth interviews with industry experts provided insight into the online advertising
formats that are most important, prevalent, distinct, and emerging, as well as the
perceptual dimensions on which the various online ad formats can be distinguished.
Sample. A total of 34 online advertising experts were identified representing
academe (6) and the advertising industry (26). Advertising academicians were selected
from the set of authors of papers or articles on the topic of online advertising published
during the past three years in the Proceedings of the American Academy of Advertising,
the Journal of Advertising, the Journal of Interactive Advertising, and the Journal of
Advertising Research. Practitioners were selected from those who either wrote or were
quoted in trade publication articles about online advertising. In addition, industry


65
members of the American Academy of Advertising were contacted for referrals and a
message was posted on the Online Advertising Discussion List to solicit additional
prospects.
Eleven members of the advertising community, including academicians and
practitioners, were interviewed. Of those in academe, five were contacted and three
completed the interview. Of those in industry, 11 were contacted and 8 completed the
interview. Sixty-nine percent of the contacts made resulted in a completed interview.
The academe participants represented the fields of marketing (2) and advertising
(1). The industry participants included three who work for research organizations, one
Web site advertising account director, two interactive creative directors, and two former
employees of online advertising networks.
The selected individuals were contacted by e-mail and invited to participate in this
research. The informed consent form was either faxed or sent via e-mail. The interviews
were conducted by phone and lasted approximately 20 minutes to one hour.
Measures. The depth interviews with industry experts served to narrow the online
ad formats that should be considered for further research to facilitate the later collection
of detailed data on online advertising formats and determine online ad format
perceptions.
Participants were asked to list prevalent online ad formats. They were also asked to
name formats that are and will be important in the future, should be included in an
attitude study, and are most similar or dissimilar, with special emphasis on the
dimensions that differentiate the formats. Participants were also asked to describe their


66
opinions of various online advertising formats. A discussion guide for the interviews with
industry experts is included in Appendix A.
Depth Interviews With Experienced Online Users
Depth interviews with experienced Web surfers were used to further develop a
typology of the dimensions of online ad formats and determine user familiarity with the
range of online advertising formats.
Sample. Experienced Web surfers were located through e-mail recruiting.
Seventeen students from a large southern university and six non-students from a southern
metropolitan area were screened for the interview. The screening process involved asking
questions about familiarity with online advertising formats and the amount of time spent
surfing the Web during the typical week. Prospective participants who exhibited the
highest levels of familiarity with multiple online advertising formats and spent the
greatest amount of time online were selected based on the assumption that they would be
able to discuss online advertising formats more knowledgeably, thereby producing more
valuable data. To somewhat disguise the purpose of the study prior to the actual
interview, prospective participants were also asked to name three Web sites they
regularly visit and up to three sites from which they have made an online purchase.
Of those recruited, six students and four non-students qualified to participate in the
interview. All students who were interviewed reported surfing a minimum of eight hours
per week (M = 10.8). All non-students except one estimated that they spend at least 20
hours per week surfing the Web, while one reported spending approximately 45 hours per
week surfing. All participants were familiar with at least three formats of advertising
prior to the interview.


67
Once an individual qualified to participate, an appointment for the hour-long
interview was arranged. Participants were paid $25 for their participation.
Stimuli. Stimulus ads were selected from the advertising displayed on several
popular Web sites, as well as various online galleries, collections, and portfolios. Table 3-
1 lists the advertisers used to illustrate each of the formats. The stimuli represent a broad
range of online advertising formats mentioned by Internet advertising experts including
banners, buttons, floating ads, pop-ups, interstitials, large rectangles, skyscrapers, and
Top Roll.
Table 3-1. Advertisers Represented in Stimulus Ads
Online Advertising Format
Advertiser
Banners
Apartmentguide.com, Casino on Net, UBid
Buttons
Amazon, Staples, Wal-mart
Floating ads
Circuit City, Emirates Airlines, Boston Red
Sox, ING
Pop-ups
Air Force, Nikon, Ford Expedition
Interstitials
Glaxo, Casino on Net
Large rectangles
Absolut, Dell, IBM
Skyscrapers
Best Buy, Classmates
Top Roll
Ford Focus, Coca-Cola
During the interview, a laptop computer was used to demonstrate online ad
formats. Ads were shown in the context of a Web site to simulate an actual ad
impression.
Measures. Participants were first asked about their general impression of online
advertising. The interview also tapped specific online advertising formats to determine


68
familiarity with various online advertising formats, opinions of these formats, and the
differences among the formats.
Participants were then asked to focus specifically on one ad format. Three
examples of each format were presented for illustrative purposes. Thought-listing was
implemented at this point. This approach has been applied successfully in the study of
advertising (Batra & Ray, 1986; Lutz & MacKenzie, 1982) and more specifically, to the
study of attitudes toward advertising in general (Muehling, 1987).
Participants were invited to read the standard thought-listing instructions (Cacioppo
& Petty, 1981) and were given two minutes to complete each thought-listing exercise.
They were instructed to write their thoughts about each online ad format as it was
presented. The most prevalent thoughts were considered appropriate for further analysis.
Participants were also asked to describe what they like and dislike about the ad
format, as well as their opinion of Web sites that use the ad format. This process was
repeated for a total of five online advertising formats. Finally, participants were asked
describe the similarities or dissimilarities among various online advertising formats.
Questions used in the depth interviews with experienced Web users are included in
Appendix B.
Procedure for Selecting Online Advertising Formats
Four criteria were used to determine the inclusion of an online advertising format in
future studies. The ad formats chosen can be described as prevalent, important,
distinctive, or emerging, with many of the ad formats representing several of these
categories.
First, only the most prevalent online ad formats were considered. These formats
included those mentioned by Web surfers during unaided recall, those that Web surfers


69
were familiar with during aided recall, and formats cited as the most prevalent by
industry experts. These formats were also compared to those representing the highest
percentage of online creative elements as reported by AdRelevance (2003) and online
advertising revenue as reported by PricewaterhouseCoopers (2002) in the IAB Internet
Advertising Revenue Report.
Second, important ad formats were considered for inclusion. To determine the
important advertising formats, advertising experts were asked which formats should be
included in a consumer attitude study about online advertising formats.
Third, to further narrow the possibilities, only distinct advertising formats were
selected. Therefore, if two formats are virtually indistinguishable to Web surfers or the
experts, one was dropped from further study. Advertising experts were asked to describe
various categories of advertising formats. Experienced Web surfers were asked to
compare and contrast several formats.
Finally, emerging online ad formats cited by industry experts were considered. The
goal of this selection process was to determine five to eight prevalent, distinct, important,
and emerging online ad formats, as this number should be manageable for a later
quantitative study.
Format Selection Results
From the experienced Web surfer interviews, banners and pop-up ads emerged as
the two most frequently cited formats in terms of unaided recall. Almost all participants
mentioned pop-ups during unaided recall of online advertising formats and most
mentioned banner ads. Participants were familiar with most of the formats demonstrated.
Table 3-2 illustrates how the formats ranked in terms of unaided recall and recognition.


70
The ad formats with the most mentions during the interviews with Internet
advertising experts included banners, pop-ups, pop-unders, skyscrapers, large rectangles,
floating ads, sponsorships, and interstitials. Other ad formats mentioned included top
Rolls, jump pages, Superstitials, fixed logos, buttons, towers, Web sites, search engine
listings, electronic mailing lists, text links, streaming media, and e-mail.
Table 3-2. Unaided Recall and Recognition of Online Ad
Formats by Experienced Web Surfers {N= 10)
Format
Unaided recall
N
Recognition
N
Pop-up
9
10
Banner
7
10
E-mail
4
*
Pop-under
2
10
Floating ads
2
8
Instant messaging
1
*
Tower
1
*
Large rectangle
1
10
Button
1
10
Contextual
1
6
Skyscraper
1
10
Interstitial
0
9
Top Roll
0
8
Sponsorship
0
4
*Not demonstrated.
The IAB Internet Advertising Revenue Report conducted by
PricewaterhouseCoopers reported that the two formats gamering the highest percentage


71
of revenue for the first six months of 2002 were banners and sponsorships
(PricewaterhouseCoopers, 2002). Banners represented 33% of online banner revenue and
sponsorships represented 24% (PricewaterhouseCoopers, 2002). Interstitials and rich
media ads (e.g., floating ads) each represented 3% of revenue (PricewaterhouseCoopers,
2002).
In contrast to PricewaterhouseCoopers method of calculating the proportion of
total online advertising revenues each format contributes, AdRelevance bases its data on
the total number of creative elements. According to AdRelevence data (2003) for the
week of April 28, 2003, banners were the most prevalent online advertising format,
representing 33% of online advertising elements. Including half banners increases this
percentage by 4% (AdRelevance, 2003). Skyscrapers also represented a high percentage
of online advertising elements at 17% for standard skyscrapers, wide skyscrapers, and
vertical banners combined (AdRelevance, 2003). Buttons represented 14% of elements,
and squares and medium rectangles totaled 10% (AdRelevance, 2003).
When asked what advertising formats should be included in a consumer attitude
study about online advertising formats, advertising experts were most likely to mention
banners, pop-ups, pop-unders, skyscrapers, floating ads, and sponsorships. Other formats
with fewer mentions included Point Roll, Superstitials, large rectangles, and text links.
Advertising experts suggested the following categorization schemas: flat, animated,
or interactive ads; small, larger, or floating ads; ads contained within Web page or ads
outside of Web page. Both experienced Web users and advertising experts often
perceived advertisements that were integrated into the content of the Web page to be one
distinct group and advertisements that appeared over or under the content to be another.


72
In further categorizing ads that are integrated into page content, skyscrapers and large
rectangles were often perceived to be distinct from banners and other smaller ad formats,
such as buttons. Another category identified were ads that appeared in the place of
content, such as interstitials and Superstitials.
Using this framework, banners, large rectangles, skyscrapers, towers, and buttons
would fall into one category while pop-ups, pop-unders, floating ads, and Top Rolls
would be a separate category. Interstitials and Superstitials would constitute a third
category. Ads integrated into page content might be further classified as large or small.
Finally, emerging online ad formats cited by industry experts were considered for
inclusion. From the interviews with the advertising experts, floating ads were often cited
as an emerging format that will become more popular in the future. Larger sizes, such as
large rectangles, were also mentioned as a trend in online advertising.
Analysis of formats using these criteria produced six advertising formats that were
used in subsequent studies: banners, pop-ups, floating ads, skyscrapers, large rectangles,
and interstitials. All of these formats were mentioned the most often by advertising
experts, and banners and pop-ups had the highest unaided recall by experienced Web
surfers. Furthermore, floating ads and large rectangles were often cited as emerging
formats. Banners, pop-ups, floating ads, and skyscrapers were all mentioned by
advertising experts to be important to include in an advertising attitudes study. While
interstitials were not cited as important or emerging, they were often cited as prevalent by
advertising experts. In addition, they represent a unique category of ads that appear
between content and are distinct from other formats. Table 3-3 illustrates how these six
formats rate on the four decision criteria.


73
Table 3-3. Summary of Performance of Chosen Formats across Selection Criteria
Criteria
Banner
Pop-up
Skyscraper
Floating
Large
Rec
Interstitial
Prevalent
X
X
X
X
X
X
Important
X
X
X
X
Distinct
X
X
X
X
X
X
Emerging
X
X
At this point, it is important to note that although a number of advertising experts
considered sponsorships to be an important online advertising format, and sponsorships
represented the second highest percentage of online advertising revenue for the first half
of 2002 (PricewaterhouseCoopers, 2002), this format was not considered in subsequent
studies for two reasons. First, sponsorships are often comprised of other online
advertising formats. Second, because sites offer a wide variety of sponsorship
opportunities, there is no single definition of a sponsorship.
Other ad formats were dropped from consideration because they were not
distinguishable enough from another format. For example, while pop-under ads were
often cited as prevalent and important, this format is quite similar to pop-up ads.
In contrast, although skyscrapers and banner ads are similar in shape, skyscrapers
were included in the list of formats for future study. Banners were one of the first formats
to emerge online, while skyscrapers are a more tecent creation. For this reason, it is
possible that attitudes differ. In addition, some participants associated skyscrapers more
with large formats, such as large rectangles, and banners with smaller formats, such as
buttons. The placement of the ads also differs, with banners placed across the top of a
Web page and skyscrapers along the side.


74
Perceptual Dimensions of Online Advertising Formats
Online advertising perceptions emerged from an analysis of the responses to the
interview questions. These perceptions were then categorized into dimensions using
conceptual factor analysis.
Internet advertising experts mentioned a total of 40 unique perceptions in
descriptions of online advertising, which were used to define perceptual dimensions. A
conceptual factor analysis of the perceptions was performed by grouping similar (or
opposite) perceptions into the same category. Within each category, the perceptions are
either synonyms (or antonyms) or were used by participants to describe the same concept.
This analysis resulted in the categories presented in Table 3-4. An indication of the
incidence of mention for each category is also provided.
Web surfers mentioned a total of 84 unique perceptions in descriptions of Internet
advertising, which were also used create dimensions. Once again, a conceptual factor
analysis of the adjectives was performed in the same manner described previously. This
analysis resulted in categories presented in Table 3-5. Because of the vast number of
adjectives mentioned by Web surfers, an attempt was made to further refine the
categories developed from the data for the advertising expert sample. An indication of the
incidence of mention for each category is also provided.
Irritation
Annoying and irritating clearly emerged as the most common descriptors of
online advertising. This dimension was more generally described by advertising experts
with the following adjectives: annoying, interrupts, intrusive, abrupt, distracting, and
interferes.


75
Table 3-4. Descriptors of Online Ad Formats Used by Online Advertising Experts
Descriptors N
Annoying, Interrupts, Intrusive, Abrupt, Distracting, Interferes
Informational value, Content, Compelling message, Room for content
% of screen occupied, Position, Size of ad, Clutter, Obtrusive 6
Relevance, Targeted 5
Interactive, Involvement 5
Control, Forced vs. voluntary, Choice 4
Cutting edge, Different, Sophisticated, Innovative, Clever, Creative 4
Animation, Flashing, Static (ant.) 3
Enjoyable, Entertaining 2
Classic, Tasteful, Cordial 1
Copy heavy 1
Provides reward 1
Ubiquitous 1
Visual 1
Note. N = number of participants who mentioned at least one of the descriptors.
Other categories which may contribute to the annoyance of online advertising
include one referring to the clutter caused by online advertising (percentage of screen
occupied, position of ad, size of ad, clutter, obtrusive), one referring to the activity of
online ads (flashing, animated), one referring to the ubiquity of ads (ubiquitous), and one
referring to the ability of the user to control the surfing experience (control, forced,
voluntary, choice).


76
Table 3-5. Descriptors of Online Ad Formats Used by Experienced Web Surfers
Descriptors N
Animated, Flashy, Blinking, Movement, Hyperactive, Static (ant.) 10
Annoying, Bothersome, Frustrating 10
Disruptive, Distracting, Diverts attention, Distorts content, Gets in the 9
way, Takes over page, Takes up space, In your face/Out of the way,
Interferes with background, Intrusive
Inconvenient, Time-consuming, Quick (ant.) 9
Entertaining, Exciting, Fun, Appealing, Cool, Neat, Amusing 9
Catches attention, Holds attention, Eye-catching, Interesting, 9
Noticeable, Obtrusive, Blends with site (ant.), Easy to ignore (ant.),
Contrasts with background
Innovative, Inventive, Clever, Cutting-edge, Different, Creative 8
Forced exposure, Wanted/unwanted, Control, Removal requires action 7
Cluttered, Overbearing, Pervasive, Obtrusive 6
Cool graphics, Good pictures, Images of product, Interesting graphic 6
Bold, Bright colors, Colorful 5
Audience-driven, Relevant to content 5
Big, Small, Size, Space 4
Simple, Plain 4
Beneficial, Useful offerings, Pointless (ant.) 4
Cute, Eyesore (ant.) 3
Informative 3
Separate from page, On page 3
Easy to read, Too many words (ant.) 2
Respectful, Goochbad etiquette 2
Extravagant, Dynamic 2
Interactive, Involvement 2
Sound 2
Repetitious 1
Deceptive 1
Note. N= number of participants who mentioned at least one of the descriptors.


77
As mentioned previously, the volume of descriptors mentioned by Web surfers
warranted developing several categories which may by encapsulated into the broader
category of annoying from the general descriptions of annoying, bothersome, and
frustrating to more specific segmentations. These segmentations include one that refers to
the disruption of the surfing experience (disruptive, distracting, diverts attention, distorts
content, gets in the way, takes over page, takes up space, in your face/out of the way,
interferes with background, intrusive, cluttered, overbearing, pervasive).
Another segmentation of annoyance refers to the activity of the ad itself, which
includes such descriptors as animated, flashy, blinking, movement, and hyperactive. Yet
another segmentation refers to the time involved in dealing with online ads as expressed
by the descriptors of inconvenient and time-consuming. Finally, irritation may be caused
by the fact that online advertising is often forced onto the user, which was described as
forced exposure, wanted/unwanted, control, and requires action to remove. In fact, Li,
Edwards, and Lee (2002) found the measure of intrusiveness to be independent from that
of irritation, which provides some evidence for the separation of irritation and intrusion.
The finding that online advertising is defined by or can be described by its level of
irritation or annoyance is consistent with that of Uses and Gratifications research
(Eighmey & McCord, 1997; Plummer, 1971; Schlinger 1979) and attitude toward
advertising studies (Ducoffe, 1995, 1996). Irritation is such a pervasive issue in
advertising that this characteristic has also merited studies about it exclusively, as
demonstrated by the advertising clutter research (Elliott & Speck, 1998; Ha, 1997).
Entertainment
Online advertising was also described by participants in terms of its entertainment
value. These categories ranged from the general category of entertainment (entertaining,


78
enjoyable, exciting, fun, appealing, cool, neat, amusing) to more specific categories
referring to activity of the ad itself (animation, flashing, blinking, movement,
hyperactive), to the fact the ad is eye-catching (catches attention, holds attention, eye
catching, interesting, noticeable, obtrusive, contrasts with background), or to the
entertainment value in the graphics of the ad (cool graphics, good pictures, images of
product, interesting graphic).
As noted in Chapter 2, perceptions of the entertainment dimension of advertising
have been considered in previous studies (Alwitt & Prabhaker, 1992, 1994; Bauer &
Greyser, 1968; Ducoffe, 1996; Lee & Katz, 1993; Mehta, 2000; Mittal, 1994; Pollay &
Mittal, 1993; Schlosser, Shavitt, & Kanfer, 1999; Shavitt, Lowrey, & Haefner, 1998).
Information
While the information dimension clearly emerged from the interviews with
advertising experts, Web surfers were less likely to mention it. While only three Web
surfer participants noted the informativeness of online advertising, advertising experts
described information in terms of informational value, content, compelling message, and
space in ad for content.
Because many of the advertising expert participants were responsible for creating
or selling online ads, they should be more attuned to the content possibilities of online
advertisements, providing a possible explanation their emphasis on information. The Web
surfer participants may have been more focused on the design or behavior of the online
ads during the interview, particularly if the advertised product was not of interest to them.
While this dimension was not described in great detail by Web surfer participants,
its mention by advertising experts and its dominance in both Uses and Gratifications
research (Eighmey & McCord, 1997; Plummer, 1971; Schlinger, 1979) and attitudes


79
toward advertising research (Alwitt & Prabhaker, 1992, 1994; Ducoffe, 1996; Lee &
Lumpkin, 1992; Mehta, 2000; Mittal, 1994; Muehling, 1987; Pollay & Mittal, 1993;
Schlosser, Shavitt, & Kanfer, 1999; Shavitt, Lowrey, & Haefher, 1998) warrants its
inclusion in further studies.
Informativeness is also linked to relevance, as determined by Plummer (1971)
who identified informativeness and personal relevance as a factor explaining attitude
toward television commercials. The relevance of an online ad was mentioned by
participants who used such adjectives as audience-driven, relevant to content, and
targeted to describe this dimension. Web surfers also referred to online ads as beneficial
or having useful offerings, which can also be incorporated under this dimension.
Novelty
The novelty dimension also emerged from the qualitative research. Advertising
was described as cutting-edge, different, sophisticated, innovative, clever, creative, and
inventive. Both Plummer (1971) and Schlinger (1979) identified this dimension in their
studies of attitudes toward television commercials.
Interactivity
The interactivity of or involvement with online ads also surfaced during the
interviews. Interactivity has been defined as the extent to which users can participate in
modifying the form and content of a mediated environment in real time (Steuer, 1992, p.
84). This characteristic was addressed more by advertising experts, which may be
explained by the experience of many of the experts with the sophisticated technologies
used to create interactive online ads. Again, this dimension has appeared in Uses and
Gratifications studies as either involvement (Plummer, 1971) or interactivity
(Eighmey & McCord, 1997).


80
Composition
The final dimension is the look or composition of the online advertisement.
Web surfers defined this characteristic with descriptors referring to the colors of the ad
(bright colors, colorful, bold), the size (big, small), the simplicity (simple, plain), the text
(easy to read, too many words), or the overall appearance of the ad (cute, eyesore).
Industry experts also addressed the look of the ad to a lesser extent using descriptors such
as classic, tasteful, cordial, copy heavy, and visual.
This dimension reflects the instrument of advertising, which Sandage and
Leckenby (1980) differentiated from the institution of advertising. While institution
refers to the purpose and effects of advertising, instrument refers to advertisings
executional properties.
Table 3-6 lists these dimensions and their subdimensions and corresponding
descriptors. Several descriptors were selected from each of these dimensions to represent
the dimension in the next stage of research. For the annoyance dimension, the descriptors
of annoying, intrusive, overbearing, and disruptive were selected. To represent the
entertainment dimension, the descriptors entertaining, amusing, and eye-catching were
selected. Information, useful, and beneficial were chosen to represent the information
dimension. Innovative, different, and sophisticated were selected for the novelty
dimension. Finally, attractive and elaborate (antonym of plain) were chosen to represent
the composition dimension. Because the focus of future studies will be collecting data on
subjective dimensions, the interactive dimension was disregarded as it tends to be more
objective.


81
Table 3-6. Summary of Dimensions and Corresponding Descriptors
Dimensions
Subdimensions
Descriptors
Annoyance
General
Annoying, bothersome, frustrating
Disruption of
experience
(Intrusion)
Interrupts, abrupt, disruptive, distracting, diverts
attention, intrusive, interferes, distorts content,
gets in the way, takes over page, in your
face/out of the way, interferes with background
Clutter
Percentage of screen occupied, position of ad,
size of ad, clutter, obtrusive, takes up space,
overbearing, pervasive
Activity
Flashing, animated, flashy, blinking, movement,
hyperactive
Ubiquity
Ubiquitous
Ability to control
Control, forced, voluntary, choice, forced
exposure, wanted/unwanted, requires action to
remove
Time factor
Inconvenient, time-consuming
Entertainment
General
Entertaining, enjoyable, exciting, fun,
appealing, cool, neat, amusing
Activity
Flashing, animated, flashy, blinking, movement,
hyperactive
Eye-catching
Catches attention, holds attention, eye-catching,
interesting, noticeable, obtrusive, contrasts with
background
Graphics
Cool graphics, good pictures, images of
product, interesting graphic
Information
General
Informative, informational value, content,
compelling message, space in ad for content
Relevant
Audience-driven, relevant to content, targeted,
beneficial, useful offerings
Novelty
General
Cutting-edge, different, sophisticated,
innovative, clever, creative, and inventive
Interactivity
General
Interactivity, involvement
Composition
Colors
Bright colors, colorful, bold
Size
Big, small
Simplicity
Simple, plain
Text
Easy to read, too many words
Overall appearance
Cute, eyesore


82
Discussion
The depth interviews identified critical perceptual dimensions of online advertising
formats and informed the development of items to be used to measure each dimension.
The interviews also highlighted six online advertising formats worthy of future study.
Online Advertising Formats
The six formats selected were banners, pop-up ads, skyscrapers, large rectangles,
floating ads, and interstitials. These formats have often been included in research studies
either in combination, in isolation, or in comparison to a traditional medium, such as
television.
The Dynamic Logic (2001a) Ad Unit Effectiveness Study measured the
effectiveness of banners, skyscrapers, and large rectangles. The Advertising Reaction
Study also by Dynamic Logic (2001b) measured attitudes toward banners, pop-up ads,
skyscrapers, large rectangles, and interstitials. Attitudes toward pop-ups and banners have
been compared (Statistical Research, 2001). Other studies have examined the
effectiveness of banner ads (Briggs & Hollis, 1997; Cho, 1999; Gilliam, 2000; Morgan
Stanley, 2001), large rectangles (Lefton, 2001), or Superstitials (Harris Interactive,
2001).
Two of these formatsthe skyscraper and the large rectangleare part of the
IABs recommended universal ad package, which further validates their importance
(Elkin, 2002d). Furthermore, Nielsen//NetRatings reported that banners, rectangles, and
skyscrapers represented the highest percentages of online advertising impressions (Martin
& Ryan, 2003).
While floating ads have yet to be included in an attitude study, this format is
expected to attract the attention of consumers and researchers as it becomes more


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ATTITUDE TOW ARD THE ONLINE ADVERTISING FORMAT: A REEXAMINATION OF THE ATTITUDE TOW ARD THE AD MODEL IN AN ONLINE ADVERTISING CONTEXT By KELLI SUZANNE BURNS A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY UNIVERSITY OF FLORIDA 2003

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Copyright 2003 by Kelli Suzanne Bums

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Dedicated in loving memory to my grandmother

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ACKNOWLEDGMENTS I would like to acknowledge the dedicated professors at the University of Florida who guided me throughout this dissertation. I would like to thank Dr. Richard Lutz, who went above and beyond his duties as a professor in the Warrington College of Business to supervise and cochair a dissertation for a communications student. His intellectual contributions and financial resources were critical to the successful completion of this dissertation and are greatly appreciated. I would like to thank my dissertation chair, Dr. John Sutherland, who contributed to this study through his incredible facility for data analysis and knowledge of research methods. Committee members Dr. Marilyn Roberts, Dr Joseph Pisani, and Dr. Bart Weitz also deserve commendatio n for their feedback, support, and participation. My appreciation extends to Dr. David Eason and Dr. Bob Wyatt for inspiring me as a graduate student at Middle Tennessee State University and for later hiring me. I would like to thank my husband, Corey, who believed in me and supported my dream. I am also grateful to John and Anne Berg, who generously and warmly welcomed me into their home and lives for two years. I wo:ild like to thank my parents for instilling in me all the values that made this possible and for giving me so mai1y opportunities to lead a fulfilling life. Finally, I would like to acknowledge my son, Griffin, who arrived duri11g this jotrrney and added to the adventure IV

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TABLE OF CONTENTS Page ACKN"OWLEDGMENTS . ....................................... .. .. ...... . .... . ...... ........ .. . .. ..... .. .. .. iv LIST OF T .AB LES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . x LIST OF FIG~S ........... ........ ....... .. ...... .. ....... ..... .. .... . . .. ........ .................... I xv .ABS TM CT . ..... .... .. ...... .. .... .. .. .... .. . ..... .. . .. . ........ ................ .. .......... ... ....... .. . ......... xvi CHAPTER 1 IN"T R OD U CTI ON .. .... .......... .. .... .. .. . .. .... .......... .... .. . ...... .. .. ...... .. ... . .......... .. ..... ... . 1 The Ori gins of Online Advertising .............................. .. .. .......... . .. .. .. . .. ..................... 2 Online Advertising Today .... .. . .............................................................................. .. .. 6 Current Online Advertising Formats ...... ........ ... .... .. . . ...................................... 6 Demand for New Online Advertising Formats .. ... . ........................................... 11 Online Adve11ising Mix . .. . ... . .. .... .. . .. .. . .. . .. .... .. .. . . . .. .... .. .... ...... ...................... 12 Online Advertising Spending . .. . .. . ........................................................................... 13 Online Advertising Effectiveness . ....... .. . .. . .. .. . .. .. . .... . . .... . .... . .. . . .. . .. .. .. .. . .. 15 Statement of Purpose .............. ..... . .. . .. .. . .. . ... .................. ... . .. ... .. . .... .... .............. 18 Im,portance of the Study .. .. .... .. .. . .. .. ........................................................................ 19 Outline . . .. ...... .. . ..... .... .. .. .. .. . .. .. ... ... ... .................................................... ........... 20 2 LITERA. T~ REVIEW ........................... .. . .. .. . .... . .. . . ........... ...... ....... . .. .. .. . .. . 21 Atti tu.de Toward the Ad ............................. . .. . ..... ... .... .... .... . . .... . ...... .. .... .. ..... .. . 23 Attitude Toward the Ad as a Mediator .. .......... . ...... .... . . .. . .... . .. .. . .. .. .. .. .. 24 Likability Studies .......... . .. ..... .................. . .. . .. ......... . . ... .... .... ..... ...... .... .. 26 Attitude Toward th e Ad Model .. .. .... .... .. . .. . .. .... . .. ... ... .... .. . ................ ....... 27 Attitudes Toward Advertising in General . .... .. .......... . . .. . . .. .. .. . .. ... .. . .. .............. 31 Beliefs About Advertising in Gene1al .. .... .. .. . .. ........... . .... .... ............................... 34 The Relationship Between B e li efs and Attitudes .......... . .. ... ............................. 35 Categorizing Beliefs About Advertising ... ............. . .................... .. . .. ..... .. .. .. 36 Belief and Attribute Dimensions Included in Previous Studies ... .. . ............... .. 37 Attitudes Toward Advertising in a Specific Media Vehicle . .... . .. ... . .. . .. ........... .. 48 Online Advertising Effectiveness .. ... ... . .... .. .. ... . .. .... . .. ... . .................................... 51 Effectiveness of Executional Elements .................... . . .. ... . .. . ........ .... .. . ...... .... 51 Online Consumer Behavior as a Measure of Effectiveness ....... ................... .... 52 Attitudes Toward Online Advertising .. .... .. .. . . .. .... ...... ........... ... .. ... ....... .... ..... .. ... 53 V

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3 4 Proposed Mod e l. .5 9 Conclu s ion ..... . . e t e e e e e e e t e t t e e t t e e t e t t e t e e t t t t t t e e e t e I t e e t t e t t t t t t t t t t t t t .6 1 ST'UDY 1 ..... .... .. .. .. .......... . .. .. .. . ..... .... .. . .. .. ... .. . .... . . .... . .. . .... . .. ... . ... . . .. . 6 3 Purpo s e .63 R es earch Que s tions ... . .. .. .. . .. .. . ... . .. .. ... .. . .. .. . . . .. . . .. . . .... . .. . ... .... .. . . .. ... ..... 63 Critique o f M e thodolog y in Pr e vious R ese arch .. . . .... .. . .. ... ...... .. ... . .. . .. . .. . .. .. ... . 63 M e thod .. . .. .. ....... . .. .. . .. .. .... . .... .... . .. .... .. . .. . .. .. .... .... .... .. . ..... . ....... . .. ..... ..... 6 4 Depth Interviews With Industry E x pert s .. ... .. . .. .... . .. . . . .... . . .. . .. . .... .......... . 6 4 Depth Interviews With Experi e nc e d Online Us e r s 66 Procedur e for Selecting Online Advertising Formats . .. . . .............. .. .. .. ... ..... ........ 68 Format S e l e ction Results 69 Perceptual Dimensions of Online Ad v ertisin g Format s .7 4 Irritation ... . . .... .. .. . .. .. .. .. . .. .. . .... . ...... . ... ... .. .. .. . .... . ... .. . . . .. . .. . . .. ..... ..... Entert a inm e nt Infor1n a tion N o v el ty In tera c ti vi ty . . . .. . .. . ...... ....... ..... . ..... .. . .. . .... .. ........ . .. . ... . . ... .... .. .. .... .. . 74 .77 .78 79 79 Composition t t t t t I t I t t I I I I t t 1 I t t f I f I I I t t t I f e t f f I f I I I I f t I t t I e I I I I I I I I t I t t t 80 D . lSCU S Sl on . .. . . .. ....... .. . ..... . .. .. .. .... . ... . .. .. .. ... ......... . ... ..... . ... ... .. ... .. .... .......... 82 Onlin e Adv e rti s in g Formats 82 Perceptual Dimension s 83 STUDY 2 .. . .. .. . ... .. .... ..... .. .... .. .. ....... .. .... .. . .. .. ... .. . . .. ........ . .... . .. ... ...... ...... 8 6 .86 Purpo se Hypothe s e s t t t t t I I t t t I I I I t t I f t t I I I I I I e I t t I t I I t I t I I I t t t I I t e I t I I t t e t t I I t I I t t t e t I e t I t 89 Method . ... t f e t t t e t t t I I I I I t I I t t I e I t e I t t I t I I I I I I I I I I I I I I I I I I I I t t t 90 t t t t I I I I I I I t I I I I f I I I I t I I I I t t I t t t t I I I t t I I I I I t I I t I I I I I I I I I t f I f f t I I I I I I I t I t I I I f Sample Procedure I I t I t I I I I e I I I I I I I t I I t t t t t t t t t t I I t t I I t t t 1 I I 1 t 1 t t 1 1 Stimulus Ads 90 9 0 9 1 Measures 9 1 Results .. . .. . .9 4 Sampl e D es cription Overall Data Structure .... .9 4 97 9 8 Verifi c ation of Measures Test-R e te s t Reliability .. .... .. . ..... ............ . .. . .. ... . ..... . ... .. . . ...... ..... ............... 99 Fa c tor Analysi s of Perceptual Items and Attitude M e asures . ... . . . .. .. .... ... ... 1 00 C orr e l a tions Amon g Variabl es for E ach F onnat .... . .. . ... .. ............. .............. . 1 07 Predictors of Attitude Toward the Online Ad Forn1at ... . . .. . ...... ............... ..... 11 3 Predi c tor s of Attitude To w ard the Ad 12 0 B e havioral Mea s ure s 123 Discu s sion . .. t 12 7 O v ervi ew 12 7 Interpretation of Re s ult s 128 Stud y L imitations 13 1 V I

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5 6 Implications for Online Advertising Tl1eory ... .. .... . ... .... . .. .... . ......... . .. ..... .. . 135 Implications for Online Advertising Industry 135 Future Research ............ . . .. .. ... .. ..... .... . .... .. ... . . .... . .. . . .. .. ........ .................. 135 Conclusion ..... .. .. .. . 136 ST"UDY 3 . . ...................... . .. .. .... .... .. . ....... .. .... .. .... ...... ........... . .. ... . .... .. .. .. .. .. 13 7 Purpose Hypotheses Method ..... Sample Procedure Stimulus Ads Measures Re s ults ....... Sample ...... ...................... ....... .. ... ... . .. .. . .. .. ..... ........... ...... .... ... . .. . .... ... ...... Attitude Toward Online Advertising ........... . ....... . . .. . . .. . .... ... .... .............. Perceptions of and Attitude Toward Online Advertising Format Relationships among Var i ables . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . Behavioral Moderators Discussion ..... Overview .. .. Interpretation of Results Study Lim i tatio n s Implications for Online Advertising Theory .. .. . .... .... . ..... . ... .. . .. .............. Implications for Online Advertising Industry Future Research 1 37 13 7 13 8 138 13 9 140 140 14 2 142 150 150 153 156 162 162 162 163 166 167 168 "IMPLICATIONS .. .. . .. . ........... ..... . .. .. . .. ..... ..... . .. .... . . .. . . ... .. . .. ........ .... ......... 170 Introduction .. . .. . 170 Results Overview 172 Future Re sea rch .. 174 Conclusion 17 6 APPENDIX A B INTERVIEW GUIDE FOR ONLINE ADVERTISING EXPERTS . .. . .. .... . ...... .. 177 Screener Informed Consent Interview Guide 177 177 179 INTERVIEW GUIDE FOR EXPERIENCED WEB SURFERS .. .......................... 1 8 1 Screener 181 Informed Co nsent .... .. . . . ... ........ .. . .. . .. .. .. . .. 18 2 Vll

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C D .Inte'fView Guide .. ..... ................. .. .... .... .......... .. . .. . .... ...... .... . .. ... . .... ......... .. ....... 18 3 ONLINE SURVEYS FOR STUDY 2 ... ... ... .. ... . .. .... . .... . .. ... .... .... . .. .. ........... 189 Version A . .. ..... 189 Introduction 189 Informed Consent Extra Cre dit 189 191 Surf m g the Web .... .............. .. .... . .. .. . .. .. ....... . ...... . .. . . .. ... ... .. . .. .. .. ..... .. 191 Advertising on the Web ....... .. .. . .. .. . .. .... ....... .. .... . ..... . . . ..... . ..... ............. 191 First On lin e Ad .............. .... ... ... .. . ... . .. . .......... .. . . .......... .. ... .. ... ................. . 192 Second Online Ad 195 Third Online Ad 198 Demographics . .. . .. ..... .. .. . .. ....... .. .. . .. . .. .. .. . .. .... . ...... . .... . ........ .... ......... 20 1 Conclusion ....... .. .. .... . .. .. . ... . .. .. .... .. .. ............ . ... . . ... .. . . .. . . .. . . . . .......... 202 Version B .202 Introduction 202 Inforrried Consent .202 Extra Credit 204 Surfmg the Web .... ... .......... .... .. .. . ..... ... .. ... ... . .... ... .... ........ .. ... .. ................ 204 Advertising on the W eh . .. . ........ .. .... . .. . .. . .. .. . .... . .. . .......... .... .... .. ........... 20 4 First Online Ad Second Online Ad Third Online Ad Demographic s Conclusion ..... ONLINESURVEYFORSTUDY3 Invitation Survey ............. . Introduction t t t Informed Consent t Esearch. com ID Advertising on the Web Format Introduction ... . First Online Ad Fo rmat Second Online Ad Format t t t t t t t t t t t t t t t I t t t I t t t I t I t t t t t t t t t t t t t t t Third Online Ad Fo rmat Pro gress Report Fourth Online Ad Forrnat Fifth On lin e Ad Format. Sixth On l ine Ad Forrnat Demographics Conclus ion .. .. Vlll .205 208 211 215 216 217 .2 1 7 .2 1 7 2 1 7 2 1 8 219 .2 19 .220 .221 .223 .225 .227 .227 .229 .231 .233 .235

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E FA C TOR ANALYS E S FOR PERCEPTUAL AND ATTITUDINAL MEASURES BY ONLINE AD FORM.AT . ........ . .. ....... . .. .. . .. ... .... .... .. ..... .... . . .. . ...... ....... 236 Analyses for Barmer Ads ... . ............. .. ....... . .. .. ............ ..... ... ............................ .. 236 Analy ses for Pop-up Ads . ... ... .. .. .... .. ...... .. . ..... .. . .. . .... . .. . ... .. . ... . .. ......... .. ... .... 238 Analyses for Skyscraper Ads . .. .. .. . ..... . . .. .. . .. . .. . ......... ... .. .. ... . . ................... .. 2 41 Analyses for Large Rectan g le Ads ... .. .. . .. .. .. ... .. ...... .. ... ........ .. ............... .. . .. .. ..... 243 Analyses for Floating Ads ...... ... .. .... .. .... .. .... ... ..... .. .. . . ............. ... ....... ... .. ............ 2 4 6 Analyses for Interstitial Ads ..... . ........ ....... ..... .. ... ....... . . .... .... ..... .. .. ................. 2 4 8 LIST OF REFERENCES . .... . .. .............. .... .. ....... . .. .. . .... . .. . . . ....... . . . . ....... .. .. .... .. 251 BIOGRAPHICAL SKETCH .... .. . .......... .. ....................... .. . .... . .................... .... .. ....... 264 IX

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LIST OF TABLES Table page 3-1 Advertisers Represented in Sti1nulus Ads ................................................................ 67 3-2 Unaided Recall and Recognition of Online Ad Formats by Experienced Web S-urfers (N= 10) . .................. .. . ..... ....... .. ....... .... .... .. .... ........ ... .... . . ................. 70 3-3 St1mmary of Performance of Chosen Formats across Selection Criteria ..... ........ . 73 3-4 Descriptors of Online Ad Formats Used by Online Adve1iising Experts ................ 75 3-5 Descriptors of Online Ad Formats Used by Experienced Web Surfers .. . .. . ... ...... 76 3-6 Summary of Dimensions and Corresponding Descriptors ....................................... 81 4-1 Demographic Characteristics of Respondents .... .. . .... . .... ... ........ .. . . .. .................. 95 4-2 Internet Usage Characteristics of Respondents . .. .. ... .... . ...... ...... . .. . ........... .... 96 4-3 Online Purchase Behaviors of Responde11ts ............................................................. 97 4-4 Verification of Commo11 Attitude Measures ............ ............. ........ ... ....... .. ..... ...... 99 4-5 Mean Ratings for Attitude Indices for Respondents who Completed Both Versions (n = 69) .................................................... ................................................................ 100 4-6 Summary of Factor Loadings for the Rotated Three-Factor Solution for Perceptual I terns .......... ....... .. .. ............... .. ..... ............ ..... . .. ........... . .. ... ............................ 1 02 47 Means, Standard Deviations, and Alphas for Three-Factor Solution ..................... I 03 4-8 Mean Scores for Attitude Indices (with Coefficient Alpha) for Each Online Ad Fonnat ......... . .................................................. .. ......... .. ....... .. .. .. ........ .. ........... .. ........... .................................................................. 104 4-9 Mean Scores for Perceptual Factor Indices (with Coefficient Alpha) for Each Online Ad Fonnat ................. .. ... ... ..... ............ .... ... .. ........................... .............................. 105 4-10 One-Way Analyses of Variance for the Effects of Format on Attitude and Perceptual Factor :In.dices ............................................... ... .. .................................................... .. ..... ... ....... .. ............................ 106 X

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4-11 Post-Hoc Comparisons of Attitude and Perce p tua l Factor Means Across Format Using LSD .. .......................................... .... .... .... .. . .. . . . .. . . .. . . .. . .... .. .. ....... .. 107 4-12 Intercorrelations for Attitude and Perceptual Factor Indices for Banner Ads ........ 108 4-13 Intercorrelations for Attitude and Perceptual Factor Indices fo r Pop Up Ads ....... 109 4 14 Intercorrelations for Attitude and Perceptual Factor Indices for Skyscraper Ads .110 4-15 Intercorrelations for Attitude and Perceptual Factor Indices for Large Rectangle Ads .......... ........... ......................... .... ..... ..... .... .... .. . . .. ... . .... . .. . . .. . .. .. . ... ... 1 1 1 4 16 Intercorrelations for Attitude and Perceptual Facto r Indices for Floating Ads ... .. 112 4-17 Intercorrelations for Attitt1de and Perceptual Factor Indices for Interstitial Ads ... 113 41 8 Regression Ana l ysis Summary for Variab l es Predicting Attitu d e Toward Banner Ads ...................... ............................................... ..................... ...... ....... .... .. . ... . 115 41 9 Regression Ana l ysis S u mmary for Variab l es P redicting Attitude Toward Pop Up Ads ...................... .. .... ....................................... ..................................................... 115 4-20 Regression Ana l ysis Summary for Var i ables Predicting Attitude Toward Skyscraper Ads .... .. . ... ...... .. ...... .. .. .... ... .... .. .... .. .... .. .. . .. . . .. . ... .. . . .. ... .. . .. ............ .. ... .. 116 4 21 Regression Ana l ysis Summary for Variab l es P r edicting Attitude Toward Large Rectangle Ads ....... .. .............. ... ........... . ........ .. ............ .. . .. ......... . .. .... .. ... . .. .. .. .............. 117 4-22 Regression Analysis Summary for Variables P redic ti ng Attitude Toward F l oating Ads ............................................................................. ........................................................................................ 11 7 4-23 Regress i on Analysis Summary fo r Variab l es Predicting Att itu de Toward Interstitial Ads ..... ... .. ... ...... ....... ... .. ..... .. .... .. ... .. .... .. .... .. ............................ .. ... .. ..................................................................................... 118 4 24 Summary of Significance of P r edictor V ai.-iables Across A l l Formats ............... .. 118 4 25 R egression Analysis Summary for Variables Predicting Attitude Toward Banner Ads .. .. ................. .. ................................................ ... . .. . .. .... . ....... . .. ... . .. .... ...... .. .................. 12 I 4-26 R egression Ana l ys i s Summary for Variab l es Predicting At t i tud e Toward Pop-Up Ads ...... ........... .......... .... .. . .. ..... .. ..................................................... .... .. ................ 121 4-27 Regression Ana l ysis Summary for Variab l es Predicting Attitude Toward Skyscraper Ads ............................... ... ... .... ..... .. .......... .. . .... ........................................ .... .. .. ... 122 4-28 Regression Analysis Summary for Variables Predicting Attitude Toward Large Rectangle Ads .. ..... .. ........... ................ .. ................ ..... .. .. . ............................................... 122 Xl

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4-29 Regression Analysis Summary for Variables Predicting Attitude Toward Floating Ads ....................... .................................................... . . .... ... ......... ... .... ..... .. ....... 122 4-30 Regression Analysis Summary for Variables Predicting Attitude Toward Interstitial Ads ................... . .................................................... . .... ...... . .... . .......................... 123 4-31 One-Way Analyses of Variance for Effects of Format Familiarity on Arormat ....... 124 4-32 Post-Hoc Compa rison s of Atarrnat Means Across Fonnat Familiarity Using LSD .125 4-33 Group Differences for Attitude Toward Online Ad Format Between Respondents Who Had Clicked Through on Certain Onli11e Ad Forrnats and Respondents Who Had Not Clicked Through ...... .. .. ....... .. . .. . .. .. . ................................................... 126 4-34 Post-Hoc Comparisons of Aforrnat Means Across Clickthrough Frequency Using LSD ..................... .. ............................... .. . .. .. .... . ...... . .. . ...................................... 126 4-35 Group Differences for Aronnat Between Respondents Who Had Later Visited Sites Advertised Using Certain Online Ad For1nats and Respondent s Who Had Not Later Visited Sites .................. ... .... . ... .... .. ....... .. ...... .. ...... .. .......... . ... .......................... 127 4-36 Regression Analysis Summary for Attitude Toward Large Rectan g le Ads for FirstTime Respondents .... .. . ........ . .. .... .. .. ............................................ . .. ...... . ........... 13 3 4-37 Regression Analysis Summary for Attitude Toward Large Rectangle Ads for Second-Time Respondents . .. ..... ....... .. ... .. ....... .. .... ... .. ................... .. ......... ...... . 133 4-38 Post-Hoc Comparisons of Mean Familiarity Scores Across Fo1mats Using LSD.134 5-1 Gender, Age, Race, and Marital Status of Respondents ...................... .. . .. .. . ...... 143 5-2 Education, Income, and Employment of Respondents ........... ... .. ... ....... ............... 146 5-3 Geographic Region of Residence of Respondents ..................... . .. . ................ ... 148 5-4 Internet Usage Characteristics of Respondents .................... .......... . .. . ................. 14 9 5-5 Online Purchase Behaviors of Respondents .......................... ... .... ......................... 150 5-6 Coefficient Alphas for Measures Across Formats . .. . ........................................... 151 57 ANOV A for Formats on Attitude and Perceptual Item Factor Indices .................. 152 5-8 Post-Hoc Comparisons of Attitude and Perceptual Format Means Across For1nats Using LSD ....... ............. .. ............... .. .. .. ...... ............ ... . .. ... ................................ 153 5-9 Regression Analysis Summary for Perceptual Factors Predicting Attitude Toward Banner Ads ........... ..... ............ ....... ..... .. .... .... ....... .. . ................... ...................... . 154 .. Xll

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5-10 Regr e ssion Analysis Summary for Perc e ptual Factors Pr e dictin g Attitud e T ow ard PopU p Ads ...... . .. .... .. .. .. . .. .. .... . ... . .. .. . .. . .. . .. . .. . .. ... .. . ..... . . .. ... . . .. . ... ... 154 5 11 Regres s i o n Anal ys i s Summ a ry for P e r ce ptual Fa c tors Pr e di c tin g Attitude To w ard Skyscrap e r Ad s .... .. ...... ..... .. .. . .. .. . ... .... . .. .... .. .. ... . . .. . .. .. .... .... . .. . ..... .. . .. . .. 15 5 5 1 2 Regr es sion An a ly s is Summ a ry for Perc e ptual Factors Pr e dicting Attitud e To w ard Large Rectan g l e Ad s . .. .. . . .. .. . ... .. .. . .. . . .. . .... ... .... . . . . . . .. .... .. . .. . .. .. ....... 15 5 5-1 3 Regr ess ion An a l y si s Summ a ry for P e r ce ptual Factor s Predictin g Attitud e To w ard Floatin g Ads .. .. .. .... .. .. .. . .. .. .. .. . . .... .. .... .... ....... .. .. . . .. . . .. ... ... .... .. .. ........ . .. .. 15 5 5-14 Regr ess i o n An a l ys is Summar y for P e r ce ptual Facto1 s Predictin g Attitud e T ow ard Inter s titial Ad s .. . .... .. ... .... . .. .. ..... . ....... .. . .. .. . .. .... . . .. . .. ... ...... . .. ............... 15 6 5-15 Group Di f fer e nces for A r o rmat Between Early and Late Internet Adopter s ............. 15 7 5 16 Group Differences for A r o rmat Betwe e n Hi g h-Sp e ed Internet Acce ss and Lo wSp ee d Internet Acc ess Re s pondent s ......... ... ................. .. ... . ....................... ................... 1 5 8 5-17 Group Di f ference s for A rormat B e tween Re s pondents Who Had Cli c ked Thr o ugh on Certain Onlin e Ad Format s a nd Re s pond e nts Who Had Not .. . .. .. . .. . .. ... ........ .... 1 5 9 5 1 8 One-Wa y Anal ys es of Variance for Effect s Format Familiarity on A 60 5 19 Post-Hoc Comparison s of A ronnat Means Acro s s Fonnat Familiarity U sin g LSD 1 6 1 5 2 0 Group Differ e nces for A rormat B e twe e n R es pond e nts Who Had Mad e an Online Pur c h ase and Thos e Who Had Not . .......... .................... . ...... .. ... . ......... ............ 1 6 1 E-1 Rotated C omponent Matri x of P e rc e ptual Item s for Banner Ad s ... . ................... 236 E 2 Means Standard Deviations and Alphas for Banner Ad Factors ........ ....... ...... . 23 7 E-3 Factor Analysis of A ad for Banner Ad s .. .. ... .. ..... ...... .... .. . ... .. . .... .... . .. ..... . .. 2 37 E -4 Factor Analy s is of A rormat for Banner Ads . ..... . ....... . ............. ............................. 2 3 7 E -5 Factor Analy s is of A s i t e for Bann e r Ads ... .. . .. .... .................. ... .... ........... .. ........... 238 E-6 Rotated C omponent Matrix of Perceptual Iten1s for Pop tip Ads ............ .. ...... .... 238 E 7 Mean s, Standard Deviati o ns and Alphas for Pop-up Ad Factors .. ................ ...... 239 E-8 Factor Anal ys is of A act for Pop-Up Ads .. .. .. . .. . .. ...... ... .. . . ...... ... . ....... ... .... .. 2 3 9 E 9 Factor Anal ys i s o f A rormat for Pop-up Ad s ................ . . .. ... . . .... . . .. . .. . .... . ........... 2 4 0 E1 0 Fact o r Anal ys i s of A s it e f o r Pop-up Ad s ............ . . .... .. . . ......... ............. ... .. .. .. 2 4 0 X lll

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E 11 Rot a ted Component Matrix of Perceptual Item s for Skyscraper Ads ............. ..... 2 41 E 12 Mean s, Standard De v iations and Alpha s for Sky s crap e r Ad Factor s ... . .. . .. ..... . . 241 E -1 3 Factor An a ly s is of A ad for Sky s craper Ad s ..... . .... .. .... .......... ...... . . .... ............ 24 2 E 14 Factor Anal ys i s of A r o rmat f o r Sk ys craper Ad s ...... .. ... .... ... .. . .. ... . .... .... ..... . .. .. 2 4 2 E 15 Fact o r An a l y si s of A s it e for Sky s craper Ad s ............... ... ....... ..... .. . . . .... ..... .. .. .. 2 4 3 E1 6 Rotated C omponent Matrix of Perceptua l Items for Lar ge Rec Ad s . .. . .. . .. . .. . . 2 4 3 E -1 7 M e an s, S t and a rd D ev iation s a nd A l pha s fo r Lar g e Rec Factor s .......................... 2 44 E -1 8 Fact o r An a l ys i s of A ad for Lar ge R e c Ad s . .......... .... ..................................... ..... 2 44 E1 9 F act o r An a l ys is o f A r o rmat for Lar ge R e c Ads . .. . . .. . . .. .. . . .. . .... . . .... .. ... . . .. 2 4 5 E 20 Factor Anal ys i s o f A si t e f or Lar ge Rec Ads . . .. . . .. . . .. . . .. . . . ... ... .. . .. . .. .. .. .. . 2 4 5 E 21 Ro t ated C ompon e nt M a tri x of P e rceptua l Items for Floatin g Ad s ...... .. ....... . ..... 2 4 6 E -2 2 Mean s, Stand a rd D ev iati o n s, and Al p ha s for Floating Ad Factor s ........... .. .... . ..... 2 4 7 E23 Factor An a l ys i s of A ad f o r Floatin g Ad s .... . . ........ ....... .. ................... ................. 2 4 7 E -24 Factor Ana l ys is of A rormat for F l oatin g Ad s . .. .. . . .. . . .. .. . .. ... .. . .. . .. . .. . ... . ... 2 4 7 E 2 5 Fa c t o r Ana l ys is of A s ite f o r Floating Ad s .... .. ................ ....... ........ ......... ........... 2 4 8 E-26 Rotated C omponent M a tri x of P e rceptual It e m s for Inter s titial Ad s . ............. ..... 2 4 8 E-27 Mean s, Standard De v iat i o n s, and Alphas for Interstitia l Ad Factors ... ... . .. . .. .. ... 2 4 9 E-28 Factor An a l ys i s of A.ad for Int e r s titial Ad s ...................... ...... ............... ........... ... 2 4 9 E2 9 Fact o r Ana l ys i s of A r o rma t for Int e r s ti t ial Ai s .. .... .. ... . .. . .. .... .. . ... . ................... 2 5 0 X IV

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LIST OF FIGURES Figure p age 2-1 Modified Structural Model of A ad Formation .. ......... .. ... ...... . .. ....... .. ................... 28 2 -2 Prop osed Structural Model of A ad Formation (showing two antecedents) in an Onlin e Advertising Context .... .. .. .... ......... .. . .. ....... .... .. .......... .. . . . .. .. .. . .. . .. .. .. 60 4-1 Modified Attitude-Toward-the-Ad Model for Testing R e lat io nship s in the Online Context . .... ...... ........ .......... ... ..... .... .. . .. ... ... . ............................................. 89 4-2 Modified Attitude-Toward-the-Ad Mod e l for the Online Context Us in g Shading to Indicate the First Set of Relation s hips to be T es t e d ... ...... ... .. ........ ...................... 114 4-3 Modified Attitude-Toward-the-Ad Model for the Online Con text Us in g Shading to Indicate the Second Set of Relationships to be T es ted .. . . .... . . .. . ... .. . ..... .... .. .. . 1 20 4-4 Significant R e lation shi p s in the Modified Attitude-Toward-the-Ad Model for the Online Context .... .... ............................... .... .. . .. ... .. . . ... . ... .. . .... . . . ..... . .. .. .. .. 131 5-1 Com pari so n of Formats Across P erce ptua J Descriptors ............ ........................... 164 xv

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Abstract of Dis s ertation Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy ATTITUDE TOWARD THE ONLINE ADVERTISING FORMAT: A REEXAMINATION OF THE ATTITUDE TOW ARD THE AD MODEL IN AN ONLINE ADVERTISING CONTEXT By Kelli Suzanne Bums August 2003 Chau: John C. Suth e rland Cochair: Richard J Lutz Major Departrr1ent: Journalism and Communications This dissertation introduced a new construct : attitude toward the online advertising for1nat (Af ormat ) and demonstrated its relevance in the attitude-toward-the-ad (Aact) model. As the online advertising environment becomes more c lutt ered, technological possibilities expand, and expenditures show improvement an understanding of consumers attitudes toward the various online advertising formats is critical. In Study 1 depth interviews with Web surfers and online adve1ti s ing experts identified 15 p e rceptions of on lin e advertising format s. The interviews also d e te1 mined six online advertising forrriats for future study including banners, pop-ups skyscrapers, large rectangle s, floating ad s, and interstitials XVl

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In Study 2, a survey with a student sample was used to determine the influence of A rormat on A ad and the ability of the perceptions identified in the first study and other variab l es to predict A ro rm a t The regression equation revealed that while A ro rm a t was a significant predictor of A a ct attitude toward online advertising was not. The influence of A rormat on A ad is particularly important given that A ad is a docum~11ted precursor of brand attitude, brand choice, and purchase intentions. Online ad perceptions were found to be related to A ro r mat for all six online ad for1nats tested The formats differed in terms of the specific perceptions that were s ignificantly correlated with attitude toward each format. The other hypothesized predictors of A rormat (i.e., attitude toward online advertising, attitude toward the Web site and attitude toward the Internet) were found to be either significantly correlated with only certain forn1ats or not significantly correlated at all Study 3 produced descriptive data on A rorma t using a national survey of 1,0 7 5 adult s This study also determined how each fonnat was rated on the perceptual dimensions and tested the ability of perceptions to predict Ar o rm a t The data suppo1ied the three hypotheses of this study. Web users possess significantly different attitudes acro ss formats Users also hold a varied combination of perceptions about each format. Furth et more the three perceptions of entertainment annoyance, and inforrnation have a significant impact on A rormat XVll

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CHAPTER 1 INTRODUCTION If you don't get noticed you don't hav e anything. You just have to be noticed, but the art is in getting noticed naturally, without screaming or without tricks. Leo Burnett, The Art of Writing Advertising In 2001, the notoriously t1biquitous online ads for Xl O wireless cameras garnered much attention in trade publications and caused frustration and annoyance for many Web users. Using an ad contained within its own window that '' popped under' the user's browser window, Xl O Wireless Technologies was successful in achieving mass reach online (32.8% of the Web's entire audience bet\vee11 January 2001 and May 2001) and a total of28 million unique visitors by the end ofiviay 2001 (Jupiter Media Metrix, 2001b). According to Nielsen//NetRatings, 388,000 unique visitors entered the XlO Web site the month prior to the campaign launch (Mediapost, 2001). By May 2001, the number of unique visitors for the month had climbed to 3.5 million (Mediapost, 2001). However, the company experienced a steep decline in traffic with 73% of unique visitors leaving the si te or closing the window within 20 seconds (Jupiter Media Metrix, 2001 b). Onl y 4.2 % of visitors spent more than three minutes on the site (Jupiter Media Metrix, 2001b). While this campaign was successful in increasing the nurr..ber of unique visitors to the site, several indicators suggest it failed to enhance the company's image. These ads generated negative publicity for the company and were met with disapproving reactions by consumers (Olsen, 2001). In addition, chat rooms discussion s focu sed on how to disengage these ads and many articles were written describing how to re strain Xl O's efforts (Mediapost, 2001). Downloads of the ad-blocking software AdSubtract have been 1

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2 on the rise since the launch of this campaign (Taylor, 2001) and were predicted to reach 2 million users by the end of 2001 (Lefton, 2001a). Yet, X 10 Wireless Technologies remained undeterred in its advertising approach. One year later, the company was the leading pop-up advertiser with over one billion pop up ilnpressions in the first seven months of the year (Martin & P,yan, 2002). The XI O example suggests the possibility of a relationship between the online advertisi11g format and consun1er attitude toward that ad itself. However, before this relationship can be explored, it is important to consider the specific dimensions or perceptions of online ads that contribute to the attitude a consumer has about an ad fo11nat. The intrusiveness of the pop-under ad, for example, may constitute a dimension that shapes consumer attitudes toward pop-under ads. Pop-under ads are just one of many online advertising formats. A review of the origins of on line advertising will illustrate how the efforts of a few advertisers, content providers, and programmers set into n1otion what is today a multi-billion dollar industry teeming with a variety of advertising formats The Origins of Online Advertising The Internet is a product of ARP ANET, which was launched by the Advanced Research Projects Agency of the U.S. government in 1969 to connect research computers at universities (Public Broadcasting Service [PBS], 1997). By 1971, ARPANET grew to 23 hosts, up from the original group of four host universities (PBS, 1997). In the 1980s, Vint Cerf, known as the ''Father of the Internet," and Bob Kahn created TCP/IP, which is the language shared by Internet computers, and soon after, the ARP ANET computers began to be referred to as the Internet (PBS, 1997). The explosion of the personal computer industry in the 1980s helped spur the use of the Internet in corporate America

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3 (PBS, 1997). Today, the Internet consists of a worldwide system of networked computers accessible to hundreds of millions of people. The World Wide Web 1 was invented in 1991 by Tim Bemers-Lee while he was working for CERN, the Etrropean Particle Physics Laboratory, in Switzerland (PBS, 1997). The code he posted in a newsgroup allowed users to combine text, images, and sound on Web pages and easily publish information on the Internet (PBS, 1997). The development of Mosaic, a user-friendly, graphical interface browser, by Marc Andreessen and others at the University of Illinois in 1993 helped move a mass audience online. Mosaic incorporated the new programming language Hypertext Markup Language (HTML). When Mosaic was released, Internet traffic increased at an annual growth rate of 341,634% (PBS, 1997). The emergence of several national commercial Internet service providers in the early 1990s (i.e. America Online, CompuServe, and Prodigy) also contributed to tl1e astronomical growth rate. As more and more consumers went to the Web, this medium became even more enticing to advertisers. Some early browsers only supported a text-based interface, containing no graphics, while browsers with graphical interfaces were not always used with a high-speed modem. Although advertisers dreamed of sending television commercials over the Internet the necessary bandwidth was not available at the time (Koprowski, 1999), and graphical interfaces were not widely used by consumers Under these constraints, online advertising naturally evolved into a form of advertising similar to that of print media. 1 While often us ed int ercha ngeably th e Int e rn e t and World Wide Web are not the sa me Th e World Wide Web is the term used to describe the co llection of documents that are linked to one another through the u se of Hypertext Markup Language ( HTML) and are ho s ted by co mputers connected to th e Internet

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4 Online advertising emerged during the summer of 1994 when Coors Brewing Company and Moden1 Media launched the first national consumer brand Web site for Zima beer (Koprowski, 1999). Around the same time McDonald's sponsored an onlin e chat on America Online (Koprowski, 1999). Wir e d magazine's online maga z ine Hot Wir e d drew serious attention from th e advertising community (Koprowski, 1999) As the first online magazine supported by advertising H o t Wir e d was introduced in 1994 with 12 advertisers paying $30,000 for 12 weeks (Koprowski 1999) Advertisers includ e d AT&T, Sprint MCI, and Volvo (DiBlasi 1997) While HotWir e d has often been credited for offering the first banner advertisement the fir s t online banner ad may have been hosted by Prodigy and its origin may be further traced back to previous videotext and teletext services (Dolley 1998; Elwell 1998; Williamson, 1998). Also launched in 1994 was Time Warner's Pathfinder site, which included access to magazines and featured test ads from AT&T (DiBlasi 1997). Ziff Davis launch e d ZDNet the san1e year. Both sites acquired their first advertisers a year later The spring of 1995 saw the explosion of Web sites for major national brands from Maytag to United Airlines to Ragu. These advertisers used banner ads to lure cu s tomer s to their sites (Koprowski, 1999) Also in 1995, the Procter & Gamble online advertising account was awarded to Grey Interactive and Modem Media acquired the AT&T account (DiBlasi 1997). About the same time, Oldsmobile developed commercial chat rooms to provide a showcase for the Oldsmobile brand using celebrities to attract consumer attention Again banner ads were used to publici z e the chat rooms (Koprowski, 1999) Also in 1995

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5 America Online changed its anti-advertising policy and became more receptive to onlin e advertising The company began to accept ads from advertisers such as DLJdir e ct General Motors, and 1-800-FLOWERS on ''sponsored sites'' (Koprowski 1999). Introduced in 1995, the Java computer language provided advertisers with th e technology for creating more elaborate graphics. audio, and animation (Koprowski 1999) AT&T used this technology in 1996 to create animated banner ads (DiBlasi 1997). The dominanc e of banner advertising and lack of consistency in banner ad s i z es l e d the Interactive Advertising Bureau (IAB) formerly the Internet Advertising Bureau a nonprofit trade association founded in 1996 to adopt standards for online banner s i z es (IAB 1996). This development ensured advertisers would not have to redesign their banner ads to meet the specifications of individual sites. While banners were receiving attention from advertisers and the IAB consumer intere s t in clicking through banner ad s dropped significantly from a 40 % clickthrough rate in 1995 and 1996 to less than 1 % in 1997 (Koprowski, 1999). In 1996 Yahoo! agreed to allow Procter & Gamble to pay for advertising space on the basis of clickthrough rates ratl1er than ad impressions (Williamson, 1996). The decline in clickthrough rates on banner ad s certainly challenged advertising agencies to rethink th e purpose and format of online advertising. In recent years, faster modem speeds l1ave enabled the application of new technologies to online graphics, audio and animation. The online interface can now ha ve the same look and feel as television. St1bsequently, online advertising has evolved to incorporate formats analogou s to television commercials

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6 Online Advertising Today Ads seem to be popping up and under everywhere online. Some of the more recent and creative online advertising formats include floating ads ( often refe1Ted to by the trademarked name Shoshkele ads), which resemble cartoons floating over text, and Webmercials, which feature animation or streaming media to transmit an advertisement that uses video and audio. Another recent online innovation is the use of large rectangle shaped advertisements wrapped by text. Sliding billboards are also being used by Web sites such as USAToday.com (Elkin, 2002c ). These ads appear as a large square when first accessing a Web page and then slide up into a smaller banner ad. Another new fortnat is the full-screen ad introduced in 2003 by Unicast. Current Online Advertising Fonnats Below is an alphabetical list of current online advertising formats derived from articles on online advertising, the Interactive Advertising Bureau 's (2001 c) Glossary of Interactive Advertising Terms, and personal experience. Banners are rectangular-shaped graphical elements often found at the top of Web pages. The IAB guidelines are 468 x 60 pixels for a standard banner and 234 x 60 pixels for a half banner (IAB, 2001a). Banners can be static or employ animated graphics to capture the user's attention. Clicking on a banner directs the user to another Web page Buttons are clickable graphics tl1at are similar to banners, but are smaller, often shaped as a square, and placed anywhere on a page. The IAB guidelines are 125 x 125 pixels for a square button and 120 x 90 or 120 x 60 pixels for rectangular button s (IAB, 2001a). At a size of 88 x 31 pixels microbars can also be placed in this category (IAB, n.d.) Chat room advertising provides advertisers with access to chat room participants

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7 Classified ads are well-suited to the interactive environment. Users input their requests and are presented witl1 the appropriate listings to match their criteria. Contest sponsorships are provided by content providers to allow advertisers to sponsor and promote a contest Contextual advertising highlights words within the text of a Web page that are hyper links to an advertiser. Toptext developed by Ezula is one of the technologies us e d to highlight and provide the link s This program is unknowingly downloaded by the user when downloading other software Other programs for delivering contextual advertisin g include SurfPlus and AdPointer Daughter window ads open in a separate browser window at the same time a banner is displayed on the Web page of the primary browser window. E-mail can be ad-supported by selling advertisements on the e-mail reader or home page. The service then provides a free e-mail system to users. Two examples of free mail services are Hotmail and Juno Advertisers may also send direct e-mail to consumers. Direct e-mail marketing is classified as either permission marketing whereb y the recipient ha s provided per1nission to receive e-mail, or spam, which is unsolicited mail. The e-mails are often fo1matted to resemb]e a letter, a newsletter or a version of the marketer s Web site Rich media can also be incorporated in e-mails Expandable banners increase in si z e from 468 x 60 to as large as 468 x 200 when the user clicks or moves the cursor over the banner The user has the option to read the ad, click through to the advertiser s Web site, or send the ad away by rolling the mouse to another area on the page (Balian 2001). One of the leading companies in this format is PointRoll, which offers PointRoll technology. Point Roll produces additional message s

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8 above, below, or to the side of the original ad when the user rolls over the ad. The message disappears when the cursor i s moved away to another part of the page. Floating ads u se a combination of Flash and Dynamic Hypertext Markup Language (DHTML), which is an extended set of HTML commands. These ads create a translucent or shaded layer over the content ru1d tl1en execute an animated ad within this layer using Flash technology. The ads load after the parent page content has loaded and do not require user initiation. United Virtualities and Eyeblaster are the two leading companies using this technology to develop online ads. United Virtualities' patent-pending ad technology creates Shoshkele ads. Full-screen overlays, introduced by Unicast in 2003 and also offered by Eyeblaster, occupy the entire screen for 15 seconds (Elkin, 2003c ). Half-page units used by the New York Times Digital take up one side of the screen and two of the site's four columns (Elkin .. 2003a). Inter st itials are contained within the current browser window and are automatically presented to a viewer when moving between two content pages Once the requested page loads the interstitial fades away to the requested page. Interstitials are also referred to as transition ads, interrnercial ads, s plash page s, and Flash pages (IAB, 2001 b ). Large rectangle ads are large ads placed within the copy where an editorial photo or graphic would normally go. The editorial copy either wraps around the side of the ad or appears above and below the ad. Large rectangles provide advertisers with more space than traditional brumer ads. The space can feature rich media animation, interactive product information or e-commerce opportunities. Users can often click within the ad or click through to the advertiser's site. The IAB guidelines for large rectangles are 336 x

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9 280 pixels (IAB, 200 1 a). Other rectangle sizes include the vertical rectangle (240 x 400 pixels), the medium rectangle (300 x 250 pixels), and the rectangle (180 x 150 pixels) (IAB, 2001a). Leaderboards are giant banners with the dimensions of 728 x 90 pixels (IAB, n.d .) Nonlinking advertisements are name recognition builders. They are typically fixed logos on a Web site that do not allow the user to click through to the advertiser's site. Paid listings are available to feature advertisers' listings prominently on the results pages of many search engines. Paid listings are also called search engine listings or key word listings. Pop-under ads open underneath the user 's browser and usually are discovered when the user ha s closed or minimized the browser. The user is forced to close the pop-under ad separately. Pop-up ads interrupt the user by opening another window over the user 's browser The user must close or minimi ze the window to remove it from the screen A pop-up ad may appear while the user is on a Web page or while transitioning between two Web pages This ad format is similar to a daughter window but is not served with an associated banner ad The IAB guidelines for pop-up ads are 250 x 250 pixels (IAB, 2001a). Portals reside in a tool bar For examp l e, CNET.com uses text portals for its featured advertisers. Sliding billboards appear as a large advertising unit when first accessing a Web page and then s lide up into a smaller banner unit. Skyscrapers are similar to banners, but rather than being located at the top of a Web page, these tall thin ads are situated alon g the side of a Web page The IAB guidelines

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10 for skyscrapers are 160 x 600 and 120 x 600 pixels (IAB, 2001a) A tower ad also called a vertical banner is a shorter version of a skyscraper. Sponsored electronic mailing lists are e-mails distributed to subscribers of the service. Many niche markets are available to advertisers through these lists. By sponsoring an electronic mailing list advertiser s can distribute their content to a group o f people interested in the topic. A sponsorship is an association with a Web site that provides more visibility for th e advertiser than run-of-site advertising (IAB, 2001 b ). With sponsorships adverti s er s hope users will favorably associate the content with the advertiser ESPN Sportszone s Injury Report is an example of sponsored content. Microsoft s $200,000 sponsorship of the Superbowl Web site and Toyota and Chemical Bank's $120,000-per-year sponsor s hip of the New York Times Digital were some of the earliest example~ of online sponsorship advertising (DiBlasi 1997) Superstitials developed by Unicast load into temporary memory while a user i s viewing a Web page and instantly appear when the user clicks to another page on the s ame site Superstitials range from the si z e of a postage stamp to 550 x 480 pixel s (about two tlurds of the screen) Superstitials typically feature full animation sound and graphics and can run as long as 30 seconds Surround sessions first launched by the New York Times Digital provide a user with banners, large rectangles skyscrapers, and buttons from a single advertiser during a visit to the site (Saunders 2001b) Web site s are the most common format of advertising on the Internet. The sit e can be structured as a destination s ite, whereb y information and entertainment ar e u s ed t o

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11 attract users to the site, or as a microsite (also cal]ed a jump page) which uses small clusters of pages hosted by a content site or network Although the most prevalent type of online advertising, a Web site is similar in purpose to a physical store, or even a customer service infotrnation hotline, and Web site hosting costs are not included in estimates of online advertising expenditures. W ebmercials ( also called interrnercials or W ebformercials) feature animation or streaming video and audio a11d require a downloadable plug-in to be viewed or heard. Webmercials are often launched through either the use of an interstitial or a hypert ext link. While a W ebmercial may be the same commercial that runs on television the image is smaller and not as sharp. BMW and Jaguar are two companies that have used this type of advertising. Viral marketing is used to quickly spread inforrnation online and is typically accomplished through the use of e-mail. For example, Hotmail tags a logo to all outgoin g e-mail messages to promote its free e-mail. Some sites allow users to e-mail content b y clicking on ''e-mail this to a friend.'' Other sites encourage users to tell friends about th e site through e-mail. Viral 1narketing can also be used in newsgroups and chat rooms. Advertisers can spread news about their company or products t1sing this method. Demand for New Online Advertising Formats New online advertising fo1mats have emerged as a result of the demands of adve1tisers and their agencies and the economic situation of many online content providers. For advertisers disappointed with the low clickthrough rates of banner ads, more technologically innovative forms of online advertising evolved to supplement the use of banner ads. Advertising agencies also recognize these more sophisticated formats of ads as a way to increase their profit margins for online advertising (Black 2001 ).

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12 A sagging economy and the failure of many dot com companies have slowed revenue growth for the online advertising industry (Heim, 2001). As a result, online content providers have been desperate to sell advertising space and are willing to allow their advertisers to try more daring advertising concepts to attract the attention of the user (Mediapost, 2001). At the same time, marketers and advertisers are also recognizing the value of perrnission marketing, whereby the consumer grants permission to receive e-mail solicitations. Research firm eMarketer estimated 226 billion permission-based e-mails will be distributed by the end of 2003 (eMarketer, 2001b). Permission is typically provided when a user registers at a Web site and checks (or unchecks) a box indicating his or her willingness to accept communications from the Web site or one of its partners. Permission marketing allows users to have more control over their online advertising expenence. As demonstrated, the Internet provides the advertiser with a medium for transmitting advertisements in a variety of formats. The variety of online advertising formats has evolved greatly from the original static banner ads, and variations of current formats seem to appear almost daily. Online Advertising Mix The most prevalent online advertising format is still the banner, which represented 33% of online advertising elements for the week of April 28, 2003 (AdRelevance, 2003) Including half banners increases this percentage by 4% (AdRelevance, 2003). Skyscrapers also represented a high percentage of online advertising elements at 9% for standard skyscrapers, 4 % for wide skyscrapers, and 4 % for vertical banners

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13 (AdRelevance, 2003). Buttons represented 14% of elements and squares and medium rectangles totaled 10% (AdRelevance, 2003). A report by Nielsen//NetRatings found similar results, citing the domina11ce of the banner ad (Martin & Ryan, 2003). Of the impressions for the top I 00 cross-media advertisers in the fourth quarter of 2002, 29% were full banners and I 0% were half banners (Martin & Ryan, 2003). Rectangles ( e.g., standard size, medium, large and vertical) totaled 24% of impressions and skyscrapers totaled 11 % (Martin & Ryan 2003). Another Nielsen//NetRatings study also reported that pop-ups only represented 3 5% of all online advertising impressions for the fourth quarter of 2002 (Buchwalter & Martin, 2003). Interestingly, pop-ups garnered over 11.3 billion ad impressions in the first seven months of 2002 and 80% of the pop-up ads were used by only 63 advertisers (Martin & Ryan 2002). The remaining 20% of pop-up ads were distributed among 2,145 advertisers (Martin & Ryan, 2002). Over 9% of advertisers during these seven months used a pop-up ad (Martin & Ryan, 2002). In the two-year period before the fourth q11arter of 2002, the average number of online ad formats supported by Web sites more than doubled to 11 fonnats from 5 .3 formats (Buchwalter & Martin, 2003). Almost all Web sites accepted the banner ad and 60% of advertisers in a Nielsen//NetRatings study were found to use banner ads (Buchwalter & Martin, 2003) Only 10% of advertisers used the skyscraper format, while 70% of sites accepted the forrnat and less than 10% of advertisers used pop-ups, which were also accepted by a high percentage of sites (Buchwalter & Martin, 2003) Online Advertising Spending Online advertising represented only a $0.2 billion industry in the U.S. in 1996 (Jackson, 2001a). In 1998, online advertising reven11e reached $1.92 billion, passing

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14 outdoor advertising revenue for the first time (Koprowski, 1999). For 2000, PricewaterhouseCoopers reported that online spending by U.S. advertisers totaled $8.2 billion (Black, 2001 ). U.S. online advertising revenue was down 12% in 2001 from the PricewaterhouseCoopers' estimate, resulting in expenditures of $7.2 billion for the year (Jackson, 2001a). In 2002, online advertising spending totaled $5.95 billion (IAB 2003) Tl1e fourth quarter of 2002 showed the first consecutive quarterly increase in online advertising revenue since the second quarter of 2000 (IAB, 2003). Jupiter Research predicted a 10 % growth rate for 2003 and $14 billion in expenditures by 2007 (Jupiter Research, 2002). Worldwide online advertising expenditures are expected to reach $42 billion in 2005 (Forrester Research, 2001). Analysts at Jupiter Research anticipated that much of this growth will be fueled by the rise in online classified ad spending (i.e., paid search engine listings) and the increase in spending by traditional advertisers (Jupiter Research, 2002). Publishers are now catering to traditional advertisers with better service, improved tools for measuring results, and new technology for more creative ad format options (Green, 2003). In addition, online ad prices have fallen dramatically and lowered the cost per thousand ad impressions (Green, 2003). In March 2001, a study by Nielsen/ IN etRatings reported that online advertising spending by traditional advertisers surpassed spending by dot-corns for the first time (Saunders 2001 a). In addition of the top 100 online advertisers, more than half were traditional advertisers. This trend has been attributed more to the increase in offline advertisers moving online than to the recent failures in the dot-com industry (Saunders,

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15 2001a). A Nielsen//NetRatings report cited a number of the top ten cross-media advertisers that increased their online presence in 2002, namely DaimlerChrysler with a 407o/o increase over 2001 online advertising expenditures, Verizon Communications with an 88% increase, Johnson & Johnson with a 39% increase, Ford Motor Company with a 34% increase, and Walt Disney and AOL Time Warner, both with a 28% increase over 2001 expenditures (Martin & Ryan, 2003) Online Advertising Effectiveness Clickthrough rates, an early measure of advertising effectiveness, have been dropping fast (K.hennouch & Lowry, 2001) The increase in the sheer number of online advertisements may provide some explanation for this decline (Song, 2001). Because clickthrough rates are calculated by dividing clicks by impressions, it is possible that people are not necessarily clicking less often, but that impressions have increased, driving the clickthrough rate down These low clickthrough rates have made the medium less attractive to advertisers (eMarketer 2001a). In a 2001 study of marketers and ad agency executives by Myers Mediaenomics 85 % of respondents cited ''driving traffic to the Web site'' as one of the top five reasons for using online advertising (receiving a higher percentage of responses than any other alternative), and 49% of marketers and 57% of ad agency executives indicated that the clickthrough rates were not high enough to motivate them to increase their online ad spending for 2001 (second only to budget limitations) (eMarketer, 2001a) The focus on clickthrough as a measure of online advertising effectiveness has been downplayed since the initial online advertising boom. An alternative and more popular view is that the value of online advertising cannot be solely measured by clickthrough rates (Briggs & Hollis, 1997)

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16 One problem with the use of clickthough rates as a measure of effectiveness is they do not fully represent the totality of banner ad conversions. Data from Engage (2001) suggested only 25% of sale or lead conversions by consumers who were exposed to an online advertising campaign result from clicktbroughs on an ad itself and slightly less than half of all conversions occur one or more days after being exposed to a banner ad for the site A study by ad agency Avenue A found that 20% of consumers who made a purchase on a travel site clicked through on a banner ad, while 80% had previously seen the ad and later went directly to the site to make a purchase (Gilliam, 2000) In addition consumers who saw ads accounted for 10% more sales and traffic than those who did not (Gilliam 2000). Research has supported the idea that mere exposure to the banner ad itself ( even without a clickthrough) can have a positive effect on the brand. The 1996 HotWired Ad Effectiveness Study (Briggs & Hollis, 1997) found banners have a brand building effect The 1997 IAB Online Advertising Effectiveness Stt1dy conducted by Millward Brown (IAB, 1997) found a single exposure to a banner ad was enough to generate lifts in ad awareness, brand awareness, purchase intent and product attribute communication Using a survey of 18,000 respondents covering multiple product categories, Dynamic Logic reported the average brand awareness lift for banner advertising to be 6 % (Dynamic Logic 2000a). The same organization conducted a study for Travelocity and saw a 16% lift in aided brand awareness, a percentage that increased to 44% for respondents who saw the ad four or more times (Dynamic Logic 2000b ) A report by Morgan Stanley Dean Witter (2001) concluded that consumers are 27% more likely to

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17 recall a brand after seeing an Internet ad, representing a recall level higher than that for magazines (26%), newspapers (23%), and television (17%). A study by Dynamic Logic of advertisers in a program by Forbes.com that guaranteed brand improvement results found the online campaigns of 12 participating marketers increased message association by 28%, purchase consideration by 14%, aided awareness by 11 %, and brand favorability by 6% (Elkin, 2003b ). Research by Millward Brown Interactive has also confirmed that various online advertising for1nats, including interstitials, Superstitial ads, rich media, adaptable cursors, and streaming media, have a positive effect on brand awareness, brand perceptions, and intent to purchase (Briggs & Stipp, 1999). A study by Morgan Stanley found banner ads using streaming media were five times as effective in generating brand recall than traditional banner ads (Morgan Stanley, 2001 ). As these studies have shown, online advertising is capable of impacting brand image, and therefore, clickthrough rates are certainly not the only measure of effectiveness. Brand awareness, image, and intent-to-purchase measures may be better indicators of long-term advertising effectiveness. Advertisers and marketers are recognizing the implications of these studies and have been changing the way they mea sure advertising effects. A report by Jupiter Media Metrix (2001a) found only 15% of marketers measured online branding effects, while many chose to use direct response metrics such as clickthrough rate (60%) and cost per conversion (75%). By 2002, the percentage of marketers who measured long-term metrics, such as branding, had risen to 35% (Jupiter Research, 2002).

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18 Marketers may also want to consider measuring offline sales resulting from online advertisements. A joint study by Procter & Gamble and Infonnation Resources, In c. found offline sales for an impulse food product to be 19% higher for the test group with three online ad exposures than the control group with none (Welch & Krishnamoorthy 2000). As the advertising industry moves away from measuring the effe ctiveness of online advertising through direct response metrics such as clickthrough rates, traditional measures of effectiveness, including brand awareness and intent-to-purchase are being embraced A natural extension of these measures is attitude toward a specific advertisement, which may be predicted, in part, by attitude toward the online advertising format. Statement of Purpose The cluttered online advertising environment, the expanding options for online advertising, and the estimates for future growth in online advertising expenditures all suggest the need for the advertising industry to be concerned about consumers' attitudes toward online advertising and attitudes toward individual online ad fonnats. The current study hypothesizes that attitude toward the online ad format plays a critical role in determining attitude toward the ad As Dynamic Logic director of client services Jeffrey Graham wrote in his company newsletter column, ''You can 't expect people to separate the medium (pop-ups) from the message (bad advertising)'' (Graham, 2001). The oft-quoted ''medium is the message'' pronouncement by Marshall McLuhan (1964, p 7) further suggests a way to think abo11t online advertising formats as these fo1mats themselves communicate a message.

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19 Identifying the specific perceptions of online advertising that may raise or lower attitudes toward an online advertising format was the first purpose of this study. This study also collected descriptive data on attitudes toward different formats of online adve11isements and developed and tested a model of online advertising attitudes that specified the antecedents of attitudes toward these new advertising formats and the effect of attitudes toward online ad formats on attitude toward the ad (Aaa). Importance of the Study This study has a number of potential implications for advertisers and advertising agencies. First, a greater awareness of attitudes toward online advertising fo1mats should influence the use of online advertising in general and choice of online advertising by advertisers and their agencies Second, the findings from this study identified the specific perceptions that raise or lower attitudes toward a particular online ad format. These results will be useful during the creation of an individual ad. This research also makes an original contribution to the flourishing body of literature in the area of attitudes toward advertising in general, attitudes toward advertising in a specific media vehicle, and attit11de toward the ad. This research will also be directly useful in future studies of online advertising effectiveness and attitude toward the online ad. While deriving and testing dimensions of attitudes toward current online advertising formats has both practical and theoretical significance, these findings also have implications for emerging online ad formats, further strengthening the importance of this study This research can help guide the development of new online advertising formats.

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20 Outline Chapter 2 reviews the research on the attin1de-toward the ad model, which incorporates, as an antecedent of Aad, the concept of attitude toward advertising in general. The research streams on attitude toward advertising in general and attitude toward advertising in a specific media vehicle are then reviewed, with particular emphasis on attitude toward online advertising. The literature review concludes with a discussion of the hypothesized model guiding the present study, illustrating the proposed role of attitude toward the online advertising forrr1at in a modified attitude-toward-the ad model This research utilized a multi-method approach, using qualitative methods in the first study and surveys in two additional studies. Chapter 3 describes the first study, which used a qualitative approach. Chapter 4 disct1sses the second study, which tested the hypothesized model using a student sample. Chapter 5 describes the third study, which used an online survey to gather descriptive data ~om a nationwide sample of adults. In Chapter 6, the implications of the findings of these studies are addressed in relation to the future of the online advertising industry and theory

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CHAPTER2 LITERATURE REVIEW This study introduces a new construct attitude toward the online advertising format (Aronnat)-and proposes to demonstrate both its determinants and its relevance in the attitude-toward-the-ad model. According to Rodgers and Thorson (2000, para. 85), ''Attitude toward the ad ... is a response easily applied to interactive advertising Paralleling the definition of attitude toward the ad (Lutz, 1985, p 46; MacKenzie & Lutz, 1989, p. 49), attitude toward the online advertising format is defined as a predisposition to respond in a consistently favorable or unfavorable manner toward an online advertising format. Ad format has been simply defmed as ''the manner in which [ an ad] appears'' (Rodgers & Thorson, 2000, para. 47). For example, television advertising can be categorized in tem1s of the length of the commercial (e.g., 30 seconds), while magazine advertising can be classified according to size (e g., full page) (Rodgers & Thorson, 2000). The need to consider the ad format variable in a study of online advertising stems from the proliferation of various online advertising formats, from banner ads to the more television-like Webn1ercials. While research on attitudes toward advertising in general has been extended to analyses of attitudes towarJ advertising in specific media vehicles it has barely addressed the existence of multiple formats of advertising within one medium. Research has demonstrated that consumers possess different beliefs about advertising in various media. When comparing beliefs about advertising, several studies 21

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22 have found that consumers perceive newspaper and magazine advertisements to be the most inforrr1ative (Mittal, 1994), with consumers significantly more satisfied with the informational value of magazine advertising than with television advertising (Soley & Reid, 1983). Bauer and Greyser (1968) found television advertising to contain the highest proportion of ads classified as annoying, while print advertising was more likely to be categorized as informative and enjoyable. Similui ly, in another study, newspaper and magazine advertisements have been classified as less irritating and annoying than television advertising (Mittal, 1994). These studies demonstrate that consumers have different beliefs about advertising in various media and suggest the possibility that consumers may also have unique beliefs about each online advertising format These belief sets are expected to lead to different attitudes toward each online ad format. Academic studies in the area of attitudes toward online advertising are theoretically and methodologically grounded in the tradition of research on attitudes toward advertising in general, an area that has evolved to include a focus on attitudes toward advertising in a specific media vehicle. The emphasis in both the trade and academic literature on understanding attitudes toward advertising may be attributable to the documented relationship between general attitudes toward advertising and attitude toward a specific advertisement, i.e., the attitude-toward the-ad construct (Bauer & Greyser, 1968; Lutz, 1985; MacKenzie & Lutz, 1989; Mehta, 2000). In turn, considerable research has demonstrated a positive association between A a d and brand attitude, brand choices, or purchase intention (Drage, 1989; Gardner, 1985; Homer, 1990; MacKenzie & Lutz, 1989; MacKenzie, Lutz, & Belch, 1986; Miniard, Bhatia, & Rose, 1990; Mitchell & Olson, 1981; see discussion in Shimp, 1981; see Brown & Stayman, 1992, for a

PAGE 40

23 comprehensive review). In addition, the Advertising Research Foundation Copy Research Validity Project identified likability of an advert~sement as the single best discriminator of advertising effectiveness (Haley, 1990). The following literature review will first detail the Aad model, describing relevant studies in this area and illustrating the antecedents of A a d This review will then describe tl1e research on attitudes toward advertising in general in more detail. Recent trends in research on attitudes toward advertising will also be addressed, including the emphasis on understanding attitudes toward advertising in a specific media vehicle and attitudes toward online advertising Finally this review will describe hov the proposed concept attitude toward online advertising format-is hypothesized to fit into the existing model. Attitude Toward the Ad Attitude toward the ad is defined as a ''predisposition to respond in a consistently favorable or unfavorable manner to a particular advertising stimu l us during a particular exposure situation'' (Lutz 1985, p. 46). Early research focusing on the origins of A ad incorporated a cognitive processing approach, in much the fashion of the central route to persuasion in Petty & Cacioppo's elaboration likelihood model (ELM) (1981; see Lutz, 1985). The idea that cognitions about an ad (as opposed to cognitions about the advertised brand) could have an influence on attitude toward the ad was extrapolated from the findings of previous studies confuming the link between brand-related cognitions and brand attitude (Mitchell & Olson, 1981) and the relationship between cognitive responses to an advertising message and attitudinal message acceptance (Wright, 1973). Subsequently the relationship between ad-related cognitions and attitude toward the ad has been documented {Lutz MacKenzie, & Belch, 1983).

PAGE 41

24 Aad represents an affective response to an advertisement and the validity of such a response is further bolstered by persuasion theories from social cognition, which recognize the influence of not only cognitive, but also affective responses on message effectiveness. Petty and Cacioppo' s (1981) ELM, which describes two routes to persuasion, posits a ''central route'' to persuasion occurring thro 1 1gh diligent processing of message content and a ''peripheral route'' to persuasion resulting from more casual processing of tl1e message source or other contextual factors. The level of involvement deterrnines which path to persuasion dominates Attitude Toward the Ad as a Mediator Introduced by Mitchell and Olson (1981) and Shimp (1981), Aad has been found to be a mediator of brand attitude (Ab), brand choice, and purchase intentions (Gardner, 1985; Homer, 1990; MacKenzie & Lutz, 1989; MacKenzie, Lutz, & Belch, 1986; Miniard Bhatla, & Rose, 1990; Mitchell & Olson, 1981). A meta-analysis by Brown and Stayman (1992) of 47 samples confirmed a significant relationship between A ad and brand attitudes, brand-related cognitions, and purchase intention. The significance of brand attitude is its documented link to purchase intentions (Brown & Stayman, 1992) MacKenzie, Lutz, and Belch (1986) applied the concepts of ELM to two of their four structural specifications of the mediating role of A ad In the ''affect transfer hypothesis," the central route to persuasion explains the direct relationship between brand cognitions and attitudes toward the brand, while the peripheral route serves to explain the path from attitudes toward the ad to brand attitudes. In situations of high message involvement (the cognitive effort directed toward processing message content) and low ad execution involvement (the effort focused on processing non content properties) the central processing mechanism dominates persuasion and brand cognitions lead to brand

PAGE 42

25 attitudes (MacKenzie & Lutz, 1989) As Droge noted, ''A ad appears to be a peripheral cue that has little or no impact when central processing predominates'' (1989, p. 202). In contrast in situations of low ad message involvement regardless of the level of ad execution involvement the pe1 ipheral route provides a framework for understanding how attitudes toward the ad are directly related to brand attitude (MacKenzie & Lutz 1989) While Petty and Cacioppo's (1981) theory can be applied in situations of low message involvement to explain how peripheral processes operate to allow a periph e ral cue such as attitude toward the ad to have persuasion abilities, it does not explain how attitude toward the ad may serve as a peripheral cue to influence the central route to persuasion (MacKenzie, Lutz, & Belch 1986). Within this ''dual-mediation'' model attitude toward the ad is directly related to brand attitude and al~o indirectly related to brand attitude by influencing the degree to which the audience incorporates messa ge content into its brand cognitions (MacKenzie & Lut z, 1989). Extending this line of research Miniard, Bhatla, and Rose (1990) determined that the A ad -brand attitude relationship can be viewed as the result of not only peripheral processing, but that the two constructs can be related even when persuasion follows the central route. While MacKenzie, Lutz, and Belch (1986) found the relationship between A ad and A b to be stronger than any other relationship in the four models tested, they recogni z ed that shared method variance may have heightened this effect. MacKenzie and Lutz (1989) also found A ad to have a strong effect on A b, while cognitions about the brand did not influence A b as strongly as expected. Brown and Stayrnan's (1992) meta-analysis demonstrated that while some path analytic studies did not find a significant relationship between brand cognitions and brand

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26 attitude ( e.g., MacKenzie & Lutz, 1989), others found a significant path ( e g., Homer, 1990). Based on aggregated study data, Brown and Stayman (1992) suggested that brand cognitions do significantly affect brand attitudes, but tl1at this relationship is the weakest in the model. Furthermore, the meta-analysis supports the indirect effect of attitude toward the ad on brand attitude through brand cognitions (Brown & Stayman, 1992). In addition, while most studies found a substantial and significant direct relationship between Aad and brand attitude (e.g MacKenzie, Lutz, & Belch, 1986), Brown and Stayman's (1992) meta-analysis found this relationship to be weaker than these studies suggest. Other studies have documented the circumstances under which Aad has strong effects (Drage, 1989; Gardner, 1985; Park & Young, 1986). Drage (1989) found A a d to be a significant predictor of Ab only for noncomparative, rather than comparative, ads. Gardner (1985) found that a positive and significant relationship existed between A a d and attitude toward the brand for both brand and nonbrand processing set conditions. Park and Young (1986) differentiated cognitive, affective, or low involvement and found that Aad influenced brand attitude only in situations of affective or low involvement. Likability Studies A number of studies have addressed liking of an advertisement, a concept virtually identical to Aa
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27 Validity Project (Haley, 1990) found liking of a commercial to be the strongest predictor of the sales differences due to advertising for the cases evaluated. Attitude Toward the Ad Model While studies have demonstrated how A ad is predicted through cognitive responses to the execution elements and the perception of advertiser credibility (Lutz MacKenzie & Belch, 1983) A ad may also be the result of a peripheral processing mechanism (Lutz, 1985) Affective reactions to the advertiser and advertising in general, as well as the mood of the consumer may operate through peripheral processing to influence A ad (Lutz, 1985). Lutz (1985) developed a structural model of five cognitive and affective antecedents of A ad and MacKenzie and Lutz (1989) further refined Lut z's (1985) original n1odel. The five antecedents include ad credibility ad perceptions attitude toward advertiser, attitude toward advertising in general, and mood The model also incorporates '' second-order d e terminants," which directly influence the five antecedents of A ad and indirectly impact A ad through the ''first-order'' antecedents. Figure 2-1 summarizes the modified structural model (MacKenzie & Lut z, 1989). Descriptions of each antecedent as defmed by Lutz (1985) and MacKenzie and Lut z (1989) are also provided. Ad credibility. The assessment of ad credibility, defined as ''the extent to which tl1e audience perceives claims made about the brand in the ad to be truthful and believable '' (Lutz, 1985 p 49) is a cognitive process requiring a central processing model Ad s perceived to be credible receive more favorable responses by consumers

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28 Message Content Execution Characteristics Past Experience and Informati o n Individual Differences Reception Context Ad Claim Discrepancy Advert i s i ng Credibility Advertiser Credibility Ad Credibility Ad Perceptions Brand Perceptions Advertising Perceptions Advertiser Perceptions Attitude toward Advertiser Attitude toward Advertising Legend : Mood CJ Perceptual Constructs 0 Affective Constructs 0 Exogenous Variables Noncausal Identities Hypothesized Causal Relationships Figt1re 2 -1 Modified Structural Model of A a d Format i on. From '' An Empirica l Examination of the Structura l Antecedents of Attitude Toward the Ad in an Advertising Pretesting Context ," by S. B. MacKenzie and R. J Lutz 1989 Journal of Marketing 53 p. 53. Copyright 1989 by Scott B. MacKenzie and Richard J Lutz. Reprinted with permission. Ad credibility re s ults from three s econd-order deterrninants: perceived ad claim discrepancy adverti s er credibility and advertising credibility. Ad c l a im discrepanc y is the gap between the advertisement s claim s about the brand and the consumer s perceived performance of tl1e brand a perception influenced by past experience, information about the advertised brand and the content of the mes s age Adverti s er credibility reflect s the con s umer' s perceived truthfulne ss of t he ad s spon s or Furthermore pa s t experience and information about the advertiser directly influence

PAGE 46

29 advertiser credibility. Advertiser credibility also serves as a component of the second order determinant of the multidimensional advertiser perceptions. Advertising credibility, the perception of the believability of advertising in general, also influences ad credibility. As with advertiser credibility, advertising credibility is one component of advertising perceptions. Advertising credibility has also been modeled to influence ad credibility indirectly through the more specific construct of advertiser credibility (MacKenzie & Lutz, 1989) While MacKenzie and Lutz (1989) established a significant relationship between ad credibility and Aad, they could not find support for their hypothesis that advertising credibility affects ad credibility. The findings did support a significant relationship between ad credibility and another second-order determinant: advertiser credibility (MacKenzie & Lutz, 1989). Ad perceptions As one of many perceptual responses to an ad, ad credibility is actually a special case of ad perceptions the second major antecedent to Aact Because of the amount of research in the area of ad credibility, a separate classification for this variable was warranted (Lutz, 1985). Like ad credibility, ad perceptions also entail so me degree of central processing. This construct incorporates only consumer perceptions of the advertising stimulus and not perceptions of the advertised brand. As a mediating variable, ad exec11tion characteristics have been found to have a strong positive relationship with Aact through ad perc e ptions (Lutz, MacKenzie, & Belch, 1983). Attitude toward advertising and attitude toward the advertiser are modeled to

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30 impact ad perceptions, demonstrating the possible influence of affect on a perceptual process (Fazio & Zanna, 1981 ) Under ad pretest conditions, MacKenzie and Lutz (1989) found advertiser attitude to have a strong positive relationship with ad perceptions, while the relationship between attitude toward advertising and ad perceptions could not be cross-validated. Ad perceptions were found to exhibit a strong positive correlation with Aad (MacKenzie & Lutz, 1989). Attitude toward the advertiser Defined as ''a learned predisposition to respond in a consistently favorable or unfavorable manner to the sponsoring organization'' (Lutz, 1985, p. 53), attitude toward the advertiser represents a more affective response to an advertisement. Perceptions of the advertiser, including advertiser credibility, are expected to influence attitude toward the advertiser Perceptions emanate from consumers' past experience and information about the company. Advertiser attitude was fot1nd to have a strong positive correlation with A a d under ad pretest conditions (MacKenzie & Lutz, 1989). Attitudes toward advertising. Attitude toward advertising represents a ''learned predisposition to respond in a consistently favorable or unfavorable manner toward advertising in general'' (Lutz, 1985, p 53; MacKenzie & Lutz, 1989, p. 53-54) This concept reflects consumers' general attitudes toward advertising, rather than attitudes toward a specific advertisement or about advertising in a specific medium The study of the relationship between consumers' attitudes toward advertising in general and ratings of specific ads dates back to Bauer and Greyser's (1968) classic study described in Advertising in America: The Consumer View. Bauer and Greyser (1968, p.

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31 121) suggested a re lationship between overall attitudes toward advertising and the proportion of ads classified as either favorable or unfavorable. In addition, the data revealed a relationship between attitudes toward advertising and the perception of certain ads as informative (Bauer & Greyser, 1968, p. 136). The model of Aad formation proposes that attitudes toward advertising resulting from perceptions of advertising have a direct impact on Aad MacKenzie and Lutz (1989) could not confirm a relationship between attitude toward advertising and Aad in a study under ad pretest conditions; however, they suggested that in focusing attention on the evaluation of a specific ad, subjects were less lilr ely to base Aad assessments on general constructs, such as attitude toward advertising, than on specific constructs. MacKenzie and Lutz (1989) suggested that in a natural setting, as opposed to a forced exposure situation, a stronger relationship between attitude toward advertising and Aad might exist. Mood. As the most purely affective antecedent to Aad, mood is ''the consumer s affective state at the tin1e of exposure to the ad stimulus'' (Lutz, 1985 p. 54). Mood is influenced by individual differences, which are the basic predispositional tendencies of consumers; ad execution characteristics; and reception context, comprised of the nature of the exposure, the amount of ad clutter, and the program or editorial context. Attitudes Toward Advertising in General A more thorough discussion of attitudes toward advertising is provided below and will be followed by a discussion of attitudes toward advertising in a media vehicle and attitudes toward on line advertising. This review is provided to demonstrate how the construct of attitude toward the on line ad fonnat emerges as a natural extension of this body of research.

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32 Researchers and industry practitioners have long been interested in attitudes toward advertising (see Mittal, 1994; O'Donohoe 1995; Pollay & Mittal 1993 ; Zanot 1981 1984 for review s ), a construct found to influence attitudes toward specific advertis e m e nt s (Bauer & Greys e r 1968). The earliest studies in this area date back to 1939 and are characterized by consumers generally favorable attitudes toward advertising ( Bauer & Greyser 1968) A 1942 survey b y the Association of National Advertisers found more than 80 % of respond e nts to b e supportive of advertising during the war (as cited in Bauer & Grey s er 196 8) In the 1950s attitudes toward advertising remained favorable as indicated by a 1951 survey by Mcfadden Publications (as cited in Bauer & Greyser, 1968) in which 90 % of respondents agreed that advertising has played an important role in raising the standard of livin g in the U.S. In the late 1950s, a R e dbookmagazine survey conducted b y the Gallup Organization Inc. (1959, as cited in Bauer & Greyser, 1968) determined that more than 80% of the over 1 600 respondents believed advertising helped raise nationwide prosperity In addition, 75 3/ o reported that they liked advertising and the most frequently cited reason for liking advertising was its informational value. General attitudes toward advertising have been on the decline since these earl y studies. The percentage of Americans holding a generally favorable view of advertising dropped to 54 % in 1960 (Univer s al Marketing Research, 1961, as cited in Bauer & Greyser 1968) Bauer and Greyser (1968) found the percentage of respondents with a favorable attitude toward advertising to be 41 o/ o by 1964 Although a majority of respondents in this study believed advertising to be misleading and capable of persuadin g

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33 people to buy products they should not buy, the~ still considered advertising to be essential. Zanot s (1981) review of 38 public opinion polls from the early 1930s to the 1970 s revealed that attitudes toward advertising became increasingly more unfavorable during that time According to Zanot's analysis: The number of surveys conducted ... during the 1970s increased dramatically; 20 are presented here . they reflect a decidedly negative public opinion toward advertising. In almost every instance where a study was replicated the later one shows more negative attitudes (1981, p 146) Research in recent years has focused more on attitudes toward advertising in a specific medium than attitudes toward advertising in general (Alwitt & Prabhaker 1992 ; Mittal, 1994) One exception is a 1998 study of 1 000 adult consumers current attitude s toward and confidence in advertising (Shavitt Lowrey, & Haefner, 1998) This stud y revealed more favorable public attitudes than suggested by previous studies Only one fourth of respond e nts in this study indicated that they disliked advertising. Another focus in recent years has been an attempt to understand the structure of advertising attitudes Because these studies have tended to use smaller and less nationally representative samples results are not generali z able to the American public ( e.g Alwitt & Prabhaker 1992; Andrews 1989; Mittal 1994; Muehling, 1987; Pollay & Mittal 1993; Reid & Soley 1982; Sandage & Leckenby, 1980) Other studies have tested the relationship between general attitudes toward advertising and advertising e f fectiveness Research has demonstrated that attitudes toward advertising in general are related to ad recall and buying interest (Donthu Cherian, & Bhargava 1993; Mehta, 2000).

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34 A study of outdoo r advertising found that consumers with positive attitudes toward advertising in general exhibited greater recall of outdoor advertisements than those with negative attitudes (Donthu, Cherian, & Bhargava, 1993). Mehta (2000) found that respondents who reported that they like advertising, feel that it provides useful information, and view it as not being manipulative were more likely than those who did not feel this way to notice and recall advertisements. In addition, buying interest was found to be positively related to almost all of the advertising belief statements tested in the study (Mehta, 2000) Another study examined the influence of attitudes toward advertising in general on involvement with specific advertisements, operationalized as the amount of time spent looking at the advertisement (James & Kover, 1992). The group of subjects that believed advertising to be manipulative and the group that found advertising to be irritating were both more involved in the advertisements. Beliefs About Advertising in General While early studies often measured favorability or unfavorability toward advertising, later studies focused on beliefs about certain aspects of advertising (Mittal, 1994). Referred to as ''co11sequences'' of advertising in some studies (Mittal, 1994) and ''ftmctions'' in others (Alwitt & Prabhaker, 1992), these statements generally reflect beliefs about advertising Beliefs represent descriptive statements about tl1e attributes an object possesses, creating a link between an object and an attribute. Beliefs are generally considered to contribute to the fonnation of attitude (Ajzen & Fishbein, 1980). As noted by Fishbein and Ajzen, ''a person's attitude is a function of his salient beliefs at a given point in time'' (1975, p. 222). Attitudes are summary eval11ations of the perception that an object

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35 possesses certain attributes and the desirability of those attributes (Ajzen & Fishbein, 1980). While an attitude is a ''general and enduring positive and negative feeling about some person object, or issue, a belief can be described as ''information that a person ha s about other people, objects, and issues'' ru1d this ''information may have positive negative, or no evaluative implications for the target of the information'' (Petty & Cacioppo, 1981 p. 7). Therefore, the feeling or attitude that people hold about online advertising formats should be derived from what people think, know, or believe about online advertising formats. The Relationship Between Beliefs and Attitudes Studies in the area of attitudes toward advertising often fa 1 l to draw a distinction between attitudes and beliefs often measuring beliefs in an attempt to measure attitudes (Muehling, 1987) Other studies have examined perceptual dimensions without directly relating them to advertising attitudes (Muehling, 1987). Other studies have examined this conelation between beliefs and attitudes toward advertising. According to Lutz (1985), attitude toward advertising in general is determined in part by consumer beliefs about advertising in general. A number of studies in the area of attitudes toward advertising have measured and then correlated attitudes toward advertising and consumer perceptions of the evaluative attributes, or beliefs, that form those attitudes (Aaker & Stayman, 1990; Alwitt & Prabbaker 1992, 1994 ; Biel & Bridgwater 1990; Cho, 1999 ; Mittal, 1994; Schlosser, Shavitt, & Kanfer, 1999; Shavitt, Lowrey, & Haefner, 1998). Generally speaking, these studies have found a positive corre lation between attitt1des and perceptions, but there are exceptions (see Mittal, 1994). Mittal (1994) found ratings on ten evaluative items about product-specific commercials to be congruent with overall likeability of the commercial, but this was not

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36 always the case More specifically some commercials were rated as enjoyable but were not liked As Mittal concluded '' The merits and demerits of product specific comm e rcial s do individually register on the consumer mind despite overall favorable or unfavorable predispositions '' (1994 p. 47). Applying this perspective to online advertising provides a possible explanation for why a user may not like a pop-up ad, even though it is perceived to be entertaining. Similarly, a u s er may rate a banner ad as infom1ative, but becaus e it i s associated with all online advertising, the user may not have a favorable attitude toward this format. Categorizing Beliefs About Advertising The strong emphasis on belief dimensions is attributable to Bauer and Greyser s (1968) influential study. In this study Bauer & Greyser (1968, p. 124) demonstrated how beliefs about advertising in general influence attitudes toward advertising in general. Bauer and Greyser's (1968) study categorized eight beliefs about advertising as either economic effects ( e g., ''raises standard of living'' or ''results in better products'') or social effects (e.g ., ''persuades you to buy what you don't need'' or ''insults the intelligence of an average consumer''). Others have adopted this approach to examining advertisin g beliefs as classifiable under these two factors (Reid & Soley 1982), and subsequent factor analyses supported this distinction (Anderson, Engledow, & Becker 1978 ; Andrews 1989). While Bauer and Greyser (1968) found consumers to have a generally favorable view of the economic role of advertising, they also found consumers to hold an unfavorable view of the social role Other studies have confirmed Bauer and Greyser s (1968) finding that consumers feel more favorable toward the economic role of advertising than the social role (Andrews 1989; Greyser & Reece, 1971) A study b y

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37 Anderson et al. (1978) of Consumer Reports subscribers found that attitudes became less favorable from 1970 to 1976 on both the economic and social factors of advertising. Beliefs have been studied in terms of generalized and personalized levels (Reid & Soley, 1982). P erso nalized belief items tap the influence of advertising on a person 's own behavior ( e.g., ''advertising misleads me'' (Reid & Soley, 1982)), while generalized belief items focus on how advertising affects the behavior of other people ( e.g., ''advertising misleads people'' (Reid & Soley 1982)) Researchers have demonstrated a significant difference in attitudes toward advertising's social and economic effects depending on whether personalized or generalized beliefs are used (Reid & Soley, 1982). Distinctions have also been made between the informational value of advertising and its persuasiv e effects. Research has demonstrated that consumers tend to have positive reactions toward advertising for its informational value and negative reactions toward advertising as a result of any perceived manipulation, intrusion, or deceit (Mehta, 2000; Shavitt, Lowrey, & Haefner, 1998). Sandage and Leckenby (1980) divided advertising attitudes into attitude toward the institution and the instrument of advertising. While institution reflects the purpose and effects of advertising, instrurnent refers to advertising's executional properties Mittal (1994) used this distinction in a study of attitudes toward television advertising Muehling (1987) examined the belief items that comprise these dimensions. Belief and Attrib11te Dimensions Included in Previous Studies Studies measuring attitudes toward the institution of advertising often incorporate belief statements to tap underlying dimensions. These statements often reflect the effects and consequences of advertising or the value of advertising For example, Mittal (1994) used belief statements to dete11nine whether televisio11 advertising offers useful social

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38 image infonnation, is a valuable source of information about local sales, a11d is sometimes more entertaining than the programs. Muehling (1987) measured the influence of 20 beliefs about advertising in general on attitudes toward the institution and instrument of advertising and found five of these beliefs to be significant and explain over 57% of the variance in attitudes toward advertising in general. The significant beliefs included whether advertising insults the intelligence of consumers, presents a true depiction of the advertised products, or wastes natural resources by creating desires for necessary goods. Whether a limit should be placed on the amount of money a company can spend on advertising and whether today 's standards for advertising are higher than 10 years ago were two additional significant predictors of attitudes toward advertising in general. Muehling (1987) concluded that the set of beliefs that influence attitudes toward advertising was smaller than expected and that beliefs about both institutional and instrument aspects of advertising influenced attitudes. However attitudes toward the institution of advertising were higher than attitudes toward the instrument, which was consistent with the findings of Sandage and Leckenby (1980). Measures of the advertising instrument often involve the use of attributes, as in the earlier Reaction Profile studies (Wells, 1964). In these studies, respondents are asked to indicate the extent to whicl1 attributes describe advertising or the percentage of advertising that can be described by the attributes. For example, Mittal (1994) used ten evaluative attributes (borrowed mainly from Santos, 1976) and asked respondents to assess the proportion of television advertisements that possesses each attribute The list included s11ch attributes as informative, honest,

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39 enjoyable, boring, annoying, and silly. Mittal (1994) further categorized these attributes under the headings of information/disinformation, enjoyment/annoyance and silliness. While infor1nation/disinformation was found to contribute the most to overall attitude toward advertising silliness was found to contribute the least (Mittal 1994) A number of belief dimensions have been identified by applying the Uses and Gratifications approach to the understanding of advertising particularly for tmderstanding the uses and gratifications of television commercials (Plummer 1971 ; Schlinger 1979) Using a factor analy s is of adjective s and descriptive statements Plummer (1971) found the ''viewer rewards'' of television to fall into seven categories including entertainment or stimulation, irritation familiarity, empathy or gratifying involvement, confusion info11nativeness or personal relevance and brand reinforcement Schlinger (1979) had similar fmdings in a related study of 49 adjectives and descrip t ive statements. The dimensions determined by this study included entertainment confu s ion, relevant news, brand reinforcement empathy familiarity and alienation or irritation In both of these studies co11fusion was des c ribed by items referring to the clarity of expression and organization of commercials. F amiliarity refers to the uniqueness or novelty of an ad ve rtisement. Tl1e Uses and Gratifications approach has been used to understand motivations for and benefits of surfing the Web and the characteristics a Web site should exhibit to be s ucces s ful (Eighmey & McCord 1997). Eighmey and McCord (1997) identified s ix factors that di s criminate between the be s t and worst Web sites and labeled the s e factors marketing perceptions (referrin g to the business relationship between the site and t1ser s), entertainment value info1mational value ease of use credibility, and interactivity

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40 The purpose of the following review is to understand the dimensions that have been established in previous studies. The current stt1dy will then derive its own dimensions for quantitative research. The dimensions presented in this section are for later comparison purposes and can be used as a benchmark for the dimensions derived in the current s tudy. These dimensions also provide a preview of the dimensions expected to be derived in this study. Studies on attitudes toward advertising particularly attitudes toward online advertising also suggest dimensions relevant to this research. The three belief dimensions that appear to be most relevant to the understanding of attitude toward onlin e advertising format date back to the 1968 study by Bauer and Greyser and were used in a more recent study by Ducoffe (1996) Ducoffe (1996) found the informational, entertainment, and irritation dimensions of adve1tising to be significant predictors of attitudes toward advertising. Buying confidence will be addressed as a subcategory of the informative dimension. Finally, offensiveness of advertising and other dimensions will be discussed Information. Bauer and Greyser defined informative ads as follows: These are ads that you learn something from that you are glad to know or know about They may tell you about a new product or service or they may tell you something new about a product or service you were already familiar with. Th e main thing is that they help you in one wa y or another because of the information they provide. (1968 p. 182) Bauer and Greyser's (1968) finding that attitude toward advertising is positively related to inforrr1ation-related reasons for liking advertisements possibly 1notivated the inclusion of the infonnational value of advertising in a number of subsequent advertising belief taxonomies (Alwitt & Prabhaker, 1992 1994; Ducoffe, 1996; Lee & Lumpkin

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41 1992; Mehta, 2000; Mittal, 1994 ; Muehling, 1987 ; Pollay & Mittal, 1993; Schlosser, Shavitt & Kanfer, 1999; Shavitt, Lowrey, & Haefner 1998). The idea that advertising provide s information to consumers is grounded in information theory (Gardner, 1983) The informational role of advertising has often been regarded as its foremost l egitimizing function (Rotzoll, Haefner & Sandage, 1989) and the ability of advertising to provide info1mation was found to be the primary reason for consumer approval (Bauer & Greyser, 1 968) Stigler's (1961) classic study was the first to demonstrate how advertising i s an important source of product information. Product information provided in advertisements is perceived to result in better decision-making by consumers (Alwitt & Prabhaker 1992) Furthermore, advertising has been found to stimulate competition, promote new product or brand entry, and simplify consumer sho pping (Albion & Farris, 1981 ). Resnik and Stem (1977) defined informative advertising as that which provides relevant informational cues to help a consumer make an intelligent choice among alternatives. Some of these cues inc lud e price, performance, quality, packaging and special offers (Resnik & Stem, 1977). Resnik and Stem (1977) found that over 49 % of the television ads samp l ed were inforrnative. A replication of the Resnik and Stern study found no significant differences in the overall pr ~ portion of informative ads in 197 7 and 1991 but did find significant differences in the use of various types of informational cues (Stem & Resnik 1991) In contrast, Aaker and Norris (1982) found just over 18 % of a sample of 524 prime-time television ads to be perceived by respondents as infonnative. In a more recent

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42 study, Mittal (1994) found that almost three fourths of respondents described only 25% or less of television advertising as ''informative and helpful .'' Other studies of magazine advertising found 923/o (Laczniak, 1979) and 86% (Stem, Krugman, & Resnik 1981) of the sampled consumer ads to be informative. Soley and Reid (1983) found consumers to be more satisfied with the info1mational value of magazine advertising than television advertising, although consumers were neither highly satisfied nor dissatisfied with the informational value of the advertising in either medium. More recent studies have examined the relationship between the informational value of advertising and advertising attitudes. Mittal (1994) determined that of 10 perceptions considered, perceptions of the informational value of advertising explained the most variance in overall attitude toward television advertising Pollay and Mittal ( 1993) found product information to be a significant predictor of attitudes toward advertising. Lee and Lumpkin (1992) found that the informational dimension of attitudes toward television advertising differentiates betw ee n those who rarely skip commercials on pre-recorded television programs and those who skip commercials sometimes or almost always. Informativeness has been positively related to Internet advertising attitudes (Schlosser, Shavitt & Kanfer 1999), overall advertising attitudes (Shavitt, Lowrey & Haefner, 1998), perceptions of advertising value (Ducoffe, 1996 ), and recall and buying interest (Mehta, 2000). In contrast to studies that found a positive relationship between perceptions of the informativeness of advertising and attitudes t owa rd advertising Alwitt and Prabhaker (1992) found beliefs about the informational value of television advertising to have little influ ence on attitudes toward television advertising. An

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43 explanation provided by Alwitt and Prabhaker (1992) for this result is the high intercorrelations among the four functions of knowledge hedonic social learning, and affirmation of value with only the hedonic function emerging as a significant variable in the multiple regression model. Related to info1 mativeness is the concept of buying confidence which has been addressed in a number of studies (see Mittal, 1994; Schlosser, Shavitt & Kanfer 1999) Mittal (1994) found no significant relationship between perceptions of buying confidence instilled by advertising and attitudes toward television advertising. In contrast Schlosser Shavitt and Kanfer (1999) found that the use of online advertising to make a purchase decision contributes to Internet advertising attitt:des Enjoyment/Entertainment Bauer and Greyser defined enjoyable ads as follows: These are ads that give you a pleasant feeling for any reason whatsoever They ma y be entertaining, amusing, especially attractive or well done. You might enjoy them whether or not you are interested in what is advertised. The main thing is that y ou lik e them and are pleased you s aw or heard them. (1968 p 182) Perceptions of the entertainment value of advertising has been considered in a number of previous studies (Alwitt & Prabhaker, 1992, 1994; Bauer & Greyser, 1968; Ducoffe 1996; Lee & Katz, 1993; Mehta 2000; Mittal, 1994; Pollay & Mittal, 1993 ; Schlosser Shavitt & Kanfer, 1999 ; Shavitt, Lowrey, & Haefner, 1998). Mayer (1991) found that purchase behavior is based on not only the consumer's assessment of the product itself but also the entertainment value of its advertising Alwitt and Prabhaker (1992) found beliefs about advertising's hedonic function contributed significantly to attitudes toward television advertising. Ducoffe (1996) found entertainment to be significantly correlated with perceived advertising value The enjoyment of advertising ha s been shown to be the strongest predictor of attitudes toward

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44 Internet advertising (Schlosser, Shavitt & Kanfer, 1999) and attitudes toward advertising (Shavitt, Lowrey, & Haefner, 1998) Pollay and Mittal (1993) found the dimension of hedonic / pleasure to be significantly and positively related to advertising attitudes. Mehta (2000) found that subjects who indicated that they enjoy looking at advertisements exhibited higher recall and stronger buying interest than those who do not enjoy looking at ads. Lee and Kat z (1993) found over three fourths of their sample of video store patrons disagreed that commercial s on a videotape are fun to watch. In contrast, Mittal (1994) did not find a relationship between entertainment value and attitudes toward television advertising but did find the group of evaluative dimensions labeled enjoyment/annoyance to contribute significantly to variance in attitude toward advertising. Annoyance / Irritation Bauer and Greyser defined annoying ads as follows: These are ads that irritate you They may be annoying because of what they say or how they say it. They may annoy you because they are around so much or becau s e of when and where they appear. There may be other reasons for ads to be annoying the main thing is that they bother or irritate you. (1968, p. 182) The idea that advertising is defined by or can be described by its level of irritation or annoyance is consistent with the foundations of Uses and Gratifications research (Eighmey & McCord 1998; Plummer 1971; Schlinger 1979) and attitude toward advertising studies (see Bauer & Greyser, 1968; Ducoffe, 1995, 1996; James & Kover 1992; Mehta, 2000). Irritation is such a pervasive issue in advertising that this characteristic has also merited a body of research about a common cause of irritation: advertising clutter (Elliott & Speck, 1998; Ha, 1997). Aaker and Bru z zone (1985) found irritation to be a reason for disliking advertising James and Kover's (1992) factor analysis of belief dimensions of attitudes toward

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45 advertising resulted in just two factors, with one referring to the irritation experienced fiom advertising. Ducoffe (1996) foW1d irritatio~ to be significantly related to perceptions of advertising value. Mehta (2000) did not find a relationship between the belief that advertising is annoying and e ith er recall or buying interest. As mentioned earlier, irritation may result from the advertising clutter (Elliott & Speck, 1998; Ha, 1997). Ha (1997) defined perceived ad clutter as resulting from three communication problems: hindered search, distraction, and disruption. Hindered search hampers a person's ability to read or see the media content, while disruption is a diversion from the media use experience and distraction is merely a lesser form of disruption. Alwitt and Prabhaker (1994) found that respondents were more likely to dislike television advertising when they believed that the same ads were shown too frequently. Other beliefs and attributes. A number of studies have examined the offensive aspects of advertising (Alwitt & Prabhaker, 1992, 1994; Bauer & Greyser, 1968; Schlosser, Shavitt, & Kanfer, 1999) or more specifically, poor taste and sex in advertising (Larkin, 1977). While Bauer and Greyser (1968) contended that an offensive ad may be considered annoying, they differentiated between these two dimensions by limiting offensiveness to the moral aspects of the product or advertisement or the effect on children. Bauer and Greyser defined offensive ads as follows: These are ads that are vulgar or morally bad in your opinion. They may be dishonest, or untrue. They may be ads for c;omething you don't think should be sold or used. They may be offensive because of the way in which they were done, and you may think that such ads should not be allowed. The main thing is that you feel strongly that such ads are wrong. (1968, p. 182)

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46 As defined by Bauer and Greyser ( 1968), advertising n1ay be considered offensive as a result of its use of deception. The deceptive nature of advertising has been examined as a distinct belief dimension of attitudes toward advertising (Alwitt & Prabhaker, 1992; Bauer & Greyser, 1968; Durand & Lambert, 1985; Larkin, 1977; Mehta, 2000; Muehling, 1987; Pollay & Mittal, 1993; Schlosser, Shavitt, & Kanfer, 1999; Shavitt, Lowrey, & Haefner, 1998). Alwitt and Prabhaker (1992) found that beliefs about the offensive aspects of advertising have little infll1ence on attitudes toward television advertising. Schlosser, Shavitt, and Kanfer (1999) found that beliefs about the indignity of advertising (i.e., insulting intelligence and offensiveness) were not related to Internet advertising attitudes. In contrast, Shavitt, Lowrey, and Haefner (1998) found perceptions of the indignity of advertising (together with the entertainment value) to have the strongest effect on predicting advertising attitudes. Alwitt and Prabhaker (1994) found a significant and positive correlation between dislike of television advertising and the perception of the offensiveness of the advertising. While Pollay and Mittal (1993) found the perceived falsity of advertising to influence attitudes, Alwitt and Prabhaker (1992) determined that the deceptive nature of advertising has little influence on attitudes toward television advertising. Mehta (2000) found perceptions of truth in advertising to influence buying interest. While Schlosser, Sl1avitt, and Kanfer (1999) found that trust of online advertising did not contribute significantly to Internet advertising attitudes, Shavitt, Lowrey, and Haefner (1998) found perceptions of the trustworthiness of advertising to have a sizable effect on overall advertising attitudes.

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47 Other studies have focused on the belief that advertising promotes materialism (Durand & Lambert, 1985; Larkin, 1977; Lee & Lumpkin, 1992; Mittal, 1994; Pollay & Mittal, 1993). Both Mittal (1994) and Pollay and Mittal (1993) found perceptions of materialism fostered by advertising to have a significant and negative relationship with attitudes toward television advertising. Lee and Lumpkin (1992) did not find that perceptions that advertising leads to wasteful buying discriminate between those who rarely skip commercials on recorded programs and those who skip commercials sometimes or always. A significant and positive relationship has been established between the perception that advertising is good for the economy and attitudes toward television advertising (Mittal, 1994; Pollay & Mittal, 1993). The perception that advertising totally or partially subsidizes the cost of media was also found to be a positive and significant contributor to attitudes toward television advertising (Mittal, 1 (}94). Another belief perception in studies of attitudes toward advertising is social role and image (Mittal, 1994; Pollay & Mittal, 1993). This belief reflects the idea that advertising often attempts to sell the consumer an image or lifestyle, rather than a product or service. Mittal (1994) found that social image information explained a significant amount of variance in overall attitudes toward television advertising. This construct has also been found to have a varied impact on attitt1des toward advertising (Pollay & Mittal 1993). Other studies have addressed the need for government regulation of advertising (Barksdale & Darden, 1972; Durand & Lambert, 1985; Larkin, 1977; Schlosser, Shavitt, & Kanfer, 1999; Shavitt, Lowrey, & Haefner, 1 ~98). Schlosser, Shavitt, and Kanfer

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48 (1999) found beliefs about government regulation of advertising to be unrelated to Internet advertising attitudes. Similarly, Shavitt, Lowrey, and Haefner (1998) found perceptions of advertising regulation and effects of advertising on prices to account for an insignificant amount of variance in overall advertising attitudes. Other beliefs examined in previous studies that were found to be unrelated to advertising attitudes include manipulation (Mittal, 1994), social learning (i.e., using advertising to learn how to behave in social situations) (Alwitt & Prabhaker, 1992) and value affmnation and corruption (Alwitt & Prabhaker, 1992; Pollay & Mittal, 1993). Any inconsistencies in the findings of the studies reported above may be attributable to differences in the operationalizations of the dimensions, the sample, or the focus of the study (whether examining attitudes toward advertising in general or in a specific medium). Attitudes Toward Advertising in a Specific Media Vehicle Since Bauer and Greyser (1968) noted the moderating effects of the advertising medium on attitudes toward advertising in general, research has focused on attitudes toward advertising in a specific media vehicle. In these studies, researchers have used belief dimensions from studies of attitudes toward advertising in general to understand attitudes toward advertising in specific media vehicles. These studies, however, rarely distinguish between different formats of advertisements within the same mediun1 While studies in this area have traditionally focused on television advertising (Alwitt & Prabhaker, 1992; Mittal, 1994 ), advertising in other media vehicles has also been studied. For example, Korgaonkar, Karson, and Akaah (1997) found that general advertising attitude scales are adaptable to direct mail advertising and that beliefs toward advertising in general are similar to beliefs toward direct mail advertising (Korgaonkar,

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49 Karson, & Akaah, 1997). This study found that while respondents had negative beliefs toward certain aspects of direct mail advertising, overall, beliefs were generally positive. The study also concluded that respondents who spent more money as a result of dir e ct mail advertising and ordered more frequently had significantly more favorable beliefs toward direct mail advertising (Korgaonkar Karson, & Akaah, 1997). Donthu, Cherian and Bhargava (1993) examined the relationship between attitudes toward advertising and ad recall in an outdoor advertising context and found that consumers with a positive attitude towa1d advertising in general were more likely to recall outdoor advertisements than those with a negative attitude. Using a sample of video store patrons, Lee and Katz (1993) concluded that respondents had generally negative feelings toward advertising on videocassettes Historically, overal l attitudes toward television advertising have been negative (Alwirt & Prabhaker, 1992; Bauer & Greyser, 1968; Bartos & Dunn, 1974 ; Mirta! 1994) Bauer and Greyser (1968) found that consumers perceive television advertising to be more annoying than advertising in other media. Alwitt and Prabhaker (1992) found perceptio11s of television advertising to be more negative than perceptions of advertising in general from two earlier Ogilvy and Mather studies (1974, 1985 as cited in Alwirt & Prabhaker, 1992) Mirta! (1994) found nearly half of his respondents reported that they do not like television advertising and only one fourth reported liking it somewhat. More recent studie s have suggested that attitudes about television advertising may be becomin g more favorable (Shavitt, Lowrey & Haefner, 1999). Specific issues with regard to television advertising incluc!e a general mistrust of advertising and feelings of insult. For example, Alwitt and Prabhaker (1992) found that

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50 about 16/4 of respondents believed advertising rresents advertised products accurately and 66% felt that advertised products do not perform as claimed. Mittal (1994) found the majority of respondents to consider less than one fourtl1 of television commercials to be honest and believable. In contrast, research points to some favorable attitudes toward certain aspects of television advertising. For example Alwitt and Prabhaker (1992) found that slightly more than half of their respondents considered television advertising to be funny or clever. Similarly, Mittal (1994) found that almost half of his respondents believed that television commercials are sometimes more enjoyable than the programs Recently, researchers have begun to explore attitudes toward Web sites, which serve as both advertising and a vehicle for advertising (Bruner & Kumar, 2000; Chen & Wells, 1999; Stevenson, Bruner & Kumar, 2000). Chen and Wells (1999) developed a scale to measure attitude toward the Web site, a construct that may be antecedent to the effectiveness of online advertising on that site. A study by Stevenson Bruner and Kumar (2000) found that as liking of a Web site increases, key variables in the advertising hierarchy-of-effects, namely attitude toward the ad attitude toward the brand, and purchase intention are improved. An Online Publishers Association study of 5,000 Internet users classified respondents into high-affinity and low-affinity users whereby affinity referred to the user's connection to and engagement with a site (Elkin, 2002b ). High-affinity users were less likely than low-affinity users to feel that ads interfered with their surfing experience and more likely than low-affinity users to believe the advertised brands are relevant to

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51 notice ads more and to believe the sites carry advertising for high-quality products and services (Elkin, 2002b ) Online Advertising Effectiveness The popularity of the World Wide Web and the subsequent rise of online advertising spending have led to studies of advertising in this medium. Effectiveness of Executional Elements A review of the literature reveals an emphJsis on the impact of executional elements of Internet advertising design (Bezjian-A very Calder, & Iacobucci, 1998 ; Bruner & Kumar 2000; Chen & Wells, 1999; Dreze & Zufryden, 1997; Li & Buko v ac, 1999; Stevenson Bruner, & Ktunar, 2000). Li and Bukovac (1999) found that animated banner ads result in a faster response and higher recall than non-animated ads. In addition, respondents were more likely to respond to and have higher comprehension of larger, rather than smaller, banner ads. Bruner and Kumar (2000) and Stevenson, Bruner, and Kumar (2000) examined the influence of background complexity on the advertising hierarchy-of-effects. In addition Bruner and Kumar (2000) also considered the effects of dynamic content ( e g ., animated graphics and commercials) on attitudes. Bn1ner and Kumar (2000) found that dynamic content had both a direct negative effect on attitudes toward the Web site and a positive indirect effect. Dynamic content was found to result in less favorable attitudes toward the site, which was attributed to the annoyance caused by this type of content In contrast dynamic content makes the site more interesting and thus, it is positively related to attitude toward the site Stevenson, Bruner and Kumar (2000) found that simpler backgrounds on Web sites had a more positive influence on the advertising hierarchy-of effects including attitude toward the ad, attitude toward the brand purchase intentions

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52 and attitude toward the Web site. Bruner and Kumar (2000) could not confirm this relationship is their study. Dreze and Zufryden ( 1997) found a relati0nship between a number of executional elements (i.e., background, image size, sound file display celebrity endorsement, use of java and frames and operating system) and the dependent variables of number of pages accessed and time spent on a Web site. Chen and Wells (1999) determined that the informativeness entertainment, and organization of a Web site influence consumer response to the site. Bezjian-Avery Calder, and Iacobucci (1998) found the interactivity of online advertising may hamper persuasion under certain conditions as indicated by decreases in purchase intention and time spent viewing advertisements when compared to the more ''linear'' advertising format of traditional ads. The authors suggested that the best combination appeared to be when the system properties (i.e., whether predominately visual or verbal) matched the individual processing needs (i.e., preferring information presented in a visual or verbal manner). Onli11e Consumer Behavior as a Measure of Effectiveness Consumer behavior has been the focus of much of the online advertising effectiveness literature (see Hoffman, Kalsbeek, & Novak, 1996, for a review) In counting clicks and hits researchers have attempted to qt1antify consumers' use of Web sites and advertising (Berthon, Pitt, & Watson, 1996). While these techniques have intuitive appeal and the data may appear more valid than that for other media measurement of consumer behavior produces an incomplete picture of the effectiveness of Internet advertising.

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53 Measures of online behavior have proven to be problematic, both overestimating and underestimating actual effectiveness (Internet Advertising Bureau, 1997; Rip hagen & Kanfer, 1997). For example, the number of ''hits'' (i.e a page view or impression) often overestimates effectiveness because the user may not have attended to the message content or the page may not have loaded properly. Clickthroughs on banner ads tend to underestimate effectiveness, since exposure to the banner ad alone may impact consumer attitude or future behavior (Briggs & Hollis, 1997). Another reason consumer behavior should not be used exclusively as a measure of effectiveness is that simply observing behavior (e.g., clickthroughs on online advertisements such as banner ads) does not reveal the attitudes behind that behavior (Berthon Pitt, & Watson, 1996). Attitudes Toward Online Advertising A review of the literature reveals a dearth of studies directly measuring attitudes toward online advertising. The few published studies in this area of research have built a solid foundation for continued study of attitudes toward online advertising by applying methodological and theoretical approaches from studies of attitudes toward advertising in general or attitudes toward advertising in a specific medium such as television. One focus of recent Internet advertising studies is attitudes toward Internet advertising in general. Schlosser, Shavitt, and Kanfer (1999) found that overall attitudes toward Internet advertising were mixed, with approximately one third of the sample feeling positive, one third feeling negative and the remaining one third feeling neutral. When compared to a demographically-similar sample's perceptions about advertising in general, fewer respondents felt positive toward Internet advertising than advertising in general (Schlosser, Shavitt, & Kanfer, 1999) Previte (1998) found that 54% of

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54 respondents agreed that online advertising was a good thing, 4 7% disagreed that their opinion of online advertising was unfavorable, and 38% liked online advertising. Some studies have incorporated belief dimensions from previous studies of attitudes toward advertising in general For exan1ple, Schlosser, Shavitt, and Kanfer (1999) examined five dimensions of attitudes toward Internet advertising including utility, indignity trust price perceptions and regulation They concluded that utility (comprised of the traits of infonnative, entertaining and useful for making decisions) explained 43 % of the variance in overall attitudes toward Internet advertising Ducoffe (1996) used a scale with the dimensions of informativeness, entertainment and irritation to determine perceived online advertising value While the correlations between these three dimensions and perceived value were all significant, the relationship between informativeness and perceived value was the strongest. Furthermore, Duco f fe (1996) found a positive and significant correlation between advertising value and attitude toward online advertising. Another focus of these studies is the relationship between attitudes toward online advertising and attitude toward the ad. Cho (1999) found that subjects with more favorable attitudes toward Web advertising overall had a more favorable attitude toward a specific banner ad. Advertising attitudes and clicking behavior have been examined as well (Brill 1999; Cho, 1999). Cho (1999) studied the relationship between attitudes toward online advertising in general and clicking behavior. He found that the three of the five belief statements used to as s ess overall attitude toward Web adve1tising were capable of discriminating between subjects with a high intention to click through a banner ad and

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55 those with a low intentio11. The discriminating belief statements included the following : Web advertising supplies valuable information, Web advertising is necessary, and Web advertising is valuable. Brill (1999) found that consumers who had clicked on specific banner ads had more favorable attitudes toward the banner ad and higher purchase intentions toward the products or services advertised in the banner ad than for unclicked banner ads. An analysis by Briggs and Hollis (1997) focused on the influence of banner ads on consumers' attitudes and behavior They found that for five of the six banner ads that met the threshold on brand perception items, consumers exhibited a significant positive change in attitudes as a result of exposure to the ads. The above discussion illustrates a recent focus of attitudes toward advertising literature on attitudes toward online advertising. In examining be l ief dimensions of online advertising attitudes and demonstrating the relationship between attitude toward online advertising and attitude toward the ad researchers have expanded the applicability of th e attitudes toward advertising construct. While several studies have examined attitudes toward Internet advertising (Ducoffe, 1996; Mehta & Sivadas, 1995; Schlosser Shavitt, & Kanfer, 1999), fewer have distinguished among the various online advertising formats. Previous studies on Internet advertising often either considered attitudes toward online advertising in general (Ducoffe 1996; Schlosser, Shavitt, & Kanfer, 1999) or examined one format of online advertising (e.g., newsgroup and e-mail advertising (Mehta & Sivadas, 1995)) Others have compared one online ad format to advertising formats in traditional media (Dynamic Logic, 2001 b) or compared two or more online ad fonnats (Dynamic Logic, 2001 b ;

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56 Harris Interactive 2001; Statistical Research, 2001). No study has attempted to understand the range of dimensions that influence attitudes toward various online advertising formats or the impact of attitude toward online advertising for1nat on other variables. Studies of attitudes toward Internet advertising often ask respondents to respond to survey item s with all online advertising formats in mind ( e.g. Ducoffe 1996; Schlo s ser Shavitt & Kanf e r 1999) In the studies by Ducoffe (1996) and Schlosser Shavitt, and Kanfer ( 1999), the researchers did not define the range of online advertising formats for the respondents. In the Schlosser et al. study Internet advertising was defined as ' any form of commercial content available on the Internet that is designed by businesses to inform consumers about a product or service ' (1999, p. 36). As a result respondents almost certainly answered with unique representations of online advertising in mind In addition although these studies collected data on respondents' definitions of online advertising no comparisons were made between these conceptualizations and overall attitudes Other studies have focused on only a small subset of online ad formats. Mehta and Sivadas (1995) concluded that consumers held unfavorable attitudes toward advertising on newsgroups and via e-mail regardless of the degree of relevance of the message to the special interests of the group. Briggs and Hollis (1997) and Cho (1999) focused specifically on banner advertising While Briggs and Hollis (1997) considered attitude toward a banner ad as an independent variable and studied its effect on brand attitude Cho (1999) studied the influence of attitude toward Web advertising in general on

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57 attitude toward a banner ad and clicking intention. These findings of these studies may be limited by the narrow focus. A study by Statistical Research (2001; Jackson, 2001 b) compared consumer attitudes toward banner ads to attitudes toward pop-up ads. Respondents were more likely to agree strongly or somewhat that they notice pop-up ads more than banner ads (76% vs. 69%) and that pop-up ads interfere with reading or using a Web page (84% vs. 54 %). Respondents were also more likely to disagree strongly or somewhat that companies that use pop-up advertising are market leaders more so than companies that use banner advertising (57% vs. 48%) A study by Harris Interactive (2001) compared Superstitial advertising to television advertising in tenns of some classic communication research measures, including recall, communication, and persttasion. The study found that for the three ads tested Superstitials communicated the copy points as well or better than television ads. Two of the three Superstitials tested were as likable as the television commercials. Intentions to use, buy, or consider the brand were comparable for both Superstitials and television commercials in all three cases. Finally, brand recall for Superstitials was sligl1tly lower than that for television ads (81 % vs. 93%). The Interactive Advertising Bureau examined the use oftl1e large rectangle ad forn1at in a study for Coca-Cola (Lefton 2001 b ). The ad showed a lift in message association by 56 %, brand favorability by 7%, and purchase intent by 5% {Lefton, 2001b). A study by Dynamic Logic (2001 b) compared attitudes toward a number of online ad formats. Over half of the respondents had a positive attitude toward banner advertising

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58 (53%), followed by skyscraper ads (35 /4 ), large rectangles (17%), pop-ups (6 % ), and interstitials (3%). This study also examined attitudes toward pop-up advertising and traditional formats of advertising. Newspaper, magazine, radio, and billboard advertising were found to be more desirable than pop-up advertising, while telemarketing, direct mail, and television advertising were less desirable While more comprehensive in term s of formats than other studies, the Dynamic Logic study lacked a theoretical emphasis and did not measure other important variables such as A ad and online ad perceptions. Studies measuring attitudes toward online advertising in general are often too broad to provide practical value to the advertiser Because each online ad format possesses distinctive features, attitudes toward online advertising could differ depending on the user's perception of what constitutes online advertising. Furthermore, the findings of studies that focus on only one online ad format are not generalizable to other online ad formats. As demonstrated a review of the literature reveals no comprehensive study of attitudes toward specific online advertising for1nats within a theoretical model of advertising Although such a study has yet to be published, researchers are raising questions about the relationship between attitude toward the online ad format and attitude toward the ad. As previously mentioned, Rodgers and Thorson (2000) included ad formats and attitude toward the ad in their Interactive Advertising Model, but did not test this relationship. Schumann, Artis, and Rivera (2001) suggested a number of research questions for future research including ''What negative influences on consumer perceptions are likely to arise from interactive advertising formats?'' and 'Which interactive media fo11nats will best facilitate relationship management?''

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59 Advertising on the Internet is still evolving manifesting itself in a variety of formats, from banner ads to pop-ups to Webmer .:: ials. The Internet provides a more versatile medium for advertising than traditional vehicles and this versatility has led to the development of the varied online advertising formats. While the Internet is an appropriate context to study attitude toward ad format it is also critical that attitude s toward online fom1ats are thoroughly examined With the seemingly limitless possibilities for online advertising forn1ats an understanding of consumer attitudes and belief dimensions can certainly infotm the future development of online advertisin g. Proposed Model The Interactive Advertising Model developed by Rodgers and Thorson (2000 ) integrates the function of the Internet for consumers (i.e consumer-controlled aspects) and the structur e of Internet ads (i.e ., advertising-controlled aspects) to suggest consumer responses, which include a1nong others the formation of attitude toward the ad One of the advertiser-controlled Internet ad structures in the model is '' ad formats ," such as banners, interstitials and sponsorships (Rodgers & Thorson 2000) Another is 'ad features, which are objective (i.e advertiser-controlled) and subjective (i.e., cons umer controlled) variables The objective ad features for the Internet include color, animation and audio, while the subjective ad features include exciting interesting, and boring (Rodgers & Thorson 2000). This model has two in1plications for the current study. First this model s uggests a relationship between ad format and attitude toward the ad. Second this model acknowledges th e role of ad features or perceptions in attitude for1nation The foregoing discussions of the Interactive Advertising Model (Rodgers & Thorson 2000 ), the s tructural model of the antecedents to attitude toward the ad

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60 (MacKenzie & Lutz, 1989; Lutz, 1985) and the literature of attitude toward advertising attitude toward advertising in a media velucle and attitude toward online advertising provide a foundation for understanding how attitude toward online ad format may fit into the existing attitude toward the ad model. Figure 2 2 illustrates the structure of a st1bsection of the proposed model. Attitude toward Internet Online Ad Format Perceptions Attitude toward Online Ad Format Attitude toward Web Site Attitude toward Online Advertising Figure 2-2. Proposed Structural Model of Aad Formation (showing two antecedents) in an Online Advertising Context Attitude toward online ad format is proposed as an antecedent to attitude toward the ad. Figure 2-2 illustrates two antecedents for A ad: attitude toward online ad for1nat and attitude toward online adverti s ing. The variable of attitude toward online advertising serves to separate attitudes toward all advertising from those only related to online advertising. As a relatively new form of advertising using a medium unlike other media

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61 online advertising may produce attitudes that are distinct from attitudes toward advertising in general as found by Schlosser et al (1999). Underlying attitude toward 011line ad form1t are perceptions of online ad format s Just as attitude toward the ad is determined by ad perceptions (MacKenzie & Lut z, 1989) attitude toward online ad forrnat is predicted to be deterrnined by online ad format perceptions Because these perceptions may parallel many of the perceptions of advertising a thorough discussion of these perceptions or beliefs was provided Thi s research will identify other possible belief dimensions for the various online advertisin g formats Furthermore, this 1nodel proposes that attitude toward online ad format is influenced by attitudes toward online advertising. In addition, a user's attitude toward the Internet may influence attitude toward online advertising formats For advertising hosted on a Web site attitude toward a Web site may influence attitude toward the ad format. This relationship is suggested by previous research that found a strong and significant correlation between an attitude toward a television program and attitude toward television advertising, even after controlling for demographic variables (Alwitt & Prabhaker, 1992). Because the current interest is focused on attitude toward the online advertising forrnat only a subset of the entire A a d model was tested. The subsequent findings should provide a framework for further research into other parts of the model Conclusion This chapter presented the A ad model and then examined the research on attitude s toward advertising in general in more detail. Recent trends in research on attitudes toward advertising were also addressed, including the emphasis on understanding attitudes

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62 toward advertising in a specific medium and attitudes toward online advertising. Finally this review described how the proposed concept attitude toward online advertisin g format fits into the existing model and suggested hypotheses to be tested Chapter 3 discusses the first study in this research. This study used a qualitative approach to derive perceptions of specific online advertising formats and determine which formats should be included in a quantitative study that will test these relationship s.

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CHAPTER3 STUDY 1 Purpose The purpose of Study 1 was to use qt1alitative research to investigate the determinants of attitude toward online advertising forrnat with special emphasis on defining the dimension s of ad format perceptions, and to uncover online ad formats appropriate for further study. Research Questions The research questions guiding this study were as follows: 1. What online advertising formats should be included in a study of attitudes toward online ad formats? 2. What are the online ad format perceptions underlying online ad format attitudes? Critique of Methodology i~1 Previous Research The perceptual dimensions underlying advertising attitudes and the items used to measure them have often been constructed through reviews of previous studies rather than through exploratory methods (O'Donohoe, 1995). The influential study published by Bauer and Greyser (1968) has historically been the basis for many perceptual inventories. The use of items from previous studies offers the advantages of replication and continuity. While the precedent has been to adapt previous perceptual dimensions to the area of study, the validity of the measures relevant to a particular area ( e g., onli11e advertising) may be improved by using exploratory research, such as focus grot1ps or interviews, to derive and defrne the appropriate dimensions (Churchill, 1979). For 63

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64 example, Muehling (1987) and Pollay and Mittal (1993) incorporated thought-listing techniques and open-ended questions to derive perceptual dimensions rather than relying so lely on previous research Perceptual dimensions from previous studies of attitudes toward advertising could have been applied to a study of attitude toward online ad format. However, because attitude toward the format is a newly-considered construct, it was important to enhance the validity of the measures to be used by conducting preliminary qualitative research. Method Study 1 included depth interviews with industry experts and experienced online users to explore online ad format perception s. Tl1e literature review (Chapter 2) identified perceptions of advertising in general or advertising in a specific medium The purpose of this review was to form a foundation of understanding advertising perceptions and for comparison purposes following the depth interviews. Depth Interviews With Industry Experts Depth interviews with industry experts provided insight into the online advertising forrr1ats that are most important, prevalent, distinct, and emerging, as well as the perceptual dimensions on which the various online ad formats can be distinguished Sample. A total of 34 online advertising experts were identified representing academe (6) and the advertising industry (26). Advertising academicians were selected from the set of authors of papers or articles on fr e topic of online advertising published during the past three years in the Proceedings of the Arrzerican Academy of Advertising, the Journal of Advertising, the Journal of Intera ctive Advertising, and the Journal of Advertising R esearch Practitioners were selected from those who either wrote or were quoted in trade publication articles about online advertising. In addition, indu s try

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65 members of the American Academy of Advertising were contacted for referrals and a message was posted on the Online Advertising Discussion List to solicit additional prospects. Eleven members of the advertising community, including academicians and practitioners, were interviewed. Of those in academe, five were contacted and three completed the interview. Of those in industry, 11 were contacted and 8 completed the interview Sixty-nine percent of the contacts made resulted in a completed interview The academe participants represented the fields of marketing (2) and advertising (1). The industry participants included three who work for research organizations, one Web site advertising account director, two interactive creative directors, and two former employees of online advertising networks The selected individuals were contacted by e-mail and invited to participate in this research. The informed consent form was either faxed or sent via e-mail. The interviews were conducted by phone and lasted approximately 20 minutes to one hour. Measures. The depth interviews with industry experts served to narrow the online ad formats that should be considered for further research to facilitate the later collection of detailed data on online advertising formats and determine online ad format perceptions Participants were asked to list prevalent online ad formats They were also asked to name formats that are and will be important in the future should be included in an attitude study, and are n1ost similar or dissimilar, with special emphasis on the dimensions that differentiate the formats Participants were also asked to describe their

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66 opinions of various online advertising forrr1ats. A discussion guide for the interviews with industry experts is included in Appendix A. Depth Interviews With Experienced Online Users Depth interviews with experienced Web surfers were 11sed to further develop a typology of the dimensions of online ad formats and determine user familiarity with the range of online advertising formats. Sample. Experienced Web surfers were located tlrrough e-mail recruiting. Seventeen students from a large southern university and six non-students from a southern metropolitan area were screened for the interview. The screening process involved asking questions about familiarity with online advertising formats and the amount of time spent surfing the Web during the typical week. Prospective participants who exhibited the highest levels of familiarity with multiple online advertising formats and spent the greatest amount of time online were selected based on the assumption that they would be able to discuss online advertising formats more knowledgeably, thereby producing more valuable data. To somewhat disguise the purpose of the study prior to the actual interview, prospective participants were also asked to name three Web sites they regularly visit and up to three sites from which they have made an online purchase. Of those recruited, six students and four non-students qualified to participate in the interview. All students who were interviewed reported surfing a minimum of eight hours per week (M = 10.8). All non-students except one estimated that they spend at least 20 hours per week surfing the Web, while one reported spending approximately 45 hours per week surfing. All participants were familiar with at least three formats of advertising prior to the interview.

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67 Once an individual qualified to participate, an appointment for the hour-long interview was arranged. Participants were paid $25 for their participation. Stimuli Stimulus ads were selected from the advertising displayed on several popular Web sites, as well as various online galleries, collections, and portfolios. Table 31 lists the advertisers used to illustrate each of the formats. The stimuli represent a broad range of online advertising forrnats mentioned by Internet advertising experts including banners, buttons, floating ads, pop-ups, interstitials, large rectangles, skyscrapers, and Top Roll. Table 3-1. Advertisers Represented in Stimulus Ads Online Advertising Format Advertiser Banners Apartmentguide.com, Casino on Net, UBid Buttons Amazon, Staples, Wal-mart Floating ads Circuit City, Emirates Airlines, Boston Red Sox, ING Pop-ups Air Force, Nikon, Ford Expedition Interstitials Glaxo, Casino on Net Large rectangles Absolut, Dell, IBM Skyscrapers Best Buy, Classmates Top Roll Ford Focus, Coca-Cola During the interview, a laptop computer was used to demonstrate online ad for1r1ats. Ads were shown in the context of a Web site to simt1late an actual ad rmpress1on. Measures. Participants were first asked about their general impression of online advertising. The interview a l so tapped specific online advertising formats to deter111ine

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68 familiarity with various online advertising formats, opinions of these formats, and the differences among the formats. Participants were then asked to focus specifically on one ad format. Three examples of each format were presented for illustrative purposes. Thought-listing was implemented at this point. This approach has been applied successfully in the study of advertising (Batra & Ray 1986; Lut z & MacKenzie, 1982) and 1nore specifically to the study of attitudes toward advertising in general (Muehling, 1987). Participants were invited to read the standard thought-listing instructions (Cacioppo & Petty 1981) and were given two minutes to complete each thought-listing exercis e. They were instructed to write their thoughts about each online ad format as it was presented The most prevalent thoughts were considered appropriate for further anal y si s. Participants were also asked to describe w~at they like and dislike about the ad format as well as their opinion o f Web sites that use the ad format. Tlus process wa s repeated for a total of five online advertising formats. Finally participants were asked describe the similarities or dissimilarities among various online advertising formats Questions used in the depth interviews with experienced Web users are included in Appendix B. Procedure for Selecting Online Advertising Formats Four crite1ia were used to determine the inclusion of an online advertising format in future studie s The ad fo1rr1ats chosen can be described as prevalent important distinctive, or emerging with many of the ad formats representing several of these categories First only the most prevalent online ad formats were considered. These formats included those m e ntioned by Web surfers during unaided recall those that Web sur f er s

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69 were familiar with during aided recall, and formats cited as the most prevalent by industry experts. These formats were also compared to those representing the highest percentage of online creative elements as reported by AdRelevance (2003) and online advertising revenue as reported by PricewaterhouseCoopers (2002) in the IAB Internet Advertising Revenue Report. Second, important ad formats were considered for inclusion. To determine the important advertising formats, advertising experts were asked which formats should be included in a consumer attitude study about online advertising formats. Third, to further narrow the possibilities, only distinct advertising formats were selected. Therefore, if two formats are virtually indistinguishable to Web surfers or the experts, one was dropped from further study. Advertising experts were asked to describe various categories of advertising formats. Experienced Web surfers were asked to compare and contrast several for1nats. Finally, emerging online ad formats cited by industry experts were considered. The goal of this selection process was to determine five to eight prevalent, distinct, important and emerging online ad fo11nats, as this number should be manageable for a later quantitative study Format Selection Results From the experienced Web surfer interviews, banners and pop-up ads emerged as the two most frequently cited formats in terms of unaided recall. Almost all participants mentioned pop-ups during unaided recall of online advertising formats and most mentioned banner ads. Participants were familiar with most of the formats demonstrated. Table 3-2 illustrates how the formats ranked in terms of unaided recall and recognition.

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70 The ad for1nats with the most mentions during the interviews with Internet advertising experts included banners, pop-ups, pop-unders, skyscrapers, large rectangles floating ads, sponsorships, and interstitials. Other ad for1nats mentioned included top Rolls, jump pages, Superstitials fixed logos, buttons, towers, Web sites, search engine listings, electronic mailing lists, text links, streaming media, and e-mail. Table 3-2. Unaided Recall and Recognition of Online Ad For1nats by Experienced Web Surfers (N = 10) Format Pop-up Banner E-mail Pop-under Floating ads Instant messaging Tower Large rectangle Button Contextual Skyscraper Interstitial Top Roll Sponsorship *Not demonstrated. Unaided recall N 9 7 4 2 2 1 1 1 1 1 1 0 0 0 Recognition N 10 10 10 8 * 10 10 6 10 9 8 4 The IAB Internet Advertising Revenue Report conducted by PricewaterhouseCoopers repo11ed that the tvi r o f 01111ats garnering the highest percentage

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71 of revenue for the first six months of 2002 were banners and sponsorships (PricewaterhouseCoopers, 2002). Banners represented 33% of online banner revenue and sponsorships represented 24% (PricewaterhouseCoopers, 2002). Interstitials and rich media ads (e.g., floating ads) each represented 3% of revenue (PricewaterhouseCoopers, 2002). In contrast to PricewaterhouseCoopers' method of calculating the proportion of total online advertising revenues each format contributes, AdRelevance bases its data on the total number of creative elements. According to AdRelevence data (2003) for the week of April 28, 2003, banners were the most prevalent online advertising fonnat, representing 33o/o of online advertising elements. Including half banners increases this percentage by 4% (AdRelevance, 2003) Skyscrapers also represented a high percentage of online advertising elements at 17% for standard skyscrapers, wide skyscrapers, and vertical banners combined (AdRelevance, 2003) Buttons represented 14% of elements, and squares and medium rectangles totaled 10% (AdRelevance, 2003). When asked what advertising f onnats should be included in a consumer attitude study about online advertising formats, advertising experts were most likely to mention banners, pop-ups, pop-unders, skyscrapers, floating ads, and sponsorships. Other formats with fewer mentions included Point Roll, Superstitials large rectangles, and text links. Advertising experts suggested the following categorization schemas: flat, animated, or interactive ads; small, larger, or floating ads; ads contained within Web page or ads outside of Web page. Both experienced Web users and advertising experts often perceived advertisements that were integrated into the content of the Web page to be one distinct group and advertisements that appeared over or under the content to be another.

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72 In further categorizing ads that are integrated into page content, skyscrapers and large rectangles were often perceived to be distinct from banners and other smaller ad formats such as buttons. Another category identified were ads that appeared in the place of content, st1ch as interstitials and Superstitials Using this framework, banners large rectangles, skyscrapers, towers, and buttons would fall into one category while pop-ups, pop-unders, floating ads, and Top Rolls would be a separate category. Interstitials and Superstitials would constitute a third category. Ads integrated into page content might be further classified as large or small. Finally, emerging online ad formats cited by industry experts were considered for inclusion. From the interviews with the advertising experts, floating ads were often cited as an emerging fotmat that will become more popular in the future. Larger sizes, such as large rectangles were also mentioned as a trend in online advertising. Analysis of fotmats using these criteria produced six advertising formats that were used in subsequent studies: banners, pop-ups, floating ads, skyscrapers, large rectangles, and interstitials. All of these forrnats were mentioned the most often by advertising experts, and banners and pop-ups had the highest unaided recall by experienced Web surfers. Furthennore, floating ads and large rectangles were often cited as emerging forrnats. Banners, pop-t1ps, floating ads, and skyscrapers were all mentioned by advertising experts to be important to include i11 an advertising attitudes study. While interstitials were not cited as important or emerging, they were often cited as prevalent by advertising experts. In addition, they represent a unique category of ads that appear between content and are distinct from other formats. Table 3-3 illustrates how these six for1nats rate on the four decision criteria.

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73 Table 3-3. St1mmary of Performance of Chosen Formats across Selection Criteria Criteria Banner Pop up Skyscraper Floating Large Interstitial Rec Prevalent Important Distinct Emerging X X X X X X X X X X X X X X X X X X At this point, it is important to note that although a number of advertising experts considered sponsorships to be an important online advertising format, and sponsorships represented the second highest percentage of online advertising revenue for the first half of 2002 (PricewaterhouseCoopers, 2002), this format was not considered in subsequent studies for two reasons First, sponsorships are often comprised of other online advertising formats Second because sites offer a wide variety of sponsorship opportunities, there is no single defmition of a sponsorship. Other ad formats were dropped from consideration because they were not distinguishable enough from another format. For example, while pop under ads were often cited as prevalent and important, this format is quite similar to pop-up ads. In contrast although skyscrapers and banner ads are similar in shape, skyscrapers were inc l uded in the list of fonnats for future study. Banners were one of the first format s to emerge online, while skyscrapers are a more 1ecent creation. For this reason, it is possible that attitudes differ. In addition some participants associated skyscrapers more with large formats, such as large rectangles and banners with smaller formats, such as buttons. The placement of the ads also differs, with banners placed across the top of a Web page and skyscrapers a l ong the side.

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74 Perceptual Dimensions of Online Advertising Formats Online advertising perceptions emerged from an a11alysis of the responses to the interview questions These perceptions were then categorized into dimensions using ''conceptual factor analysis''. Internet advertising experts mentioned a total of 40 unique perceptions in descriptions of online advertising which were used to define perceptual dimensions A conceptual factor analysis of the perceptions was performed by grouping similar ( or opposite) perceptions into the same category. Within each category, the perceptions are either synonyms (or antonyms) or were used by participants to describe the same concept. This analysis resulted in the categories presented in Table 3-4. An indication of the incidence of mention for each category is also provided. Web surfers mentioned a total of 84 unique perceptions in descriptions of Internet advertising, which were also used create dimensions. Once again, a conceptual factor analysis of the adjectives was performed in the same manner described previously. This analysis resulted in categories presented in Table 3-5. Because of the vast number of adjectives mentioned by Web surfers, an attempt was made to further refine the categories developed from the data for the advertising expert sample. An indication of the incidence of mention for each category is also provided. Irritation ''Annoying' and ''irritating'' clearly emerged as the most common descriptors of online advertising. This dimension was more generally described by advertising experts with the following adjectives : annoying, interrupts, intrusive, abrupt, distracting, and interferes.

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75 Table 3-4. Descriptors of Online Ad Fo1mats Used by Online Advertising Experts Descriptors N Annoying Interrupts, Intrusive Abrupt, Distracting, Interferes 7 Info1n1ational value, Content, Compelling message, Room for content 7 % of screen occupied, Position Size of ad, Clutte1, Obtrusive 6 Relevance, Targeted 5 Interactive, Involvement 5 Control Forced vs voluntary, Choice 4 Cutting edge, Different, Sophisticated, Innovative Clever, Creative 4 Animation Flashing Static (ant ) 3 Enjoyable Entertaining 2 Classic, Tasteful, Cordial 1 Copy heav y 1 Provides reward 1 miquito~ 1 Visual 1 Note. N = number of participants who mentioned at least one of the descriptors. Other categories which may contribute to the annoyance of online advertisin g i11clude one referring to the cl11tter caused by online advertising (percentage of screen occupied, position of ad, size of ad, clutter, obtrusive), one referring to the activity of online ads (flashing, animated) one referring to the ubiquity of ads (ubiquitous) and one referring to the ability of the user to control the surfmg experience ( control forc e d voluntary, choice).

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76 Table 3-5. Descriptors of Online Ad Formats Used by Experienced Web Surfers De scri ptor s Animated, Flashy, Blinking, Movement, Hyperactive, Static (ant.) Annoying, Both erso me, Frustrating Disruptive, Distracting, Diverts attention, Distorts content, Gets in the way, Takes over page, Takes up space, In your face/Out of the way, Interferes with background, Intrusive Inconvenient, Tin1e-consuming, Quick (ant.) Entertaining, Exciting, Fun, Appealing, Cool, Neat, Amusing Catches attention, Holds attention, Eye-catching, Interesting, Noticeable, Obtrusive, Blends with site (ant.), Easy to ignore (ant.), Contrasts with background Innovative Inventive, Clever, Cutting-edge, Different Creative Forced exposure, Wanted/unwanted, Control, Removal requires action Cluttered, Overbearing, Pervasive, Obtrusive Cool graphics, Good pictures, Images of product, Interesting graphic Bold Bright colors, Colorful Audience-driven, Relevant to content Big, Small, Size, Space Simple Plain Beneficial Useful offerings, Pointless (ant.) Cute, Eyesore (ant.) Informative Separate from page On page Easy to read Too many words (ant.) Respectful, Good/bad etiquette Extravagant, Dynamic Interactive Involvement Sound Repetitious N 10 10 9 9 9 9 8 7 6 6 5 5 4 4 4 3 3 3 2 2 2 2 2 1 Deceptive 1 Note. N = number of participants who mentioned at least one of the descriptors.

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77 As mentioned previously the volume of descriptors mentioned by Web surfers warranted developing seve ral categories which may by encapsulated into the broader category of ''annoying'' from the general descriptions of annoying, bothersome, and frustrating to more specific segmentations. These segmentations include one that refers to the disruption of the surfing experience ( disruptive distracting, diverts attention, distorts content, gets in the way, takes over page, takes up space, in your face / out of the way, interferes with background, intrusive, cluttered, overbearing, pervasive). Another segmentation of annoyance refers to the activity of the ad itself, which includes such descriptors as animated flashy, blinking, movement and hyperactive. Yet another segmentation refers to the time involved in dealing with online ads as expressed by the descriptor s of inconvenient and time-consuming. Finally, irritation may be caused by the fact that online advertising is often forced onto the user, which was described as forced exposure, wanted/unwanted, control, and requires action to remove. In fact, Li, Edwards, and Lee (2002) fo1.1nd the mea s ure of intrusiveness to be independent from that of irritation, which provides some evidence for the separation of irritation and intrusion. The fmding that online advertising is defined by or can be described by its level of irritation or annoyance is consistent with that of Uses and Gratifications research (Eighmey & McCord, 1997; Plummer 1971; Schlinger 1979) and attitude toward advertising studies (Ducoffe, 1995 1996). Irritation is such a pervasive issue in advertising that this characteristic has also merited studies about it exclusively, as demonstrated by the advertising clutter research (E lliott & Speck 1998 ; Ha 1997 ). Entertainment Online advertising was also described by participants in terms of its entertainment value. These categories ranged from the general category of entertainment ( entertaining,

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78 enjoyable, exciting, fun, appealing, cool, neat, amusing) to more specific categories referring to activity of the ad itself (animation, flashing, blinking, movement, hyperactive), to the fact the ad is eye-catching ( catches attention, holds attention, eye catching, interesting, noticeable, obtrusive, contrasts witl1 background), or to the entertainment value in the graphics of the ad ( cool graphics, good pictures, images of product, interesting graphic). As noted in Chapter 2, perceptions of the entertainment dimension of advertising have been considered in previous studies (Alwitt & Prabhaker, 1992, 1994; Bauer & Greyser, 1968; Ducoffe, 1996; Lee & Katz, 1993; Mehta, 2000; Mittal, 1994; Pollay & Mittal, 1993; Schlosser, Shavitt, & Kanfer, 1999; Shavitt, Lowrey, & Haefner, 1998). Information While the info1mation dimension clearly emerged from the interviews with advertising experts, Web surfers were less likely to mention it. While only three Web surfer participants noted the informativeness of online advertising, advertising experts described information in terms of informational value, content, compelling message and space in ad for content. Because many of the advertising expert participants were responsible for creating or selling online ads, they should be more attuned to the content possibilities of online advertisements, providing a possible explanation their emphasis on information. The Web surfer participants may have been more focused on tl1e design or behavior of the online ads during the interview, particularly if the advertised product was not of interest to them While this dimension was not described in great detail by Web surf er participants, its mention by advertising experts and its dominance in both Uses and Gratifications research (Eighmey & McCord, 1997; Plummer, 1971; Schlinger, 1979) and attitudes

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79 toward advertising research (Alwitt & Prabhaker, 1992, 1994; Ducoffe, 1996; Lee & Lumpkin, 1992; Mehta, 2000; Mittal, 1994; Muehling, 1987; Pollay & Mittal, 1993; Schlosser, Shavitt, & Kanfer, 1999; Shavitt, Lowrey, & Haefner, 1998) warrants its inclusion in further studies. Informativeness is also linked to relevance, as determined by Plummer ( 1971) who identified ''informativeness and personal relevance'' as a factor explaining attitude toward television commercials. The relevance of an online ad was mentioned by participants who used such adjectives as audience-driven, relevant to content, and targeted to describe this dimension. Web surfers also referred to online ads as beneficial or having useful offerings, which can also be incorporated under this dimension. Novelty The novelty dimension also emerged f1om the qualitative research. Advertising was described as cutting edge, different, sophisticated, innovative, clever, creative, and inventive. Both Plummer (1971) and Schlinger (1979) identified this dimension in their studies of attitudes toward television commercials. Interactivity The interactivity of or involvement with online ads also surfaced during the interviews. Interactivity has been defined as ''the extent to which users can participate in modifying the form and content of a mediated environment in real time'' (Steuer, 1992, p. 84). This characteristic was addressed more by advertising experts, which may be explained by the experience of many of the experts with the sophisticated technologies used to create interactive online ads. Again, this dimension has appeared in Uses and Gratifications studies as either ''involvement'' (Plummer, 1971) or ''interactivity'' (Eighmey & McCord, 1997).

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80 Composition The final dimension is the ''look'' or composition of the online advertisement. Web surfers defined this characteristic with descriptors referring to the colors of th e ad (bright colors, colorful, bold), the size (big, small), the simplicity (simple, plain), the text (easy to read, too many words), or the overall appearance of the ad (cute, eyesore). Industry experts also addressed the look of the ad to a lesser extent using descriptor s such as classic, tasteful cordial, copy heavy, and vist1al. This dimen s ion reflects the instrument of advertising, which Sandage and Leckenby (1980) differentiated from the institution of advertising. While institution refers to the purpose and effects of advertisi11g, i11strument refers to advertising's executional properties. Table 3-6 lists these dimensions and their subdimensions and corresponding descriptors. Several descriptors were selected from each of these dimensions to repr esent the dimension in the next stage of research. For the annoyance dimension the descriptors of annoying, intrusive, overbearing, and disruptive were selected. To represent the entertainment dimension, the descriptors entertaining, amusing, and eye-catching were selected. Information, useful and beneficial were chosen to represent the information dimension. Innovative different, and sophisticated were selected for the novelty dimension. Finally, attractive and elaborate (antonym of plain) were chosen to represent the composition dimension Because the focus of future studies will be collecting data on subjective dimensions, the interactive dimension was disregarded as it tends to be more objective.

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81 Table 3-6. Summary of Dime11sions and Corresponding Descriptors Dimensions Subdimensions Desc:iptors Annoyance General Annoying, bothersome, frustrating -----------------------Disruption of Interrupts, abrupt, disruptive, distracting di v ert s expenence (Intrusion) Clutter Activity Ubiquity Ability to control Time factor Entertainment General Activity Eye-catching Graphics Information G e neral Relevant Novelty General attention intrusive, interferes distorts content gets in the way, takes over page in your face / out of the way interferes with background Percentage of screen occupied, position of ad, si z e of ad clutter obtru s ive, takes up spac e, overbearing, pervasive Fla s hing, animated, flashy blinking, movement hyperactive Ubiquitous Control, forced, voluntary choice forced exposure, wanted/unwanted, requires action to remove Inconvenient, time-consuming Entertaining enjoyable exciting, fun appealing, cool, neat, amusing Flashing, animated, flashy blinking, movem e nt, hyperactive Catches attention holds attention, eye-catching intere s ting, noticeable obtrusive, contrasts with background Cool graphics, good pictures, images of product, interesting graphic Infor1native info11national value, cont e nt con1pelling message, space in ad for content Audience-driven, relevant to content targeted beneficial useful offerings Cutting-edge, different sophisticated innovative clever, creative and inventive Interactivity General Interactivity involvement Composition Colors Bright colors colorful, bold ---------------------Size Big, small Simplicity Simple plain T e xt Easy to read, too many words Overall appearance Cute, eyesore

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82 Discussion The depth interviews identified critical perceptual dimensions of online advertising fo1mats and informed the development of items to be used to measure each dimension. The interviews also highlighted six online advertising formats worthy of future study. Online Advertising Forrnats The six forrnats selected were banners, pop-up ads, skyscrapers, large rectangles, floating ads, and interstitials. These formats have often been included in research studies either in combination, in isolation, or in comparison to a traditional medium, such as television. The Dynamic Logic (2001 a) Ad Unit Effectiveness Study measured the effectiveness of banners, skyscrapers, and large rectangles. The Advertising Reaction Study also by Dynamic Logic (2001b) measured attitudes toward banners, pop-up ads, skyscrapers, large rectangles, and interstitials. Attitudes toward pop-ups and banners have been compared (Statistical Research, 2001 ). Other studies have examined the effectiveness of banner ads (Briggs & Hollis, 1997; Cho, 1999; Gilliam, 2000; Morgan Stanley, 200 I), large rectangles (Lefton, 2001 ), or Superstitials (Harris Interactive, 2001). Two of these formats-the skyscraper and the large rectangle !--are part of the IAB's recommended universal ad package, which further validates their importance (Elkin, 2002d). Furtherrr1ore, Nielsen/ /NetRatinp:s reported that banners, rectangles, and skyscrapers represented the highest percentages of online advertising impressions (Martin & Ryan, 2003). While floating ads have yet to be included in an attitude study, this forrnat is expected to attract the attention of consumers and researchers as it becomes more

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83 prominent and widely used. A Nielsen//NetRatings study found that almost three times as many advertisers in the fourth quarter of 2002 than in the same quarter of 2001 used the format (Buchwalter & Martin, 2003). In conclusion, these six formats are appropriate for future studies based on their dominance in the depth interviews and conflfll1ation provided by inclusion in other research studies, recognition by the IAB, or data indicating the prevalence or predicted growth of the use of the format Perceptual Dimensions The five perceptual dimensions identified in this qualitative study were annoyance, entertainment, information, novelty, and composition. Four of these five dimensions have been identified in previous Uses and Gratifications studies (Plummer, 1971; Schlinger, 1979) In these studies, entertainment, familiarity ( opposite of novelty), information, and irritation (similar to annoyance) were recognized as categories 0f viewer rewards of television. These dimensions are consistent with those in studies of attitudes toward advertising. Annoyance of advertising has been linked to attitudes toward advertising (Aaker & Bruzzone, 1985; James & Kover, 1992) The study of entertainment of advertising can be traced back to Bauer and Greyser's 1968 study, which inspired the inclusion of this variable in many later studies, several of which found a relationship between entertainment and advertising attitudes (Alwitt & Prabhaker, 1992, Pollay & Mittal, 1993; Schlosser, Shavitt, & Kanfer, 1999; Shavitt, Lowrey, & Haefner, 1999). Similarly, a number of studies have confirmed a relationship between the informational valt1e of advertising and advertising attitudes (Mittal, 1994; Pollay & Mittal, 1993; Schlosser, Shavitt, & Kanfer, 1999; Shavitt, Lowrey, & Haefner, 1999). The composition

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84 dimension reflects the instrument of advertising and its executional properties, which Sandage and Leckenby (1980) differentiated from the institution of advertising. Comparing the results of the interview with online advertising experts and experienced Web surfers, the dimension that was mentioned most by both groups was annoyance. In addition, the entertainment and novelty dimensions received a high percentage of mentions by the Web surfers, while the information dimension was noted by a high percentage of advertising experts. The composition of the ad was noted by a moderate number of Web surfers and the information aspect received few mentions by this group. For advertising experts, the novelty of the ad received a moderate number of mentions, while the entertainment and composition dimensions garnered a few mentions. Annoyance of online advertising is certainly a concern for advertisers as they try to frnd the balance between attention and annoyance. Because the online environment presents the possibility of a sales conversion, communicating the necessary information is another concern of advertisers. It is not surprising that these two dimensions emerged as those with the most mentions by online advertising experts. The novelty dimension emerged during these interviews as well, which may reflect the opportunity advertisers have to try more daring advertising concepts to attract the attention of the user (Mediapost, 2001) and the technology that is now available to create more innovative formats of advertising. Finally, the entertainment and composition dimensions were not as likely to be mentioned by advertising experts, possibly because the participants were more likely to discuss the by-products of entertaining or well-composed ads, such as interactivity

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85 In the wake of the XIO pop-up heyday, Web surfers have reason to be annoyed by online advertising. Web surfers may be somewhat appeased if online advertising is at least entertaining and novel, as suggested by the frequency of mentions for these two dimensions The information dimension may have received few mentions because participants in the interview were not in a situation where they ,vere seeking information from the stimulus ads. As a result, this dimension may not have been given enough consideration by participants. Because participants were asked to look at ads and respond to them, the composition dimension emerged through these interactions. The fifteen descriptors selected to correspond with these dimensions included annoying, disruptive, intrusive, overbearing, entertaining, amusing, eye-catching, informative useful, beneficial, innovative, different, sophisticated, attractive, and elaborate. Overall, these descriptors are similar to those used in other studies of attitudes toward advertising (Cho, 1999; Ducoffe, 1995; Mittal, 1994), in reaction profile studies (Aaker & Bruzzone, 1981; Aaker & Stayman, 1990; Biel & Bridgwater, 1990), and in Uses and Gratifications studies (Eighmey & McCord, 1998; Plummer, 1971; Schlinger, 1979). The next chapter reviews Study 2, which used these six online advertising formats as stimuli to examine the relationships between the perceptual dimensions and attitude toward the online ad format. This study also examined the relationship between attitude toward the format and A a d

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CHAPTER4 STUDY 2 This chapter describes the findings of a study that tested a portion of the modified attitude-toward-tl1e-ad model to determine the influence of attitude toward the onlin e ad format on A ad and to understand the factors that influence attitude toward the online ad format This stud y involved six replicates to test the relationships in the model with each replicate representing a unique online advertising format A student sample was used to test the proposed theoretical relationships among variables. Purpose Using the online ad formats identified in Study 1, Study 2 tested the theoretical proposition that attitude toward online ad format is a significant predictor of A ad This relationship has not been tested previously. This study also tested the relationship betwee11 attitude toward online advertising (Ao a) and Aad Once again, this specific relationship has yet to be tested across multiple forrnats in an online context. While Bauer and Greyser (1968) noted a relationship between attitude toward advertising and the proportion of ads classified as favorable or unfavorable, MacKenzie and Lut z (1989) did not find a relationship between the two constructs Cho (1999) found that respondents with more favorable attitudes toward Web advertising overall had a more favorable attitude toward a specific banner ad. Examining the influence ot these two variables (Arormat and Aoa) on attitude toward the ad also serves to make the distinction between the institution and instrument of advertising as defined by Sandage and Leckenby (1980). 86

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87 The current study also tested the relationsllip between the proposed drivers of attitude toward the online advertising format Following in the tradition of the Aa a model (MacKenzie & Lut z, 1989), whereby attitude toward advertising is determined by advertising perceptions, the primary determinant of attitude toward online ad format was hypothesized to be ad format perceptions, such as the perceived information and entertainment provided by the ad format. These perceptions were derived in Study 1 Previous studies that found a positive correlation between attitudes toward advertising and the beliefs that form those attitudes (Aaker & Stayman 1990; Alwitt & Prabhaker, 1992 1994; Biel & Bridgwater 1990; Cho, 1999; Schlosser, Shavitt, & Kanfer 1999; Shavitt Lowrey & Haefner, 1998) make it possible to hypothesize that ad format perceptions will be positively correlated with attitude toward the online ad format However as Mittal ( 1994) uncovered this relationship is not always consistent. Furthermore this relationship with respect to online advertising forrnats has not been documented in the literature. Until this relationship is established, measuring ad forrnats on just a scale of perceptual dimensions provides little information abot1t the extent to which the ad is liked or disliked. In addition measuring only the degree to which an ad format is liked or disliked provides no information about how this attitude is precipitated. The researcher can only hypothesize about this attitude on the basis of objective ad format features if perceptions of subjective ad for1nat features are not measured. Objective ad features for online advertising include color, animation, and interactivity, wl1ile subjective ad features are compiled into adjective checklists, which include such adjectives as exciting, interesting, and boring (Rodgers & Thorson, 2000)

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88 Attitude toward online advertising, attitude toward the Internet, and attitude toward the Web site in which the ad appears were also examined for correlations with attitude toward the online ad format. Bruner and Kumar (2000) examined attitude toward the Web site and found as this attitude becomes more favorable, attitude toward the ad attitude toward the brand and purchase intention are improved as well. In the current study, attitude toward the Web site was hypothesized to directly influence attitude toward the format and indirectly influence attitude toward the ad. Attitude toward online advertising and attitude toward the Internet were included to encompass two general attitudes that may affect the more specific attitude toward the format Frequency of Web use and online shopping habits were considered as moderators. The inclusion of these moderators was suggested by studies such as that by Korgaonkar Karson, and Akaah (1997) that found a relationship between direct mail spending amounts and beliefs toward direct mail advertising Clicktbrough behavior was also included as a moderator as studies have shown a relationship between clickthrough and attitude (Brill, 1999; Cho, 1999) Familiarity with the format was also considered. Figure 4-1 illustrates the hypothesized relationships among variables. While this model is based on the A ad model developed by MacKenzie and Lutz (1989), several variables have been omitted, including ad credibility, attitude toward the advertiser, and mood. These omissions served to narrow the focus of this study on a smaller set of variables. Future studies can test tl1e entire model or other segments of the model. The focus here is testing the role of attitude toward online ad format on attitude toward the ad. Online ad format perceptions based on the ad perceptions in the MacKenzie and Lutz model (1989), are included as a predictor of attitude toward online

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89 ad format. Furthermore the role of attitude toward online advertising will be examined as well as attitude toward the Internet and attitude toward the Web site Attitude toward I nternet Online Ad Format Perceptions Attitude towar d 1 4 1--0nl i ne Ad Format Attitude toward Web Site Attitude toward Onl i ne Advertising Figure 4-1 Modified Attitude-Toward-the-Ad Model for Testing Relationship s in the Online Context Hypotheses The model suggests the following hypotheses to be tested in this study: 1. Attitude toward online advertising format is directly related to Aad 2. Attitude toward online advertising is directly related to A a d 3. Attitude toward online advertising is directly related to attitude toward a specific online advertising format. 4. Attitude toward the Internet is directly related to attitude toward a specific online adverti s ing format 5. Attitude toward a Web s ite is directly related to attitude toward a specific online advertising format hosted on that site.

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90 6. Online ad format perceptions are directly related to attitude toward that advertising fonnat. Method Sainple The sample used to test the proposed model consisted of undergraduate business students at a large southern university While students were not required to participate, those who did received extra credit toward their final course grade. Although student samples have certain litr'.itations, they tend to be a more homogeneous gioup than a sample from the general population and thus, are ideal samples for testing theoretical predictions about the relationships among variables (Calder, Phillips, & Tybout, 1981), which was the primary purpose of this study. Procedure Through an e-mail invitation, respondents received hypertext links to two versions of an online survey. The length of the survey necessitated the development of two versions with each including an evaluation of three ad formats. Each survey contained links to one example of each of three online advertising formats. An attempt was made to make the surveys as balanced as possible in terms of the characteristics of the formats. One survey measured attitudes toward banner acis, pop-ups, and skyscrapers, and the other measured attitudes toward large rectangles, interstitials, and floating ads. After each ad presentation, the participants completed the part of the online survey that corresponded to that advertising format Respondents were randomly assigned to one of the two surveys by the last digit of their Social Security number (i.e., even or odd). Respondents had the option to complete the other survey for additional extra credit

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91 Stimulus Ads The stimulus ads were drawn from various collections, galleries, and portfolios of online advertising to ensure that every time the site was accessed, the same ad was presented The products represented in the ads were deemed to be relevant to a student population. In addition, to minimize any strong feelings toward the product advertised or the advertiser itself, the selected ads did not represent products or companies that may elicit strong negative attitudes or companies that have faced crises or controversies. The products or companies featured in the online advertisements included Dunkin' Donuts, Saturn, Handspring (handheld computer), Travelocity, Best Buy, and Nikon. Measures The survey utilized different scales to measure the various attitudinal dimensions to avoid the problem of shared method variance, which can artificially inflate the actual relationship between two constructs. Many of the attitude measures were adapted from other studies. Others were created because some of the constructs do not have established measures. The reliability of all measures was evaluated on a post-hoc basis. The validity is established by the general body of knowledge that Likert and semantic differential scales are acceptable measures of beliefs and attitudes and by the nomological validity of whether the measure behaves as theoretically expected in relation to other constructs. The endpoints used in these measures are representative of those used in studies that examine global attitudes (Mittal, 1994; Muehling, 1987) and are consistent with Churchill's (1979) suggestion of selecting very general semantic differential pairs to develop measures of marketing constructs While 7-point scales have been widely ustd in attitude research, this study employed 5-point scales for the attitude measures. Brackett and Carr (2001) described

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92 how a pretest of their advertising attitude survey with a student population revealed that students rarel y selected the extremes on the 7-point scales. The 5-point scale is expected to produce sufficient variation for multiple-item scales Attitude measures This study used a four-item, 5-point semantic differential scale to measure attitudes toward the online advertising format. These items included: liked by me / disliked by me, one of the best fo1mats / one of the worst formats, an excellent ad format / a poor ad format, and I love it / I hate it. An index for attitude toward online ad format scores was created by averaging the responses to the four items. Attitude toward the ad was measured usin ~ a three-item, 5-point semantic differential scale with the endpoints of good/bad, pleasant/unpleasant, and favorable / unfavorable. Coefficient alpha for this scale is approximately .89 (MacKenzie & Lutz, 1989). Again, an index for attitude toward the ad scores was obtained by averaging the responses to the three items. This study used a three-item, 5-point scale to measure attitudes toward online advertising. This scale has been previously applied to the measurement of attitudes toward Internet advertising (Previte, 1998) and a similar scale was used in an earlier study of attitudes toward advertising (Pollay & Mittal, 1993). The scale included the following items: Advertising on the Web is a good thing; My opinion of advertising 011 the Web is unfavorable; and Overall, do you likt; or dislike the advertising you see on the Web? Responses to the three items were averaged to create an index. Respondents used a Likert scale to respond to the first two items and a scale ranging from strongly like to strongly dislike to respond to the third item

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93 The measurement of attitude toward the Web site used a three-item 5-point Likert scale comprised of the following items: I like this Web site; It is a good Web site; and It is a nice Web site. These statements were adapted by Bruner and Kumar (2000) from a study by Chattopadhyay and Basu ( 1990) who calculated a coefficient alpha of .97 for this scale Responses to the items were averaged to create an index. The measurement of attitt1de toward the Internet utilized a three-item 5-point Likert scale. Respondents were asked to indicate tl1eir agreement to the following statements: I feel comfortable surfing the Internet; Surfing the Internet is a good way to spend my time; and I am satisfied with the sites I visit on the Internet. These statements were adapted from Chen and Wells' (1999) study of attitude toward the (Web) site. Again, responses to the three items were averaged to create an index. The questionnaire is provided in Appendix C. Ad format perceptions The data from Study 1 were used to develop dimensions for measuring ad for1nat perceptions. Through conceptual factor analysis, the following dimensions of attitude toward online advertising format were identified: irritation, entertainment, informativeness novelty, interactivity and composition. From the dimensions derived through the qualitative study, only subjective descriptors were measured by the survey. For example, the survey was not used to assess whether an ad is aninlated or requires action to close. Therefore, descriptors were selected to represent five of the six dimensions identified ( excluding interactivity) The 15 descriptors selected from the five dimensions to measure ad format perceptions included the following: annoying, intrusive, disruptive, overbearing, entertaining, amusing, eye-catching, inforrnative, useful, beneficial, innovative different,

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94 sophisticated, attiactive, and elaborate. These descriptors were all mentioned by participants in describing online advertisements. Behavioral measures. Several behavioral measures with respect to online advertising response were inclt1ded in this survey. These questions gathered data on whether respondents had ever clicked through on each of the ad formats, how often in the past six months had they clicked through on that ad format, and whether exposure to a certain format had ever prompted them to later visit the Web site. Familiarity with the format was also measured. The survey also asked if respondents had ever made an online purchase and how many online purchases had been made in the past six months. Demographics and Web use. Because the sample was relatively homogeneous, only basic demographic information was collected. Respondents were asked to report their gender, age, and employment status. Other questions collected data on respondents' primary Internet connection, the year they started using the Internet on a regular basis, and the number of hours spent surfmg the Web each week. Results Sample Description Data were collected between July 12, 2002, and August 24, 2002, for two versions of the survey with each version containing three unique online ad formats. A total of 221 usable surveys were completed. Assignment of the survey version based on the last digit of the respondent s Social Security number resulted in 104 completed surveys of the first version and 117 completed surveys of the second version. After completing the survey assigned according to Social Security number, respondents had the option to complete the other version of the survey. Sixty-nine respondents completed both versions and 83 completed only one version for a total of 152 unique respondents.

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95 As Table 4-1 illustrates, the sample was almost evenly divided in tem1s of gender. Because the sample was drawn from college students enrolled in introductory business courses, it is not surprising that almost half of the respondents (42 4%) were 20 years old or younger. Over one third of respondents were 21 or 22, almost 12% were 23-28, and the remaining 10 % were 29 or older. The mean age was slightly more than 23 years. Over half of the respondents were employed part-time, while one fourth were not employed. Slightly fewer than 20% were employed full-time and slightly more than 5% described themselves as self-employed or ''other Table 4-1. Demographic Characteristics of Respondents Characteristic N % Gender Male Female Age (M = 23.3) 20 or younger 21-22 23-28 29 or older Employment Part-time Not employed Full-time Self-employed Other 74 73 62 53 17 12 75 37 27 2 6 50.3 49.7 42.4 36.3 11. 7 9.8 51.0 25 2 18.4 1.4 4 1 Note. Sample sizes differ as a rest1lt of omitted responses.

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96 Most respondents used a 56K modem (34.7%), a cable modem (28.6%), or DSL (19.7%) as their primary Internet connection. The highest percentage of respondents started using the Internet on a regular basis in 1998 or 1999 (3 9. 7% ), followed by 1996 or 1997 (27.4%). Table 4-2 presents these data. In addition, respondents estimated that they spend an average of almost 10 hours per week surfing the Internet (M = 9.55, SD= 9.43). Respondents' estimated online times ranged from 1 to 50 hours per week. Table 4-2. Internet Usage Characteristics of Respondents Characteristic N % Primary Internet connection 56Kmodem Cable modem DSL Tl or better Do not know 28.8K modem Other Year sta1ted using Internet 1991-1993 1994-1995 1996-1997 1998-1999 2000-2002 51 42 29 11 6 5 3 6 26 40 58 16 34.7 28.6 19.7 7.5 4.0 3.4 2 0 4.1 17.8 27.4 39 7 11.0 Note. Sample sizes differ as a result of omitted responses. With respect to online purchase behavior, almost 94% of respondents have made an online purchase and almost 40% have made one or two online purchases in the last six

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97 months. Almost 45% have made three or more online purchases in the past six months. Table 4-3 presents the responses to these questions Table 4-3 Online Purchase Behaviors of Respondents Behavior N Made online purchase Yes No Number of online purchases in past 6 montl1s None 1-2 3-4 5-6 7 or more 138 9 24 57 35 16 15 Note. Sample sizes differ as a result of omitted responses. Overall Data Structure % 93 9 6.1 16 3 38 8 23.8 10.9 10.2 Version 1 of the survey exposed respondents to banner ads, pop-ups, and skyscrapers Version 2 exposed respondents to large rectangle ads floating ads and interstitials. Two attitudinal mea sures attitude toward the Internet and attitude toward online advertising appeared once in each version. In addition, online purchase questions were asked once in each version Three attitudinal measures-attitude toward the ad, attitude toward the online ad format and attitude toward the site : were included for each of the three ad formats in each version. Respondents were also asked to respond to the ad perception items and the familiarity and previous clickthrough behavior questions for each of the formats.

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98 Verification of Measures The items comprising the common attitude measures (i.e., attitude toward the Internet and attitude toward online advertising) were factor analyzed to verify that all items loaded on the same factor. Reliability analysis was also conducted to dete11nine whether deleting any of the items would improve the Cronbach's alpha. The analysis was conducted for each version of the st1rvey. All items loaded on the same factor for each common attitude measure for each version of the survey For attitude toward online advertising, reliability analysis revealed that Cronbach's alpha would not be improved with the deletion of any item from each version of the survey. For attitude toward the Internet, no deletions in Version I would in1prove Cronbach's alpha yet the deletion of the item ''I feel confident in my ability to surf the Web'' would improve alpha slightly (up to .5972 from .S903) for Version 2 In combinjng the data for each version the items comprising the attitude toward the Internet measure and the attitude toward online advertising measures all loaded on a single factor. Deleting any item from either scale would not improve Cronbach's alpha (.60 for attitude toward the Internet and .84 for attitude toward online advertising). Table 4-4 illustrates the Cronbach's alphas and percentage of variance explained by the items for each version of the survey and then for the two versions combined. Whlle the items measuring attitude toward online advertising provided acceptable internal consistency according to Nunnally's (1978) suggested minimum alpha of .70, the items measuring attitude toward the Internet fell below this minimum acceptable alpha.

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99 Table 4-4. Verification of Common Attitude Measures Attitude Attitl.1de toward Internet a % of variance Attitude toward online advertising a % of variance Version 1 rz = 104 .61 57.3 .82 74.5 Version 2 n = 117 .59 55.7 .86 78.4 Combined N = 221 .60 56.4 .84 76.6 An examination of the items used in these two scales makes it possible to see how one scale can exhibit n1ore internal consistency than the other. The attitude toward the Internet scale included items measuring whether the user is comfortable surfing the Web whether surfing is a good way to spend time, and whether the user is satisfied with sites visited on the Web. While some corre l ation is to be expected, these items could move in different directions. For example, a user may feel comfortable using the Web but not consider surfing a good way to spend time Attitude toward online advertising is more narrowly defined in measuring agreement to statements about whether advertising is a good thing, whether opinion is favorable, and whether online advertising is liked. Test-Retest Reliability The subsample of 69 respondents who con1pleted botl1 versions of the survey was used to check test-retest reliability of attitude to\.vard the Internet and attitude toward online advertising The scores for each three-item scale were averaged to form an index for each measure.

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100 The test-retest reliability coefficient for attitude toward the Internet was 82 and a paired-samples t test did not reveal a significant difference between the two means (t = .926, df = 68 p = .358). While the Cronbach's alpha for this measure is below the range of acceptability, its test-retest reliability coefficient demonstrates its reliability. Similarly the test-retest reliability coefficient for attitude toward online advertisin g wa s 79 and a paired-samples t test revealed did not reveal a significant difference between the two means (t = 327 df = 68 p = .744). Table 4-5 presents the mean scores for each of these indices for each versio11 of the survey. Table 4-5 Mean Ratings for Attitude Indices for Respondents who Completed Both Versions (n = 69) Attitude Attitude toward Internet M SD Attitude toward online advertising M SD 1 3.96 .52 3.12 .82 Version 2 3.92 .52 3.14 .76 Note. A 5-point Likert scale was used to indicate agreement with state1nents. Statements were coded so tl1at 5 represented s trongl y agr e e with favorable statements and s trongl y disagr ee with unfavorable statements Factor Analysis of Perceptual Items and Attitude Measures Ratings of the 15 perceptual items for all six online ad formats were subjected to a principal components factor analysis with varimax rotation. A scree plot supported a possible three-factor solution with a bend in the curve at the third factor. The first 3

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101 factors accounted for over 68% of the total variance, while the remaining 12 factors explained no more than 5 % of the variance each The three major factors are : Factor 1: Entertainment This factor is described by the following items : innovative, different entertaining sophisticated, amusing elaborate, eye-catching and attractive with an eigenvalue of 4 36 and 29 /o of the variance. Factor 2: Annoyance The annoyance factor is described by disruptive, intrusi v e overbearing and annoying with an eigenvalue of 3.80 and 25 3 % of the variance Factor 3 : Information This factor was defined by the following items : informative useful and beneficial with an eigenvalue of 2.10 and 14% of the variance Table 4-6 shows the loadings of the factors generated through principal component extraction and varin1ax rotation. Mean scores standard deviations, and Cronbach s alphas were calculated for each factor Cronbach's alphas remain high for the three factors. The data are presented in Table 4-7 Factor analyses were conducted for each format to confirm that these three factor s held up across formats. For all formats, the four perceptions comprising the annoyance factor fell onto the same factor For large rectangles and pop-ups (with the exception of one item), the perceptions also factored identically to the aggregate data set. The three perceptio11s comprising the information factor fell onto the same factor for all formats except one (floating ads) yet this factor often included various other perceptions. These factors were deemed to be acceptable across forrnats. Tables presenting these data by format are included in Appendix E.

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102 Table 4-6. Summary of Factor Loadings for the Rotated Three-Factor Solution for Perceptual Items Perception Innovative Different Entertaining Sophisticated Amusing Elaborate Eye-catching Attractive Disruptive Intrusive Overbearing Annoyance Informative Usefi1l Beneficial Factor I: Entertainment .81 .75 .75 .72 .71 .70 .65 .64 -.04 .06 -.03 -.12 .08 .29 .35 Factor Loadings Factor II: Annoyance -.01 -.01 .27 -.07 .3 4 .24 .18 -.37 .89 .87 .86 .85 -.23 .37 45 Note. Bold it ems indicate items loading on each factor. Factor ill: Information .07 -.06 14 .22 11 17 .20 .32 -.21 -.14 .23 -.25 .84 .74 .65

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103 Table 4-7. Means Standard Deviations and Alphas for Three-Factor Solution Factor M SD a N Entertainment 3.24 76 .88 5 7 5 Annoyance 3.18 1.12 .92 575 Information 3 15 .88 83 575 The item s comprising the three attitude measures of attitude toward the ad attitud e toward online ad format, and attitude toward the site for all six online ad forrnats were also subjected to a principal components factor analysis The items for each attitude measure converged on one factor for each forn1at Mean scores for each of the attitude and perceptual factor indices were also calculated for each format In addition reliability analysis was conducted on the items comprising each index and factor These tables ar e also presented in Appendix E and a summary of the means, standard deviations and coefficient alphas is provided for the attitude measures in Table 4-8 and the perceptual factors in Table 4-9 1 The items measuring the attitudes and perceptual factors for each format provided acceptable internal consistency according to Nunnally s (1978) suggested minimum alpha of .70, as the lowest coefficient alpha is .78. 1 Appendi x E p r e s ent s m ea n s, s tandard d ev iations and c o e ffi c ient alpha s for ea c h unique per ce ptual fa ct or produ ce d throu g h fa ct or analy s i s for eac h format Table 4 9 pre s ent s th e data a s c al c ulat e d u s in g th e p e r c eptual fa c t o r s det e rmin e d b y the a g gr eg at e data s et

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104 Table 4-8. Mean Scores for Attitt1de Indices (with Coefficient Alpha) for Each Online Ad Format Attitude A ad M SD a A rormat M SD a A site M SD a Bann e r (n = 102) 3.42 .8 8 .8 6 3 25 1.00 .92 3 43 .72 .91 Pop-up (n = 102) 2.86 1 19 94 1 85 1 07 .95 3.44 .89 95 Online Ad Format Skyscraper (n = 97) 4.05 87 94 3.83 .82 92 3 62 .72 90 Large Rec (n = 117) 3.90 .83 89 3.36 .92 .92 3.59 .72 93 Floating (n = 76) 3.40 1.35 .96 3.07 1.41 .97 3.88 .78 .94 Interstitial (n = 8 1) 3.53 1.19 95 3.29 1 06 95 3 65 .72 .91

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105 Table 4-9. Mean Scores for Perceptual Factor Indices (with Coefficient Alpha) for Each Online Ad Format Perceptual Factor Entertain M SD a Annoy M SD a Inform M SD a Banner (n = 102) 2.87 59 .79 2.95 .95 85 3.11 89 .82 Pop-up (n = 102) 2.94 .81 .89 4.19 .90 .84 2.58 .85 .81 Online Ad Format Skyscraper (1'z = 97) 3.20 .60 .83 2.23 .70 .88 3.59 .72 .85 Large Rec (n = 117) 3.19 .68 .87 2.96 .96 .90 3.47 .72 .81 Note. 1 = strongl y disagree. 5 = strongl y agree. Floating (n = 76) 4.01 .56 .78 3 69 1.00 .94 2.87 .88 .79 Interstitial (n = 81) 3.51 72 .89 3.18 1.09 .95 3.17 .79 .78 ANOVA was used to deterrnine whether significant differences existed between the attitude and perceptual factor indices based on formats. As Table 4-10 illustrates, significant differences were found among online advertising forn1ats for the three attitt1de indices and the three perceptual factors.

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106 Table 4-10. One-Way Analyses of Variance for the Effects of Format on Attitude and Perceptual Factor Indices Variable df SS MS F Attitude toward the ad Between groups Within gro up s Attitude toward online ad format Between groups Within groups Attitude toward Web Site Between groups Within groups Entertainment factor Between groups Within groups Annoyance factor Between groups Within groups Information factor Between groups Within groups *p < .05. **p < .01. 5 569 5 569 5 570 5 569 5 569 5 569 91.50 622.63 223.49 619 88 11 .80 329.81 74.97 253.21 223.75 496.55 70 29 369.72 18.30 1.09 16. 73** 44.70 41 03** 1.09 2.36 .58 4.08** 14 .99 33.69** .45 44.75 .87 51.28** 14. 06 21 64 * .65 Po st -hoc comparisons using the Least Significant Difference (LS D) method revealed which means were significant ly higher or lower than others. The attitude toward the ad and attitude toward the ad format for pop-ups were significantly lower than all other formats. Skyscraper ads were significantly high er than every other fo11nat in terms

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107 of attitude toward the online ad format. The ratings for the Web site hosting the floating ad were significantly higher than for all other Web sites, except the one hosting the interstitial ad Floatit1g ads were rated significantly higher than all other formats on the entertainment factor, while pop-up ads received significantly higher evaluations on the annoyance factor. Evaluation of skyscraper and large rectangle ads on the info1r11ati o n factor were significantly higher than for many other ad formats. Table 4-11 summari z es these difference s. Table 4-11. Post-Hoc Comparisons of Attitude and Perceptual Factor Means Across Forrnat Using LSD Attitude A a ct A ro rm at A site Entertain Annoy Infom1 Banner (a) (n = 102) 3 43 2.87 Pop-up (b) (n = 102) 2 86 1.85 3.44 2 94 4 1 9 acdef 2.58 Online Ad Format Sky s craper (c) (n = 97) 4.05 bef 3 83 abdef 3.62 3.2Qa b 2.23 3 59 abef Large Rec (d) (n = 117) 3 90 abef 3.59 3 47 abe f Floating (e) (n = 76) 3 88 a bcd 4 .0l a b c d f 3 69 acdf Interstitial (f) (n = 81 ) 3 65 3 5 l a bed 3 18 c 3. l 7 be Note. Superscripts indicate that the mean is sign:ficantly higher than the format indicated by the s uperscript (p < 05) Correlations Among Variables for Each Format For each format correlation s among model variables were examined For banner ads, although the correlation betw e en attitude toward the ad and attitude toward the fo1n1at is significant, it is fairly low at r = 39. The attitude toward the format has a positive correlation with the rnformation factor (r = .54) and the entertainment factor ( r =

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108 .42) and a negative correlation with the annoyance factor (r = -.56) Table 4-12 shows these correlations for banner ads. Table 4-12. Intercorrelations for Attitude and Perceptual Factor Indices for Banner Ads Measure 1. Attitude toward online ad format 2 Attitude 1 -toward online 26** advertising 3. Attitude toward ad 4. Attitude toward site 5 Attitude toward WWW 6 Entertainment factor .39** .16 -.03 .42** 2 3 4 5 6 7 .19 -.29** .37** --.07 -.06 -.21 -.26** .45** .42** 10 -7. Annoyance factor -.56** -.29** 22* -.22* .11 -.14 -8 Information factor *p < .05 **p < .01 .54** .33** 45** .36** .12 .53** 44** 8 -The correlation between attitude toward online advertising format and attitude toward the ad was significant for pop up ads as well and at r = .56, was higher than the correlation for banner ads Attitude toward the format was also strongly correlated with the three factors of entertainment (r = .59), annoyance (r = .64), and inforn1ation (r = .61). Table 4 13 illustrates these relationships

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109 Table 4-13. Intercorrelations for Attitude and Perceptual Factor Indices for PopU p Ad s Measure 1 2 3 4 5 6 7 8 1. Attitude toward online ad format 2 Attitude toward onlin e advertising 3. Attitude toward ad 4. Attitude toward site 5. Attitude toward WWW 6 Entertainment factor 7. Annoyance factor 8. Infor1nation factor *p < .05 **p < .01. -. 18 -. 56** 09 -.20* .001 33** -. 12 .0 7 -.19 -.06 59** 08 62** .31 ** -.64** 19 38** .06 .61 ** .30** .46** .20* -. 15 .20* 37** --.06 .66** -.46** -Attitude toward the ad and attitude toward the format also exhibited a strong correlation for skyscraper ads ( r = .68). Again, the three factors of entertainment (r =. 58 ), annoyance (r = 56), and information (r = .57) were also highly correlated with attitude toward the format. Table 4-14 shows the s e relationships

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110 Table 4-14. Intercorrelations for Attitude and Perceptual Factor Indices for Skyscraper Ads Measure 1 Attitude toward online ad format 2 Attitude 1 2 3 4 5 6 7 toward online 28** advertising 3. Attitude toward ad 4. Attitude toward site 5 Attitude toward WWW 6 Entertainment factor 7. Annoyance factor 8. Information factor *p < 05. **p < 01. .68** .20* -.38** .20 .45** -.17 -.07 19 -.19 -.58** .18 .55** 34** -.01 -. 56** 30** -.35** -.28** .17 -.20 .57** .34** 54** 53** -.09 .65** -.44** 8 The correlation between attitude toward online advertising format and attitude toward the ad was significant for large rectai1gle ads and exhibited a correlation coefficient ofr = .75. Attitude toward the format was also strongly correlated with the three factors of entertain1nent (r =. 66), annoyance (r = -.71), and information (r = 57). Table 4-15 illustrates these relationships

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1 1 1 Table 4-15. Intercorrelations for Attitude and Perceptual Factor Indices for Large Rectangle Ads Measure 1 Attitude toward onlin e ad format 2. Attitude toward online advertising 3. Attitude toward ad 4. Attitude toward site 5. Attitude toward WWW 6. Entertainment factor 7. Annoyance factor 8. Inf or1natio11 factor *p < .05. **p < .01. 1 2 -. 20* -.7 5** .2 5** .41 ** 11 13 .08 .66 ** 13 -.71** 30** .57** .33** 3 4 5 6 7 .43** -.11 .30** 55** .29** 21 --.56** -.22* -.05 -.49** -.56** 30** .0 9 56** -.53** 8 For floatin g ads, correlation between attitude toward the ad and attitude toward the fonnat is significant and high (r = .81 ). The attitude toward the fonnat has a strong negative correlation with the annoyance factor (r = -.77) and lower but still significant, po s itive correlations with the entertainment (r = .57) and information (r =. 63) factors Table 4-16 illustrates the correlation coefficient~ among tl1e variables for floating ads.

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112 Table 4-16. Intercorrelations for Attitude and Perceptual Factor Indices for Floating Ads Measur e 1. Attitude toward online ad format 2 Attitude toward online advertising 3. Attitude toward ad 4 Attitude toward site 5. Attitude toward WWW 6. Entertainment factor 7 Annoyance factor 8. Information factor *p < .05. **p < .01. 1 2 3 4 5 6 7 8 -.23* -. 81** .25* -.40** .18 37** --.13 08 -.10 -.03 -. 57** .05 .57** .30** .004 77** -.21 -.64** -.31 ** 10 -.35** -.63** .22 .64** .40** -.08 .58** -.57** The strongest correlation between attitude toward the ad and attitude toward the format was found for interstitial ads (r = 86). The attitude toward the format has a positive correlation with the information (r = 75) and entertainment (r =. 61) factors and a negative correlation with the annoyance factor (r = -. 72). Table 4-17 shows these correlations for interstitial ads.

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113 Table 4-17. Intercorrelations for Attitude and Perceptual Factor Indices for Interstitial Ads Measure 1. Attitude toward online ad format 2. Attitude 1 -2 3 4 toward online .33** -advertising 3. Attitude toward ad 4. Attitude toward site 5. Attitude toward WWW 6. Entertainment factor 7. Annoyance factor 8 Information factor *p < .05. **p < 01. .86** .25* .33** .12 .30** 22 .08 -.22* -.004 .61 ** 13 .53** 17 -. 72** -.17 -.69** 32** 75** .22 64** 21 5 6 7 8 --.16 -. 17 18 -. 3 7** .61 ** -.48** -While the attitude toward some formats demonstrates a stronger correlation with attitude toward the ad than others, the range of correlation coefficients from r = .39 for banner ads tor = .86 for interstitials suggests that respondents were able to discern a difference between these two constructs for some for rnats. The significant correlations among variables for all formats suggest that the data are appropriate for model testing. Predictors of Attitude Toward the Online Ad Format To test the proposed model two multiple r e gression analyses were performed for each online advertising format. First, multiple regression analysis was used to examine

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114 the relationship between the independent variables of the three perceptual factors attitudes toward online advertising in general attitude toward the Web site and attitude toward the Internet and the dependent variable of attitude toward online ad format The relevant portion of the modified attitude-toward-the-ad model is shaded for reference and presented in Figure 4-2 Attitude toward Internet Online Ad Format Perceptions Attitude toward Online Ad Format Attitude toward Web Site Attitude toward Online Advertising Figure 4-2 Modified Attitude-Toward-the-Ad Model for the Online Context Using Shading to Indicate the Fir s t Set of Relationships to be Tested For banner ads the iI1dependent variables accounted for 44% of the variance in attitude toward online advertising format with 0rtly the three perceptual factors having a s ignificant relationship with the dependent variable. The data are presented in Table 4-18.

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115 Table 4-18. Regression Analysis Summary for Variables Predicting Attitude Toward Banner Ads Variable Attitude toward online advertising Attitude toward site Attitude toward Internet Entertainment factor Annoyance factor Information factor Note. Adjusted R 2 = .44 (n = 102,p < .01) *p < .05. **p < .01. B .03 -.21 -.01 .47 -.46 .28 SEB .10 .12 .16 .17 .09 .11 13 .03 -.15 -.01 .28** -.44** .2 5* Regression analysis for pop-ups followed a similar pattern with the independent variables accounting for 56 % of the variance in attitude toward format and the three perceptions being significant predictors of this attitude Table 4-19 presents these data. Table 4-19. Regression Analysis Summary for Variables Predicting Attitude Toward Pop-Up Ads Measure Attitude toward online advertising Attitude toward site Attitude toward Internet Entertainment factor Annoyance factor Info11nation factor Note. Adjusted R 2 = .56 (n = 102 ,p < .01) *p < .05 **p < .01. B -.01 .13 -.05 .33 -.54 .28 SEB .09 .09 .15 .12 .09 12 13 .0 1 .11 .02 .25** -.45** .22*

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116 While the variables in the regression equation for skyscraper ads accounted for 53% of the variance only the entertainment and annoyance factors were significant The data are presented in Table 4 20. Table 4-20. Regression Analysis Summary for Variables Predicting Attitude Toward Skyscraper Ads Measure Attitude toward online advertising Attitude toward site Attitude toward Internet Entertainment factor Annoyance factor Information factor Note. AdjustedR 2 = .53 (n = 97,p < 01) *p < .05. **p < .01 B 05 -.08 13 .59 47 06 SEB .08 10 .12 .13 .09 .13 8 .05 07 08 .43** 40** .05 Similarly, for large rectangle ads the variables accounted for 65% of the variance and only the entertainment and annoyance factors were significant predictors. In addition the attitude toward the Web site also emerged as a significant predictor of attitude toward this format. The data are presented in Table 4-21. The variables in the regression equation for floating ads accounted for 69% of the variance, with the entertainment and annoyance factors being significant. The data are presented in Table 4-22.

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117 Table 4-21. Regression Analysis Stunmary for Variables Predicting Attitude Toward Large Rectangle Ads Measure Attitude toward online advertising Attitude toward site Attitude toward Internet Entertainment factor Annoyance factor Information factor Note Adjusted R 2 = .65 (n = 117,p < .01) *p < 05 **p < .01. B 03 .25 -.05 .46 44 -.10 SEB .07 .08 10 .10 .07 .10 I3 .03 .19* -.03 34** 45** 08 Table 4-22. Regression Analysis Summary for Variables Predicting Attitude Toward Floating Ads Measure Attitude toward online advertising Attitude toward site Attitude toward Internet Entertainment factor Annoyance factor Information factor Note. Adjusted R 2 = .69 (n = 76 p < 01) *p < .05. **p < .01. B .10 .17 -.16 .77 -.81 .12 SEB .13 .13 .18 20 11 15 I3 .06 09 -.06 30** 57** .07 The variables in the regression equation for interstitial ads accounted for 81 % of the variance and all three pe1 ceptual factors were significant In addition attitude toward online advertising was significant as well The data are presented in Table 4-23

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118 Table 4-23. Regression Analysis Summary for Variables Predicting Attitt1de Toward Interstitial Ads Measure Attitude toward online adve1iising Attitude toward site Attitude toward Inte1net Entertainment factor Annoyance factor Information factor Note. Adjusted R 2 = 81 (n = 81,p < .01) *p < .05. **p < .01. B .18 -.05 -.07 .48 -.48 .40 SEB .07 .08 .11 .09 .06 .10 8 12* .03 .04 32** -.49** .30** Across all forn1ats, the perceptions play a significant role~ predicting attitude toward online advertising formats In addition, other variables were significant for certain forn1ats. Table 4-24 summarizes the significance of predictor variables across all formats Table 4-24. Summary of Significance of Predictor Variables Across All Formats Attitude toward online adv Attitude toward site Attitude toward Internet Entertainment factor Annoyance factor Informatio11 factor Banner Pop-up Skyscraper Large Floating Interstitial Rec * ** ** ** ** ** ** ** ** ** ** ** ** * ** *p < .05. **p < 01.

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119 The entertainment and annoyance factors were significantly related to attitude toward all online ad formats tested. The information factor was significant for some formats. As hypothe s ized the perceptions about online formats were related to attitudes toward those formats. While attitude toward online advertising and attitude toward the site were significantly related to attitude toward the format for two formats, attitude toward the Internet was not significantly related to attitude toward any format. Collinearity statistics for all formats were examined to assess multivariate multicollinearity. The common method for determining multicollinearity is to regress each independent variable on the other independent variables and examine the tolerance coefficients or variance-inflation factors. Tolerance levels of less than .20 and variance inflation factors (the reciprocal of tolerance) of greater than 4.0 suggest multicollinearity problems. Examining the tolerance levels and variance-inflation factors across all format s indicated no problems with multicollinearity. In addition, condition indices were examined to determine whether they indicated excessive collinearity among the variables For factors with high condition indices the variance proportions were compared to see if two or more variables were most heavily loaded on those factors. For all formats except large rectangles, the information and entertainment factors exhibited high linear dependence and were most heavily loaded on a single factor For large rectangles the attitude toward the site and the entertainment factor were most heavily loaded on a single factor and for floating ads, attitude toward the Internet and the annoyance factor both loaded on a single factor While these collinearity issues make the assessment of the unique influence of the correlated variables on the dependent variable difficult to determine, it does not diminish the primary finding

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120 of this study that perceptions play an i1nportant role in the formation of attitude toward the online ad f orn1at. Predictors of Attitude Toward tl1e Ad To determine the influence of attitude toward online ad format on Aact, multiple regression revealed the contribution to exp l ained variance in A a ct that is due to attitude toward online ad format and attitude toward online advertising. Figure 4-3 shows the portion of the modified attitude-toward-to-ad model with shading to denote th e variables under consideration Attitude toward Internet Online Ad Format Perceptions Attitude toward Online Ad Format Attitude toward Web Site Attitude toward Online Advertising Figure 4-3. Modified Attitude Toward the Ad Model fo r the Online Context Using Shading to Indicate the Second Set of Relation s hips to be Tested Bivariate corre l ations between the two independent variables were examined for col lin earity and a low but significant, positive relation s hip was found between the two variables ranging from r = .1 8 for pop-up ads tor = .33 for interstitial ads. Collinearity sta ti s tic s did not however, reveal any problem s with intercorrelation.

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121 The R 2 for banner ads was low with the two variables only contributing 14 % of the variance in A ad Attitude toward online advertising format was, however, a significant predictor of attitude toward the ad. The data are presented in Table 4-25. Table 4-25. Regression Analysis Summary for Variables Predicting Attitude Toward Banner Ads B Attitude toward online ad format .32 Attitude toward online advertising .10 Note. Adjusted R 2 = 14 (n = 102 p < 01) *p < .05. **p < .01. SEB 08 10 13 .37** .09 For pop-up ads, the R 2 wa s higher at 29 Attitude toward online advertising format was once again a significant predictor of A ad '" fhe data are presented in Table 4-26. Table 4-26. Regression Analysis Summary for Variables Predicting Attitude Toward PopUp Ads B Attitude toward online ad format .62 Attitude toward online advertising .01 Note. AdjustedR 2 = .2 9 (n = 102,p < 01) *p < 05. **p < .01. SEB 10 .13 13 56** 01 Skyscraper ads exhibited simi lar results with the variables contributing to 45 % of the variance and only the attitude toward the forrnat being a significant predictor of A ad The data are presented in Table 4-27. For large rectangle ads the variables contributed 56 % of the variance. Attitude toward online advertising format was once again a significant predictor of A ad The data are presented i11 Table 4-28.

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122 Table 4-27. Regression Analysis Summary for Variables Predicting Attitude Toward Skyscraper Ads B Attitude toward online ad f onnat 72 Attitude toward online advertising -.02 Note. Adjusted R 2 = 45 (n = 97, p < .OI) *p < .05 **p < 01 SEB 08 .09 B .67** .02 Table 4-28 Regre s sion Analysi s Stunmary for \ I ariables Predicting Attitude Toward Large Rectan g le Ads B Attitude toward online ad format .65 Attitude toward online advertising 10 Note Adjusted R 2 = .56 (n = 117 p < .01) *p < .05 **p < 01 SEB .06 .06 B .73** 10 Higher still was the contribution to variance by the variables to attitude toward the ad for floating ads (R 2 = .66) Attitude toward online advertising format was once again a significant predictor of A a d The data are presented in Table 4-29. Table 4-29 Regression Analysis Summary for Variables Predicting Attitude Toward Floating Ads B Attitude toward online ad format 76 Attitude toward online advertising .12 Note. Adjusted R 2 = .66 (n = 76,p < .01) *p < .05 **p < .01. SEB .07 .12 B .80** .07 Finally the variables contributed 74 % of the variance in attitude toward the ad for interstitial ads. The attitude toward the online ad format was the only significant predictor of Aa d The data are presented in Table 4-30.

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123 Table 4-30. Regression Analysis Srunmary for Variables Predicting Attitude Toward Interstitial Ads B Attitude toward online ad format .98 Attitude toward online advertising -.06 Note. Adjusted R= .74 (n = 81,p < .01) *p < 05. **p < .01. SEB .07 .09 B .88** -.06 In conclusion, for all fo1111ats, the regression equation revealed that while attitude toward online ad format was a significant predictor of A a d, attitude toward online advertising was not. The contribution to variance by the independent variables ranged from R 2 = .18 for banner ads to R 2 = 7 4 for interstitials. Behavioral Measures Respondents also reported the number of hours spent surfing the Web during the typical week (not including e-mail or gaming). J\. regression analysis using hours spent surfing as the predictor variable and attitude toward format as the dependent variable did not, however establish a significant relationship for any format. Respondents were classified according to whether they had ever made an online purchase or not and an independent samples t test was conducted for attitude toward the online ad format for each format Although no significant differences were found between the two groups for any format, the group of non-purchasers comprised only 8 % of the sample. ANOVA was used to test differences between mean attitude toward the format scores for each fonnat based on online purchase frequency in the past six months. This analysis also failed to demonstrate any significant differences between groups Comparing familiarity with the fom1at to attitude toward the format using one-way analysis of variance revealed that for two formats pop-ups and floating ads A rormat was

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124 significantly different based on familiarity. For these two formats, the more familiar, the less favorable the attitude toward the format. Table 4-31 presents the ANOVA data and Table 4-32 presents the post-hoc comparisons of means for all formats. Table 4-31. One-Way Analyses of Variance for Effects of Format Familiarity on Arormat Variable Banner Between groups Within groups Pop-up Between groups Within groups Skyscraper Between groups Within groups Large rectangle Between groups Within groups Floating ad Between groups Within groups Interstitial B etween groups Within groups *p < .0 5 **p < .01. df 2 99 1 100 3 93 3 112 3 72 3 78 ss 3.16 98.65 16.23 98.69 3.54 60.91 1 .77 96.27 24.45 125.65 3.68 86.88 MS 1.58 1.00 16.23 .99 1.18 .66 .59 .86 8.15 1.75 1.23 1.11 F 1.58 16 45** 1 80 .69 4.67** 1.10

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125 Table 4-32 Post-Hoc Comparisons of A ro rm at Means Across Format Familiarity Using LSD Format Banner Pop-up Skyscraper Large rectangle Floating ad Interstitial Very Familiar (a) 3.22 1 64 3.77 3.36 2.00 3.50 Familiarity Somewhat Familiar (b) 3.39 4.01 3.31 3.16 Somewhat Unfamiliar (c) * 3.41 3 50 3.50 Very Unfamiliar (d) * * 3.75 3 2.89 Note Superscripts indicate that the mean is significantly higher than the format indicated by the s uperscript (p < 05) *Cells with two or fewer responses. The relation s hip between clickthrough and A ro nn a t was also explored For each format two clickthrough questions were asked to gather data on whether respondents had ever clicked through on that format and the frequency of clickthrough on that format during the past six months For all fon11ats except large rectangles respondents who had ever clicked through on the format had a more favorable attitude toward that format Table 4-33 presents the mean attitude scores for the formats and the t values Frequency of clickthrough on the fortnat during the last six months was compared to attitude toward the format The top three categories (''7 or more," ''5-6," and ''3 4'') were combined because the top two categories received very few responses. ANOVA demonstrated significant differences for mo s t formats ; however post-hoc comparisons revealed that the differences were only between those who had clicked and those who had

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126 not. For those who had clicked, no significant differences were found based on frequency. Table 4-34 presents the post-hoc comparisons of means for all fo1mats. Table 4-33. Group Differences for Attitude Toward Online Ad Format Between Respondents Who Had Clicked Through on Certain Online Ad Forn1ats and Respondents Who Had Not Clicked Through Format Banner Pop-up Skyscraper Large rectangle Floating ad Interstitial *p < .05. **p < 01. M 3 49 2.31 4.03 3 52 3.86 3.79 Yes SD 89 1 15 .76 .96 61 1.00 M 2.51 1.58 3.58 3.26 2.86 3 13 No SD .99 92 .83 .89 1.50 1.03 Table 4-34. Post-Hoc Compariso11s of Af or m at Means Across Clickthrough Frequency Using LSD Format Banner Pop-tip Skyscraper Large rectang1 e Floating ad Interstitial Frequency of Clickthrough 3 + (a) 3.75 3.79 4.25 3 38 1-2 (b) 3 36 3.91 C None (c) 2.71 1.58 3.69 3.29 2 88 3.16 Note. Superscripts indicate that the mean is significantly higher than the forn1at indicated by the superscript (p < 05). df 100 64.9 95 114 61.3 80 t 4 64** 3.37** 2.76** 1 49 4.05** 2 50*

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127 The final question about each forrr1at dealt with whether respondents had ever later visited a site they saw advertised in a particular ad format Significant differences in attitude toward the fonnat were found for all formats except large rectangles based on whether respondents had ever later visited an advertised site or not. Table 4-35 demonstrates how respondents who had later visited an advertised site had more favorable attitudes to the format originally adve1 tising that site. Table 4-35. Group Differences for A rorrna t Between Respondents Who Had Later Vi s ited Sites Advertised Using Certain Online Ad Formats and Respondents Who Had Not Later Visited Sites Format Banner Pop-up Skyscraper Large rectangle Floating ad Interstitial *p < 05 **p < .01 Overview Later Visited M 3 50 2 35 4.02 3 46 3 83 3.98 SD 92 1.28 .77 97 60 .69 Not Visited M 2.89 1.70 3.69 3 30 2.96 3.12 Discussion SD 1.01 95 .83 .90 1 47 1.07 df 100 31 2 95 114 29 3 80 t 3 24** 2.32* 2.03* 87 3.30** 3.08** This chapter presented the findings of a study that examined the role of attitude toward the online ad for1nat in a po1iion of the modified attitude-toward-the-ad model This variable was positioned as a predictor of A a d Attitude toward online advertising wa s hypothesized to be another predictor of attitude toward the ad Predictors of attitude toward the online ad format were also tested, including ad format perceptions, attitude toward online advertising, attitude toward the Web site on which the ad is hosted and

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128 attitude toward the Internet. This study used six online ad formats and therefore produced six replicates of the test of the relationships in the model The next section will discuss the findings and offer possible explanations for relationships that were not supported. Study limitations will be addressed in the following section. Implications for the online advertising industry and online advertising theory will then be discussed. Finally, future research avenues will be addressed. Interpretation of Results The hypothesis that online ad perceptions are related to attitude toward the forn1at was supported for all six online ad formats tested in this study The formats differed however, in terms of the specific perceptions that were significantly correlated with attitude toward each format The entertainment and annoyance factors were significantly related to attitude toward all online ad formats tested. These findings support the hypotheses that perceptions of the entertainment value of an online ad is directly related to attitude toward the format and that perceptions of the annoyance caused by an online ad is inversely related to attitude toward the format. The hypothesis that perceptions of infortnation value are directly related to attitude toward the format was supported only for certain fonnats. The lack of consistent support for the relationship between information and attitude toward the format is important because it suggests that the information provided in ads may not necessarily improve the user's attitude toward that ad format Newer formats such as large rectangles that are capable of presenting more information, may not increase favorable attitudes toward that fonnat and make these ads more effective. The lack of a relationship between these two variables may have occurred because respondents were not instructed to seek info1mation

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129 from the ad formats and may not have given this dimension much consideration. Furthermore the multicollinearity diagnostics demonstrated a linear dependence between the entertainment and information factors for all but one format This relationship may have complicated the ability to assess the impact of the information factor on the attitude toward the forrnat Therefore this research cannot conclude that perceptions of the informational value of an online ad format are any less relevant in forming attitudes toward the fonnat than perceptions of annoyance or entertainment The other hypothesized predictors of attitude toward the online ad format were either found to be significantly correlated for only certain formats or not significantl y correlated. While attitude toward online advertising and attitude toward the site were significantly related to attitude toward the format for just one format each attitude toward the Internet was not significantly related to attitude toward any format. Previous research has shown that general attitudes, such as attitude toward online advertising and attitude toward the Internet, do not always correlate with more specific attitudes Furthermore while the attitude toward the Internet scale was adopted from another study (Chen & Wells 1999) the items may measure the comfort level and satisfaction of the user when surfing the Web and may have less relevance to attitudes toward formats. Additionally, the scale exhibited a lower-than-acceptable level of reliability (a = .60). Because of the limited time respondents spent on the Web site, they may not have had strong feeling s toward the site based on the advertising hosted on that site. Testing this specific relationship may require a more natural experimental setting and the existence of attitudes toward a Web site that exist prior to the introduction of an online advertisement

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130 Another key relationship tested in the model was that between the independent variables of attitude toward the online ad format and attitude toward online advertising and the dependent variable of attitude toward the ad. The regression equation revealed that while attitude toward online ad fonnat was a significant predictor of A a d, attitude toward online advertising was not. Although attitude toward online advertising was hypothesized to be a predictor of attitude toward the ad for online advertising it was not surprising to fmd that this variable was not a significant predictor for attitude toward the ad across all formats. Again, general attitudes such as attitude toward online advertising are more likely than specific attitudes to fail in predicting specific attitudes, such as attitude toward the ad. Therefore, while Hypothesis 1 that attitude toward the online ad format is directly related to attitude toward the ad was supporte
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Entertainment Attitude toward Internet 131 Annoyance I Information I / / "' Attitude toward Online Ad Format / / / / / / / / --/ / / Attitude toward Web Site Attitude toward Online Advertising Figure 4-4. Significant Relationships in tl1e Modified Attitude-Toward-the-Ad Model for the Online Context Amount of time spent surfing online per week and previou s online purchase behavior were also examined in relation to attitude toward the format and no relationships were established. Familiarity was a significa nt moderator of attitude toward the format for pop-ups and floating ads. In both cases, more familiarity was related to le ss favorable attitudes toward the format Clickthrough was a significant moderator of attitude for all formats excep t large r ectang le s. Previous clickthrough was related to more favorable attitudes toward the format. Study Limitations This study has a number of limitati ons, some related to the use of a survey as the method of data collection. First, the standardized B's for the relationship between attitude toward format and Aad ranged from .37 to .88, a relationship that grew stronger as

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132 respondents proceeded through each version of the survey. A possible explanation and validity issue is that respondents began to lose the ability to discriminate between the attitude toward the ad questions and the attitude toward the fo1mat questions, even though the instructions described what to consider in responding to each set of questions. 2 To test this hypothesis, surveys were coded to indicate whether it was the respondent's first exposure to the survey or the second. For each version of the survey, regressions were run using Ar o rrn a t as the independent variable and Aad as the dependent variable. Only the first format presented to respondents in each version was considered, which was a banner ad for Version 1 and a large rectangle ad for Version 2. For Ve1sion 1, only 10 of the 104 respondents completed this version after completing the second version, a sample size that made comparisons difficult. Although randomly assigned to a version based on the last digit of their Social Security number, 28 students who should have completed Version 2 first completed Version 1 first instead (possibly because they intended to complete both surveys and just co1npleted them in the order presented). Because of the disparity in sample sizes, this analysis was abandoned for Version 1. For Version 2 of the survey, the two categories were more comparable with 59 completes by previous respondents and 58 completes by first-time respondents. The results demonstrate that for respondents who had already completed one version of the survey, the attitude toward the first forrnat presented (large rectangles) predicted more variance in attitude toward the ad. Tables 4-36 and 4-37 present these data. 2 The survey design was constrained in that the presentation order of the formats could not be rotated. All respondents in Version 1 of the survey s aw banner ads pop-up ads, and then skyscrapers. All respondents in Version 2 saw large rectangles floating ads and then interstitials. The online survey program did allow for rotation of the ad format perceptions each time they were presented.

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133 Table 4-36. Regression Analysis Suminary for Attitude Toward Large Rectangle Ads for First-Time Respondents B Attitude toward format 63 Note. AdjustedR 2 = 45 (n = 56 p < .01) *p < .05. **p < 01. SEB f3 09 .68** Table 4-37. Regression Analysis Summary for Attitude Toward Large Rectangle Ads for Second-Time Respondents B Attitude toward format 76 Note. Adjusted R 2 = .66 (n = 57 p < .01) *p < .05. **p < .01. SEB f3 .07 .82** Because of the possible relationship between exposure to previous survey question s and attitude toward the format, the results of this study should be considered preliminary Issues caused by two sets of formats, order effects, drop-outs, sample size and respondent participation in one or two surveys make descriptive comparisons difficult. However, because the concern of this study was testing the theoretical relationship and not comparing mean scores for attitude toward the format, the analysis using the pooled data set of respondents who were seeing the survey for the first time and those had previously completed the other version was deemed to be appropriate An improved design would have respondents assessing only one format of online advertising to eliminate the bias that occurred when respondents were exposed to the same set of questions more than once. The range may also be explained by the familiarity with certain fom1ats and the l ack of experience with others. When respondents are familiar with a certain ad fonnat, they may be capable of holding distinct attitudes toward the specific ad and its format. When respondent s are not as familiar with a forn1at, they may not be able to discriminate

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134 their attitudes toward the ad from their attitudes toward the format. Table 4-38 presents levels of familiarity with eacl1 format. Respondents were significantly more familiar with banner ads and pop-tips (the first two ads presented in the Version 1) and were significantly less familiar with floating ads and interstitials (the last two ads presented in Version 2). Table 4-38. Post-Hoc Comparisons of Mean Familiarity Scores Across Formats Using LSD Familiarity M SD N Banner (a) 3 69 c cte f .51 102 Pop-up (b) 3 78 c ct ef .41 102 Format Skyscraper (c) 3 39d ef 69 97 Large Rec (d) .69 117 Floating (e) 2.70 .95 76 Interstitial (t) 2.78 .93 82 Note. Superscripts indicate that the mean is significantly higher than the format indicated by the superscript. Note. Familiarity was rated on a 4-point sca l e where 4 = very familiar and 1 = very unfamiliar. Although respondents were also instructed to use the sample online ad format as an example for the entire range of online ads in that format and respond to questions based on their attitudes and perceptions of the format in general, some respondents may have responded based on their attitudes and perceptions of that specific online advertiseme11t or any previously-held attitudes toward the advertised brand. Analysis of the online ad perceptions was done by creating three factors using the aggregate data. Although the aggregate solution was used to allow comparisons across format, these three factors may not have been the best representation of perceptions for each format (see Appendix E)

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135 Implications for Online Advertising Theory Attitude toward the fotmat was found to be a significant predictor of attitude toward the ad, which is a known influence on brand attitude and purchase intentions (Gardner, 1985; Homer, 1990; MacKenzie & Lutz, 1989; MacKenzie, Lutz, & Belch 1986; Miniard Bhatla, & Rose 1990; Mitchell & Olson, 1981 ) Furthe1more, this study identified key perceptual dimensions that explain A rorn1at Also, Aror mat corre l ates significantly with clickthrough behavior and familiarity These findings suggest A rormat is an important conceptual variable to consider in studies of online advertising effects Implications for Online Advertising Industry These results have a number of implications for the advertising industry When considering new online ad fortnats or selecting between the available ad formats, designers and advertisers should consider the perceptions consumers will have about the ad format If an online ad can be entertaining, but not annoying, the ad will generate the most favorable attitudes toward an ad format. The information value, however, does not have a consistent impact on this attitude. Because attitude toward the format is related to attitude toward the ad, which has been shown in other studies to influence such variables as brand awareness and consumer behavior, creating and choosing online ad forn1ats that gamer the most favorable attitudes should be of concern to the industry. Future Research An extension of this research could manipulate the variables of entertainment, information, and annoyance in the stimulus ads to determine the possible influence on attitude toward the format. Of particular interest would be a test of the relationship between informational content and attitude toward the online ad format to understand

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136 whether informational content does in fact, influence attitude toward the for1nat to a greater degree than the current study suggests. A replication of the current study could involve exposing respondents to only one 011line ad fonnat and measuring additional variables, such as brand attitudes. A measure of pre-existing brand attitudes could determine whether brand attitudes impact attitude toward the format. Future research could also examine consumer behavior in a more natural setting Such a study could incorporate a test in an online environment of the attitude-behavior link that has been demonstrated in previous re se-u-c h Additional studies could also focus on creating conditions that will facilitate te s tin g the relationships found not to be significant in the present study or incorporate other variables from the attitude-toward-the-ad model. For example, the relationship between attitude toward the site and attitude toward the format could be explored using a sample of st1rfers who have had prior experience with a particular site. Conclusion While this study was st1ccessful in testing relationships among variables in the modified attitude-toward-the-ad model, a more representative sample was needed for descriptive statements about attitudes and perceptions of the formats. This research is detailed in the next chapter. This study focused un a limited number of attitudinal variables and perceptual items so that data for s ix online advertising for1nats could b e gathered from each respondent.

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CHAPTERS STUDY 3 This chapter discusses the findings of a study that used a Web-based survey with a nationwide sample of Internet users to collect descriptive data about perceptions of and attitudes toward online advertising formats. Purpose The purpose of Study 3 was to produce descriptive data of Web user attitudes toward various online advertising formats. Study 3 attempted to make an applied contribution to the study of online advertising attitudes by using a national survey of adults and a larger sample size than Stt1dy 2. While the data from Study 2 was used to test the relationships among variables data from Study 3 produced descriptive data on attitudes toward online advertising fonnats, detennined how each format performed on the perceptual dim ens ions, and tested the abi li ty of perceptions to predict attitude toward online ad fonnats. This survey also collected data on attitude toward online advertising in general and behavioral data with respect to Internet usage. While Study 3 can be viewed as a replication of Study 2 with a more representative sample, some of the relationships explored in Study 2 were not tested in St11dy 3. Hypotheses This study tested the following three hypotheses: 1 Web user s' attitudes toward online advertising formats vary across formats. 2. Web users perceptions of online advertising formats vary across formats. 137

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138 3. Online ad format perceptions (i.e., entertainment, annoyance, and infotmation) are directly related to attitude toward that advertising format. Using a limited sample, Study 2 found support for these three hypotheses with some exceptions Respondents had significantly higher attitudes toward skyscraper ads and significantly lower attitudes toward pop-up ads, but no significant differences were found among the other four formats. In terms of the perceptions, banners were found to be low in entertainment, annoyance, and information. Pop-ups were perceived to be the most annoying, the least informative, and low in entertainment. Skyscrapers were the least annoying, the most informative, and moderately entertaining. Large rectangles were low in entertainment and annoyance, but higher in inforrr1ation. Respondents perceived floating ads to be the most entertaining format, high in annoyance, and low in information. Finally, interstitials we re rated high on the entertainmen t factor and moderate on an11oyance and information. Online ad format perception s were found to be directly related to attitude toward the format, with the exception of the influence of the information factor on some of the online advertising formats tested. Method Sample The survey frrm Esearch was contracted for generating and contacting a sample of respondents. Esearch began developing a panel for online research in 1995 and currently has a database of over 450,000 members The company contacted 4,000 panel members through e -mail invitations and asked them to participate in a 15-minute survey. The sample was selected based on recency (i.e only the newest panel members were

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139 sampled) and was screened to include adults between the ages of 18 and 65 who were U.S. residents Between 500 and 1000 people were contacted on five business days during a three week period beginning Jan. 31, 2003. The survey closed on Feb. 24, 2003. No incentive was offered and no reminder e-mails were used. Procedure Th e e-mail invitation included a hypertext link to an online survey built using the software package provided by Survey Monkey (surveymonkey com). This software provided an attractive graphical presentation of the survey. Using a Web-bas e d survey offered cost and speed benefits over a mail survey. Upon entering the survey, re s pondents were exposed to two examples of each of six online ad formats. Questions about each format followed the exposure Questions were presented across multiple screens. For example, respondents clicked on two online ad format examples on one screen, then proceeded to the next screen for the perceptual measures and then to another screen for the attitudinal measures This procedure prevented respondents from browsing the entire survey before responding and required that respondents answer questions in a predetermined order. This approach also allowed for branching and skips, which were incorporated into this survey for respondents who could not view the examples of certain ad formats and were restricted from an swe ring questions about that format. In the middle of the survey, respondents were presented with a message that they had only three formats remaining This tactic was used to help motivate respondents to complete the survey and update tl1em on their progress

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140 Stimulus Ads .. The stimulus ads were drawn from various collections, galleries ana c 1 portio 10s of online advertising to ensure that every time the site was accessed, the sal"h d .1..l,Je a was prese11ted. To mini1nize any strong feelings toward the product advertised or the advertiser itself, the selected ads did not represent products or companies th . at may el1c1t strong negative attitudes ( e.g. alcohol, airlines). The products or cornpa 111 c es 1eatured m the online advertisements included American Express, Office Depot MSN, Citibank Compaq, AT&T, Dell Handspring (handheld computer) the Boston Rea S L ox o Jack ( vehicle security system), Travelocity and Audi. Me asures The measurement scales used to tap the attitudes and perceptual dun . ens1ons are presented below. The survey is included in Appendix D Attitude toward online ad format. This study used the following fou 1 r-1 em, 5-pomt semantic diffe1ential scale to measure attitude toward online advertising fi .........,, lik Qr111at: ed b y me / disliked by me, one of the best formats / one of the worst formats, an ex ll ce ent ad format / a poor ad format, and I love it/I hate it. An index for attitude toward n1 o mead format scores was created by averaging the responses to the four items Thi 1 s sea e was verified in the previous study through factor analysis and the calculation f C b 0 ron ach s alpha. All items converged on one factor. The Cronbach s alphas ranging fr 9 om. 2 to .97 for the six formats demonstrated the reliability of tl1e scale. Ad format perceptions. Study 1 identified 15 perceptual descriptors f 1 o on 1ne advertising including annoying, intrusive, disruptive, overbearing, entert . a1rung amusmg, eye-catcl1ing, informative, useful, beneficial, innovative, different, sophi 1 d s 1cate attractive, and elaborate. In Study 2, respondents rated online ad formats h on eac of'these

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141 .. dimensions. The data from Study 2 were factor analyzed to identify three factors: entertainn1ent, am1oyance, and info1mation. For Study 3, three perceptions were selected to represent each factor derived in Study 2. Narrowing the list of perceptions from 15 to 9 created a list that was more manageable for respondents when presented six tin1es ( once for each forrr1at) throughout the survey for Study 3. The nine perceptions were chosen based 011 the results of the factor analysis from Study 2. Innovative, different, and entertaining were chosen because these perceptions loaded highest on the first factor. Disruptive, annoying, and intrusive were three of the four perceptions that loaded on the second factor. Informative useful, and beneficial were the only perceptions that loaded on the third factor. Attitude toward online advertising. This study used a three-item, 5-point Likert scale to measure attitude toward online advertising. This scale has been previously applied to the measurement of attitudes toward Internet advertising (Previte, 1998). The scale included the following items: Advertising on the Web is a good thing; My opinion of advertising on the Web is unfavorable; and Overall, do you like or dislike the advertising you see on the Web? Responses to the three items were averaged to create an index. This scale was verified in the previous study through factor analysis and the calculation of Cronbach' s alpha. All items loaded on the same factor and it was detemuned that Cronbach' s alpha would not be improved with the deletion of any item from the scale (u = .84). Behavioral measures. The survey included questions measuring whether responde11ts had ever clicked tlnough on each of the ad formats, how often in the past six months had they clicked through on that ad format, and whether exposure to a certain

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142 format had ever prompted them to later visit the Web site. Format familiarity data was also coll e cted. Tl1e survey also asked if respondents had ever made an onl i ne purcha se and how many online purchases had been made in the past six months. Demographics. Detailed demographic information was collected to assess the generali z ability o f the results to the general population of Internet users. Respondent s were asked to report their gender age race employment status state of residence marital status and income. Other questions collected data on respondents' primary Internet connection, the year they started using the Internet on a regular basis, and th e ntunber of hours spent surfmg the Web each week Results Sample A total of 1 269 people responded to the e-mail invitation and 1,075 surveys were consider e d complete and usable The response rate was 31.7 % and the completion rate was 26 9 %. Comparin g these respons e rates to other Web-based surveys showed that de s pite the fact this survey did not incorporate incentives or reminder e-mails, the response rate is still within an acceptable range found in other Web-based surveys. MacElroy (2000) estimated that response rates for a sample drawn from a customer registration database range from 20 % to 50%. Couper, Traugott, and Lamias (2001) achieved a response rate of 41 % (47 % if partially co1npleted surveys were counted) in a survey of U niversity of Michigan student s. A copy of the book ''We re Number One: The National Championship Season'' was offered as an incentive. The response rate may have also benefited from th e fact that the strrvey was being conducted for the student newspaper and the s ubject (affrrmation action in admi s sions) was timel y and controversial. Jones

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143 and Pitt (1999) achieved a response rate of 19 % for a Web-based survey of university staff at three universities. Medlin and Whitten (2001) had a 25% response rate for a Web based survey of business school deans. Research firtn Dynanuc Logic (2001) achieved only an 8% response rate for its ''Ad Reaction Study'' when sampling from its databa s e of respondents who had participated in previous research by the company. The sample of the current study was comprised of 60 o/ o men and 40% women. Two thirds of the respondents (67.7 % ) fell into the 25-44 age category. Almost 40 % of respondents were single and another 38 /o were married. The majority of respondents classified themselve s as white (84.8 % ), while black, Hispanic, Asian, and other group s were also represented These demographic charc:1c teristics are provided in Table 5-1 Also included in this table are demographic s tatistics (when available) from the U.S Census Bureau (Newburger, 2001) for households with home Internet access Table 5-1. Gender Age, Race, and Marital Status of Respondents Characteristic Gender Male Female Age Under 25 years 25-44 years 45-64 years 65 years and up Study 3 Sample N 639 432 190 725 156 0 % 59 7 40.3 17.7 67.7 14.6 0 U.S Census: Households with Internet Access (numbers in thousands) a N n/a n/a 2,179 21,353 16,251 3,856 % n/a n/a 5 0 48.9 37.2 8.8 (Table 5-1 continues)

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(Table 5-1 continued) Characteristic Race White Black Hispanic Asian Native American/ Alaskan Other Decline Marital Status Single Married Divorced Living wi tl1 partner Separated Widowed 144 Study 3 Sarnple N 907 42 34 31 9 19 28 427 409 128 75 23 11 % 84.8 3.9 3.2 2.9 0.8 1 .8 2.6 39.7 38.1 11 .9 7.0 2.1 1.0 Note. Sample sizes differ as a result of omitted responses U.S. Census: Households with Internet Access ( numbers in thousands )a N 36,260 3,111 2,255 1 ,9 44 n/a 69 n/a n/a 28,872 n/a n/a n/a n/a % 83.1 7 1 5.2 4.3 n/a .2 n/a n/a 66.2 n/a n/a n/a n/a a Data from 2000 U. S. Census represent s hou se holder characteristics. In comparing to the sample cl1aracteristics to the U.S. Census data (Newburger, 2001 ), it is important to note tl1at the Census includes only people with home Internet access, while the sample may have included people whose only Internet access was at work or school. Also, the Census data represe11ts a sample of hoaseholders (i.e., heads of household), which excludes other Intern e t users within the household.

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145 Because the U.S. Ce11sus data are based on householder characteristics older ages are over-represented. Therefore, the proportion of people in each age category from tl1e U.S. Census does not accurately reflect the actual proportion of all U.S. residents in each age category with home Internet access. The U.S. Census percentage of married households with Internet access (66.2%) was higher than that of married respondents in the sample for the current study (38.1 /4). Percentages were most comparable for race. Fewer than two percentage points separated the proportion of white respondents in the sa mple for Study 3 and the U.S. Census. While the U.S. Census (Newburger, 2001) demonstrated higher percentages for blacks, Asians, and Hispanics it did not provid e an option for respondents to decline as did the current study, which captured almost 3o/o of respondents. Over half of the respondent s (57.5%) were employed full-time, while students were the second n1ost represented group at almost 11 %. In terms of annual household income for 2002, almost 38% of respond ents' hou se holds earned between $35,000 and $74 ,9 99. Over 44 % of respondents described themselves as having some college or a two-year degree as their highest level of education and almost 38% have a four-year degree or more education These data are presented in Table 5-2. Again, included in this table are demograpllics (when available) from the U.S. Census Bureau (Newburger, 2001) about households with home Internet access.

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146 Table 5-2. Education, Income, and Employment of Respondents Study 3 Sample U.S. Census (thousands)a Characteristic Employment Full-time Student Part-time Not working but looking Self-employed Homemaker Retired Other Education Less than high school High school grad Some college / 2-year degree 4-year degree or more Ir1come Less than $15K $15-24K $25-34K $35-49K $50-74K $75+ Decline to answer N 617 114 78 77 73 45 39 30 25 166 477 406 100 146 166 202 201 182 74 % 57.5 10.6 7.3 7.2 6.8 4.2 3.6 2.8 2.4 15 5 44.4 37.8 9 3 13.6 15.5 18.9 18.8 17.0 6.9 Note. Sample sizes differ as a result of omitted responses N n/a n/a n/a n/a n/a n/a n/a n/a 2,032 9,666 J 3,661 18,279 1068 1714 2982 4766 7825 11886 4074 % n/a n/a n/a n/a n/a n/a n/a n/a 4.7 22.1 31.3 41 .9 3 .1 5.0 8.7 13 .9 22.8 34.6 11.9

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147 Comparing the sample data to the U.S. Census data, the scmple is more educated with a lower percentage of respondents having a high school diploma or less and a higher percentage having some college or more. The sample, however, has lower household incomes with a higher percentage of respondents reporting an annual income of less than $50,000 and a lower percentage reporting incomes higher than $50,000 than that for the population represented by the U.S. Census data. A possible explanation is that the Study 3 sample skews younger and includes more students. In addition, because the sample is comprised of panel members who often earn financial rewards for participation in surveys, the panel may skew toward people with lower incomes. Respondents were asked to indicate their state of residence and these states were grouped into the four regions (Northeast 1 South 2 Midwest 3 and West 4 ) developed by the Census Bureau in 1942 and currently used to present census data. The highest percentage of respondents in this survey resided in the South Region as shown in Table 5-3 Also included in this table are regional statistics from the U.S. Census Bureau (Newburger, 2001) about households with home Internet access. 1 The Northeast Region is represented by Maine, New Hamp s hire Vermont, Ma ss achu se tts Connecticut Rhode Island New Jersey New York, and Pennsylvania 2 The South Region includes Maryland, Delaware, West Virginia, Virginia, Kentu c ky Tennessee, North Ca rolina South Carolina, Georgia, Florida, Alabama, Mississippi, Arkansa s, Loui s iana Oklahoma Texas and th e Distri ct of Col umbia 3 The Midwest Region i s co mpri se d of No rth Dakota South Dakota, Nebraska, Kansa s, Mis so uri I owa, Minnesota, Wisconsin, Illinoi s, Michigan, Indiana and Ohio. 4 The Midwest Region i s com prised of North Dakota South Dakota Nebraska, Kansas Missouri, I owa, Minnesota, Wisconsin, Illinoi s, Michigan, Indiana and Ohio.

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148 Table 5-3. Geographic Region of Residence of Respondents Region Northeast South Midwest West Study 3 Sample N 210 352 258 242 % 19 8 33 1 24.1 22.8 Note. Sample si z e s differ as a result of omitted respon s es U S. Census: Households with Internet Access (numbers in thousands) N 8 620 9,929 14 ,. 104 10 685 % 19 8 22 8 33 0 24.5 The geographic distribution of respondent .:; in the sample for Study 3 is comparable to that reported by the U S. Cen s u s Bureau (Newburger, 2001). The proportion of respondents in the sample from the Northeast and West regions is practically identical to the proportions for those regions reported by the Census. The sample for Study 3 had a higher representation of southern respondents and a lower representation of midwestern respondents than the U.S. Census data (Newbu1 ger 2001 ). Respondents were also asked abot1t the primary Internet connection, which was either a 56K modem or a cable modem for the majority of respondents. Many respondents started using the Internet prior to 1994 (17 3 % ), while the highest percenta g e started using the Internet in 1996 or 1997 (25 7%). Less than 14% of respondents started usin g the Internet in 2000 or later These data are provided in Table 5-4.

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149 Table 5-4 Internet Usage Characteristics of Respondents Characteristic N % Primary Internet connection 56Kmodem Cable modem DSL Do not know Tl or better 28.8K modem Other Year started using In tern et Prior to 1994 1994-1995 1996-1997 1998-1999 Since 2000 374 329 181 75 72 24 13 186 234 277 234 143 34.8 30.6 16.8 7.0 6.7 2.2 1 2 17.3 21.8 25.7 21.8 13 4 Note. Sample sizes differ as a result of omitted responses Respondents reported that they spend an average of almost 18 hours a week surfing the Internet (not including e-mail, gaming, or instant messaging) (M = 17.59 SD= 17 .96). As pre se nted in Table 5-5, almost all respondents have previously made an online purchase (94.3%) and the highest percentage of respondents (30.9%) has made seven or more online purchases in the past six months.

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150 Table 5-5. Online Pu1chase Behaviors of Respondents Bel1avior N Made online purchase Yes No Number of online purchases in past 6 montl1s None 1-2 3-4 5-6 7 or more 1014 61 106 205 252 180 332 Note. Sample sizes differ as a result of omitted responses. Attitude Toward Online Advertising % 94.3 5 .7 9.9 19.1 23 4 16.7 30.9 As mentioned previously, Study 2 verified the items used in the three-item attitude toward online advertising scale. This scale was employed in the present study and coefficient alpha was recalculated based on the data from Study 3 (a= .83). The mean attitude toward online adve11ising score was slightly above neutral (M = 3.25, SD= .87). Perceptions of and Attitude Toward Online Advertising Format The present survey also collected data on the attitudes toward six online advertising formats and ratings of the perceptual items for these formats. The six formats included banner ads, pop-ups skyscrapers, large rectangles, floating ads, and interstitial s. Attitude toward format was represented by the mean of four 5-point semantic differential scales (like / dislike best/worst excellent/poor, and love/hate). The positive end points were alternated in the survey and data were later transposed for two of the scales so that the high end of the 5-point rating scale would represent the most positi ve

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151 responses (like, best, excellent, and love) Coefficient alpha for this scale was recalculated based on the data collected in this study and demonstrated high reliability for each format (Table 5-6). ''Entertainment'', the first perceptual factor represented the mean of the entertaining, innovative, and different perceptt1al items, each rated on a 5-point Likert scale. The second perceptual factor, ''Annoyanc0'', represented the mean of the annoying intrusive, and di s ruptive descriptors. Finally ''Information'' represented the mean of the informative useful, and beneficial perceptual items. Ratings for all items were transposed so that the high end of the 5-point rating scale would indicate that the respondent strongly agreed that the forrnat exhibited that perceptual dimension Coefficient alphas for these perceptual factors were recalculated based on the data collected in this study and demonstrated high reliability for each fo11nat particularly for the annoyance and information factors. Table 5-6 presents the coefficient alphas for these measures based on data from the present data. Table 5-6. Coefficient Alphas for Measures Across Formats Banner Pop-tip Skyscrape : Large Rec Measure (a) (b) (c) (d) n = 1056 n = 1062 n = 1056 n = 1063 A rormat Entertain Annoy Inform .89 .75 .90 .83 .90 .76 .90 .89 .92 .79 .9 1 .88 .94 .81 .91 .90 Floating (e) n = 1061 .96 .85 .92 89 Interstitial (f) n = 1 066 .9 4 .85 .93 .89 ANOV A was used to compare attitudes and the perceptual factors across online ad formats and significant differences were found between formats for all attitudes and perceptual factors These results are presented in Table 57.

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152 Table 57. ANOV A for Formats on Attitude and Perceptual Item Factor Indices Variable df SS MS F Attitude toward online ad format Between groups Within groups Entertainment factor Between groups Within groups Annoyance factor Between groups Within groups Information factor Between groups Within groups *p < .0 5 **p < .01 5 6359 5 6357 5 6357 5 6357 2596.03 519 21 498.03** 6629 37 1.04 1157 19 231.44 311.06** 4729.72 .7 4 2512 23 502.45 504.43** 6331.99 991.59 4908.49 1.00 198.21 256.84** .7 7 The LSD procedure was used to conduct post-hoc comparisons of means. As shown in Table 5-8, significant differences in attitude existed between the fortnats when paired for po s t-hoc comparisons. Attitude toward the format mean scores were significantly different for every pair of formats (15 out of 15 comparisons). Similar results were obtained for the annoyance factor, with all 15 possible pairs showing a statistically significant difference. Interstitials and skyscrapers were the only pair of forrnats that exhibited no significant difference on the entertainment factor while only the banners / large rectangles pair as well as the floating ads / interstitials pair failed to exhibit significant differences on the info1n1ation factor. These data provide support for Hypothesis 1 that Web users have different attitudes toward various online ad formats (15

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153 of 15 possible comparisons) as well as Hypothesis 2 that perceptions vary across fom1at s (42 of 45 possible comparisons). Table 5-8. Post-Hoc Comparisons of Attitude and Perceptual Format Means Across Formats Us ing LSD Measure A rormat Entertain Annoy Inform Banner (a) n = 1057 3 37 bdef 3.3 7bef Pop-up (b) n = 1062 1.60 2.46 4 48 acdef 2.35 Skyscraper (c) n = 1056 3 56 abdef 3.29 abd 2.6 1 3 57 abdef Large Rec ( d) n = 1063 3.11 bef 3.38 bef Floating (e) n = 1061 3 89 abcdf 3 82 acdf Inter stitial (f) n = 10 66 3.29 abd 3.69acd Note. Superscripts indicate that the mean is significantly higher than the format indicated by the superscript. Note. Perceptual items were rated on a 5-point scale with 5 = stro ngl y agree. p < .05 Relationship s among Variables Multiple regression was u sed to examine the relationship between the perceptual factors and attitude toward each a d for1nat for each of the six formats Tables 5-9 through 5-14 show the multiple regression results for each online advertising format. The three factors are significant predictors of attitude toward the online ad format for all formats. As expected, annoyance has a negative relationship with attitude toward the format whereby as annoyance declines, attitude becomes more favorable. For banner ads, the entertainment factor contributes the least to attitude toward the format Table 5-9 present s the data for banner ads

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154 Table 5-9. Regression Analysis Summary for Perceptual Factors Predicting Attitude Toward Banner Ads Factor Entertainment Annoyance Inforrnation B 15 46 .33 SEB .03 .02 .03 Note. Adjusted R 2 = .58 (n = 1055 p < .01) *p < .05. **p < 01. J3 13** -.51 ** .29** Inforrnation contributes the most to variance in attitude toward pop-up ads (Table 5-10). While perceived to be more annoying than banner ads, the reason the annoyance factor does not explain more of the variance could be attributed to the high correlation between the entertainment and annoyance factors for pop-up ads (r = .73). Table 5-10. Regression Analysis Summary for Perceptual Factors Predicting Attitude Toward Pop-Up Ads Factor Entertainment Annoyance Inf 01mation B 18 -.28 .35 SEB .03 .02 .03 Note. Adjusted R 2 = .53 (n = 1060 ,p < .0 1) *p < .0 5 **p < 01. f3 .20** -.29** .41 ** For both banner ads and pop-ups, the three factors contribute only 58% and 53 % of the variance, respectively. The contribution to explained variance for these two formats is lower than the other four formats The regression results for skyscrapers, large rectangles floating ads and interstitials are all similar in that the annoyance factor contributes the most to variance in attitude toward the format and ha s a negative relationship with attitude. Information is th e next most significant factor in explaining variance in attitude toward these four formats

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155 Finally, the entertai1lll1ent factor, while still significant in all cases, plays a less prominent role in explaining variance in attitude. The three factors contribute anywhere from 69 % to 75o/o of the variance in attitude toward the fonnat for these four formats, which is higher tl1an that for banners and pop-up ads. Tables 5-11 to 5-14 illustrate these results. Table 5-11. Regression Analysis Summary for Perceptual Factors Predicting Attitude Toward Skyscraper Ads Factor Entertainment Annoyance Information B .24 -.43 .41 SEB .03 .02 .03 Note. Adjusted R 2 = .69 (n = 1054 ,p < .01) *p < .05. **p < .0 1. B .2 1 ** -.43** .36** Table 5-12. Regression Analysis Summary for Perceptual Factors Predicting Attitude Toward Large Rectangle Ads Factor Entertainment Annoyance Information B .21 47 .40 SEB .03 .02 .03 Note. Adjusted R 2 = .7 1 (n = 1062,p < .01) *p < 05. **p < .01 B .17** -.48** .33** Table 5-13. Regression Analysis Summary for Perceptual Factors Predicting Attitude Toward Floating Ads Factor Entertainment Annoyance Information B 35 57 .42 SEB .03 .02 .03 Note. Adjusted R 2 = .7 5 (n = 1060 ,p < .01) *p < .05. **p < .0 1. B .26** -.47** .30**

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156 Table 5-14. Regre ssion Analysis Summary for Perceptual Factors Predictin g Attitude Toward Interstitial Ads Factor Entertainment Annoyance Inf or1nation B .26 55 .31 SEB .03 .02 .OJ Note. AdjustedR 2 = .7 4 (n = 1065 ,p < .0 1) *p < .05. **p < .01. 13 .22** .53** .26** Collinearity statistics for all formats were examined to assess multivruiate multicollinearity An examination of the tolerance levels and variance-inflation factors did not indicate multicollinearity for any format. Condition indices were also examined to dete1rnine whether they indicated excessive collinearity among th e variables. For factors with high condition indices the variance proportions were cornpared to see if two or more variables were most heavil y loaded on those factors. For banners skyscrapers, and large rectangles, the annoyance and information varia bles loaded on th e same factor For pop-up s, floating ads and interstitials, the entertainment and info11nation variables loaded on the same factor. While these collinearity isst1es n1ake the assessment of the unique influence of the correlated variables on the dep e ndent variable difficult to determine it does not diminish the primary fmding of this study that perceptions play an important role in the formation of attitude toward the online ad format Behavioral Moderators S eve ral b ehavio ral relation shi ps were explored to understand the influence of behavior on attitude toward the online advertising fortnat. The first three variables exa mined included the year respondents first s tarted using the Internet the primary

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157 Internet connection, and the average number of hours spent surfing the Web each week. Other variables conside r ed includ e forrnat familiarity, on lin e purchase hi story, and clicktbrough beha v ior Respondents were asked the year tl1ey first started using the Internet on a regular basis and responses were then grouped into one of two categories: prior to 1997 and 1997-2003 An independent samples t te s t found that late adopters (1997-2003) were more likely than early adopters (prior to 1997) to have more favorable attitudes tow ard floating ads and interstitial ads. Tab l e 5-15 pre se nts the means and t values. Respondents also reported the number of hours spent surfing the W eh during the typical week (not including e mail, gam i ng or instant me ssaging). A correlation analysis for hour s spent surfing and attitude toward format as the dependent variab l e produced a significant correlation only between surfing hours and attitude toward pop-up ads (r = .07, n = 1057 p = .02). Table 5-15. Group Differences for Ar ormat Between Early and Late Internet Adopters Format Banner Pop-up Skyscraper Large rec Floating ad Interstitial Early Adopters Late Adopters (prior to 1997) (1997-2003) M 3.39 1.56 3.60 3.13 2.74 2.56 SD .91 .83 .86 .95 1.35 1.07 M 3.36 1.64 3.52 3.09 2 99 2.77 SD 88 .86 .89 1 00 1.32 1.13 *p < .05 **p < .01. df 1054 1059 1053 1060 1058 1063 t .58 -1 .5 5 1 47 .65 -2 99** -3 02**

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158 An independent samples t test comparing A ro rm at for respondents with high-speed Internet access to those with low-speed revealed sigilificant differences between the groups for two formats: pop-ups and floating ads. For botl1 of these formats respondents with low-speed access had more favorable attitudes toward the format (Table 5-16). Table 5-16 Group Differences for A ro r mat Between High-Speed Internet Access and Low-Speed Internet Access Respondents For1nat Banner Pop-up Skyscraper Large rec Floating ad Interstitial *p < .05 **p < .Ol. Low speed High speed M 3.34 1.66 3 59 3 14 2.96 2 62 SD .87 .87 .88 .97 1 35 1.11 M 3.39 1.55 3 53 3.08 2.78 2 69 SD df t .92 1055 88 83 955 56 2.09* .87 1054 .98 98 1061 1.06 1.32 1059 2.08* 1. I O 1 064 -1 02 Previou s clickthrough behavior was also reported by respondents who were a s ked wl1ether or not they had ever clicked through on each online ad format. Using an independent samples t test to compare means revealed that respondents who had cli c ked through on a sp e cific format had more favorable attitudes toward that online ad format a result that l1eld true across all online ad formats. Table 5-17 presents these results.

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159 Table 5-1 7 Group Di f ferences for A ronn a t Between Respondents Who Had Clicked Through on Certain Online Ad Formats and Respondents Who Had Not Format Banner Pop-up Skyscraper Large rectan g le Floating ad Interstitial *p < .05. **p < .01 M 3 49 2.00 3 80 3.51 3.54 3.36 Y e s No SD M 84 2.55 1.02 1 32 75 3 05 .84 2. 72 1 17 2 72 1 02 2 43 SD .84 56 .90 .94 1 33 1.03 df t 1055 12 05** 592 22 12.4 9 ** 583 50 13.40** 1055.91 14 44** 271 86 8 25** 1064 12.65** Familiarity with the for1nat was also compared to attitude toward the online ad formats. ANOV A demonstrated how mean attitudes toward the ad fotmats are significantly differ e nt based on the familiarity with the format for four formats: pop-up ads, skyscrapers, floating ads, and large rectangles Post-hoc analysis of mean s revealed that the greater the familiarity, the less favorable the attitude toward the format for pop ups and floating ads a situation that was reversed for skyscrapers and large rectangle s. The ANOV A data are presented in Table 5-18 and the post-hoc comparisons of means are provided in Table 5 19.

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160 Table 5-18 One-Way Analyses of Variance for Effects Format Familiarity on Ar onnat Variable Banner Between groups Within groups Pop-up Between groups Within groups Skyscraper Between groups Within groups Large rectangle Between groups Within groups Floating ad Between groups Within groups Interstitial Between groups Within groups *p < .05. **p < .01. df 3 1053 3 1058 3 1052 3 1059 3 1057 3 1062 ss 3.18 848 33 47 .41 711.75 23.07 790.37 9 46 1000.62 1 86.22 1711 .66 8.49 1288.83 MS 1.06 .81 F 1.32 15 .80 23.49** .67 7.69 .75 3.15 .95 62.07 1 .62 2.83 1.21 10.24** 3.34* 38.33** 2.33 Respondents were classified according to online purchase experience and an independent san1ples t test was conducted for A ronnat Significant differences were fou11d for three formats (banners, pop-ups and floating ads), but the direction of that difference was not consistent. Table 5-20 presents these data.

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161 Table 5-19. Post-Hoc Compariso11s of A rormat Means Across Format Familiarity Using LSD Forrr1at Banner Pop-up Skyscraper Large rectangle Floating ad Interstitial Very Familiar (a) 3 38 1.53 3.66b cd 2.37 2.55 Fami li arity Somewhat Familiar (b) 3 35 2.25 8 3.07 2.77 8 2.68 Son1ewl1at Unfamiliar (c) 3.05 2.59 8 3 26 2 .8 4 2 .70 Very Unfamiliar (d) * 3.01 2.89 3.48ab c Note Superscripts indicate that the mean is significantly higher than the format indicated by the superscript (p < .05). *Cells with two or fewer responses Table 5-20. Group Differences for A rormat Betw ee n Respondents Who Had Made an Online Purcha se and Those Who Had Not For1nat Banner Pop-up Skyscraper Large rectangle Floating ad Interstitial *p < .05. **p < .0 1. M 3.39 1.58 3.56 3.11 2.83 2.65 Yes No SD M SD .90 3.06 86 .8 4 1 .90 .96 .87 3.56 1.00 .96 3.03 1 .22 1 .33 3.28 1.43 1.10 2 .80 1 14 df 1055 1060 1054 63 44 1059 1 64 t 2.76** -2.84** .02 .50 -2.50* -1.02

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162 Discussion Overview This study used a national survey to collect descriptive data about perceptions of and attitudes toward online advertising formats. In addition, this study tested the ability of the perceptions to predict attitude toward on line ad for111ats. This discussion section will provide an interpretation of the results study limitations, implications of the findings, and directions for future research. Interpretation of Results The data supported the three hypotheses of tliis study. For each online ad format, Web users' attitudes differed across the six formats. Skyscraper ads received the mo st favorable evaluations, followed by banners large rectangles, floating ads, and interstitials. Attitude toward pop-up ads was significantly less favorable than that for any other format. Users' perceptions also differed significantly across formats Compared to other ad formats, banner ads were rated as being low on entertainment, low on annoyance and moderate on information. Pop-ups were rated as being the highest in terms of annoyance and the lowest on the entertainment and information factors. Skyscrapers were rated high on entertainment, the lowest on annoyance, and the highest on info1mation. Large rectangles received moderate ratings on all three factors. While rated as being the most entertaining, floating ads were also rated the second highest on annoyance and the second lowest on information. Interstitials received high ratings on entertainment and moderate ratings on information and annoyance. Furthermore the three factors of entertainment, annoyance, and information had a significant impact on attitude toward the ad. The factors were si2IDficant predictors and

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163 explained 53% to 75% of the variance in attitude toward the forrnat. For all formats except pop-ups, the regression weight for annoyance was the highest weight of the three factors. Because of the strong correlations among the tlrree factors the regression weights cannot, however, be entirely trusted to indicate relative strength. Beca11se people hold a unique stereotype about each online advertising format, the formats can be profiled in a way that can be t1seful to advertisers Based on the goals of an online advertising campaign, advertisers can use such a profile to choose the appropriate online ad for1nat. For example, skyscrapers may be capable of conveying information, but are lower on entertainment and may be less likely to catch the attention of Web users Mean scores were calculated for each forrnat on each of the nine perceptual descriptors. As demonstrated in Figure 5-1, the forrnats exhibit unique combinations of perceptions by respondents. Pop-ups are the most differentiated, rating the lowest on i11formation and entertainment and the highest on annoyance Floating ads were the second lowest format on information and the second highest on annoyance, but we1e also rated the most entertaining. Skyscraper ads were rated highest on inforrnation, lowest on annoyance, and moderate on entertainment Study Limitations Panel research has received its share of criticism. Two common problems are panel fatigue and panel conditioning (Schonlau, Fricker & Elliott, 2001). Fatigue occurs because panel participants tire of filling out multiple surveys during a short period of time and conditioning results when participants learn to fill in the easiest response. The research company used to draw the sample of respondents for this study selected only the

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164 most recent (and presumably, the least tired and conditioned) additions to the panel. This common procedtrre addresses th e se isst1es 5 0 4 5 4.0 3 0 2 5 2 0 1.5 1 0 0.5 0 0 e i:}~ ~Cl) e e ~Cl) e ~ ~ ~ ~4' t-' .;,,":I ~ t,e<1' 'b-~ ~o <::>q 0~ !-,.O' e<:' ~<:<:)~ ~e Q ,~<:,~ ,~ 'v<:Banner --aPop-Up Skyscraper X Large Rec )K Floating Interstitia l Figure 5-1. Comparison of Formats Across Perceptual Descriptors

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165 The other major criticism of panel studies is that they are not representative (Churchill 1999) For this study, the population was Internet users so sampling from an online panel was appropriate. For other topics, such a sample may not be as representative. This problem is often addressed through weighting or using a complementary survey methodology ( e.g ., mail) The lack of an incentive in this study may have created a more representative sample because participation was not fmancially motivated Studies that use financial incentives may oversample panel members mo s t in need of money. Despite these drawbacks sampling panel members was determined to be most advantageous option for this study Because participants had opted-in to the panel for the purpose of completing surveys, the response rate was expected to be higher than using an e-mail list generated by a marketing company. While respondents on such lists may have opted in they are generally interested in promotional offers, rather than completing surveys for researchers All respondents were exposed to the same set of stimuli (two examples per format) and asked to respond to the perceptual and attitudinal measures with their prior experience with each format in mind. Respondents were also instructed to rate the ad on the basis of format and not on their feelings toward the brand, product, or service featured in the ads. In addition the online ads chosen as examples were deemed to not be overly entertaining, informative, or annoying in an attempt to control the executional differences as m11ch as possible (so that the format differences would not be overshadowed). Ftrrthennore, in an attempt to control somewhat for brand attitudes, the advertised products or services did not include anything controversial or inappropriate. Still the

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166 possibility remains that respondents answered the survey items based solely on their a ssessments of the sample ads or their preconceived attitudes about the brand, product, or service featured in the ad The survey design was constrained in that the presentation order of the formats could not be rotated. The online survey program did allow for rotation of the ad format perceptions each time they were presented. Possible implications of this survey design are that respondents may have been fatigued toward the end of the survey and did not discriminate as much in responding to survey items. After examining the data in Figure 5-1, respondent fatigue does not appear to be a problem as the last two ad formats presented (floating ads and interstitials) still exhibit a wide range of responses on the perceptions. However the increasing adjusted R 2 's for the regression analyses do suggest that people may have become more cognitively consistent in their reporting of perceptions and attitudes toward the formats. Implications for Online Advertising Theory A major finding of this study is that Web users hold differing attitudes toward the various online advertising formats. Previot1s studies that have asked respondents to indicate their opinion of ''online advertising'' were actually collecting aggregate data on the respondents' assessment of various online advertising formats (see Ducoffe, 1996; see Schlosser, Shavitt, & Kanfer, 1999). Each respondent is likely to consider a unique set of online advertising formats and to weight formats differently (whereby the least liked formats might be weighted heavier than the most liked fortnats) when evaluating attitude toward online advertising. Furthermore, respondents may perceive ''online advertising'' to represent the institution of online advertising, as opposed to the instrument, a distinction

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167 used by Sandage and Leckenby (1980). Researchers need to be aware of this variability in attitude when studying attitudes toward online advertising. Implications for Online Advertising Industry The research also bas implications for advertisers and graphic designers who are developing new formats of advertising or considering the use of a current format of advertising. A new for1nat or specific ad can be tested using the perceptual and attitudinal measures developed in this study. This study also has implications for the use of current fonnats of online advertising. For the more annoying formats (e g., pop-ups, floating ads, and interstitials), familiarity with the format further lowered attitude toward that format. People may have a certain tolerance level for these formats and attitudes may decline after that point is reached. Consumers have likely reached tl1at point with pop-up ads and advertisers are advised to avoid this format. Because consumers have more positive attitudes toward formats they have previously clicked, advertisers should employ techniques to tempt the consumer to click through. Offering something in exchange for the clickthrough, such as a contest entry, is one method advertisers currently employ. Advertisers sl1ould also consider the goals of their campaigns and select the format that best matches their goals. This study demonstrated that people are predisposed to thinking about for1nats in partict1lar ways. For example, users believe that banners, large rectangles, and skyscrapers are the most infonnative of the six formats tested. Campaigns that require informing consumers should select one of these fonnats or a similar format. The most entertaining fonnats are floating ads and interstitials and these formats should serve to capture tl1e attention of users. Pop-ups, floating ads, and interstitials are the most

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168 annoying for1nats. Because floating ads and interstitials are both annoying and ente11aining, they should be used with care As mentioned above, advertisers should discontinue the use of pop-ups as they are annoying and neither entertaining nor informative. Future Research This study could be extended to better understand what specific characteristics contribute to perceptions of an online advertisement as informative, entertaining, and annoying. This task is complicated by the prospect that what makes an online ad entertaining might be the very thing that makes it annoying. Separating the three perceptions and focusing on the manipulation of just one perception might relieve the analysis of multicollinearity issues Another avenue of research would be to determine how much tolerance consumers have for annoying, entertaining, and informative ads. Furthermore, these attributes could be manipulated to determine the stability of the attitude toward the for1nat measure. Perceptions of the content of certain ad formats may also play an important role in determining attitude toward the format and is worthy of attention in future studies. The measurement scales developed for this study can be used to track attitudes and perceptions about online ad formats over time. Two questions that could be answered with these longitudinal data are how attitudes change as formats evolve and as consumers become more familiar with online ads. Future research could also relate attitude toward the fo11nat to the effectiveness of the ad, a relationship that has been noted in numerot1s trade publication articles, but not forrnally tested. Although not a key objective of this study, the relationship between familiarity with the format and attitude toward the format was examined. No consistent direction of the

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169 relationship could be confll1l1ed. Future research could study this relationship with more prec1s1on.

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CHAPTER6 IMPLICATIONS Introduction The n1edia provide the ideal public space for advertising. Television, radio, newspaper, and magazines allow advertisers access to a mass audience and the means for transmitting a message to this audience. In recent years, a mass audience has found its way to the World Wide Web. Advertising has both followed and spurred this growth by providing and supporting content that attracted consumers. Online advertising will evolve. Online advertising has already evolved in a short period of time. While these changes can be attributed to several factors, such as the sagging economy and the desperation of Web publishers to attract advertising revenue, consumer attitudes and behaviors have also played an important role in shaping this industry Consumers are voicing their concerns about the pervasiveness of online advertising and publishers are responding by giving users more choice. WeatherBug.com is an exan1ple of a content provider that charges consttmers for advertising-free daily weather repo1ts. Free content is available for those consumers who allow the sponsor of their choice to appear on the site (Atkinson, 2003). Other sites have decided to rely less on ad formats that solicit negative reactions from users, namely pop-up ads. AOL and iVillage.com both annou11ced in 2002 that they would no longer accept pop-up ads from advertisers (Elkin, 2002a). A survey condt1cted by iVillage found that their users described pop-up ads as the most frustrating aspect of 170

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171 the Web. AOL cited problem s with the s low-down in se rvice caused by the ads for the high percentag e of their 3 4 million customers with dial-up se rvice (Elkin, 2002a). 1 Other portal s have reali ze d the importance of keeping their user s happ y For example, Excite@ ho1ne monitor s it s '' crank rat e," which is the number of u se r complaints about online advertising ( Han se ll 200 1 ). Intern e t se rvice provider Eart lllink ha s never allowed pop-up ad s and even offe r s free pop-up blocking so ftware for the ads that may appear when s ub s criber s are visiting o th e r s ite s ( Kopyto ff, 2002). As state d cleverly in an Earthlink ad: '' It took AOL 8.0 tri es to figure out p eo ple don t like pop-up ads. Eart hlink knew all along '' ( Kopytoff 2002). The banner ad is also becomin g de-empha size d as larger format s come into favor. The combination of the abysmally l ow clickthrough rate s of banner s and the r ecogni t ion of banner ads as a branding vehicle may have contributed to this trend toward lar ge r formats. Larger ad formats n1ay achieve hi g her clickthrough rate s and enhanced branding effects. The recommendation b y the JAB for a ''U niver s al Ad P ac kage '' of four o nline advertising format s to be offered b y all Web s ites al so demon s trate s the lack of emphasis on the bann e r ad (Elkin, 2002d). The '' much-maligned '' 468 x 60 pixel banner failed to make the IAB cut in favor of a leaderboard (a g iant banner) a s k ysc raper and two rectangular formats. The se examples provide evidence for the role of consumers in s haping the future of online adv e rti s ing and demon s trate actions by publi s her s and industry groups that see m t o recognize the importance of consumer attitudes toward format s and online advertising in 1 Users may stil l see p opup s o n the AOL a nd iV ill age s it es (Ko p y toff, 2002). AOL does n ot se ll pop-ups to third parti es, but can u se in-h o u se pop-up ads. iV illa ge co ntinue s t o use pop-up s for in-h ouse s ur veys a nd ma gaz ine s u bscr ipti o n s. The s it e also a llo ws pop-unders

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172 general. What was lacking until now is a quantification of the relationship between attitude toward online ad formats and attitude toward the ad The relationship between attitude toward the format and additional variables in the advertising hierarchy-of-effect s i s an area for future re se arch. While this s tudy focused on six ctrrrent formats of online advertising-banners, pop-t1p ad s, skyscrapers, large rectangle s, floating ads, and inter s titials the purpose was not only to determine attitudes toward these specific formats, but also to understand how perceptions about formats play a role in forming attitudes about those for1nats attitudes that in turn influence Aad Current formats may evolve or fall out of favor and new formats may emerge, but the relationships determined by this study shou l d endure. Re s ult s Overview This research introduced a new construct-attitude toward online advertising format-and demonstrated it s relevance in determining attitude toward the ad. Thus, th e results support the need for using a modified A ad model (MacKenzie & Lutz 1989) when inve s tigating online advertising effects. Identifying the specific perceptions of online advertising that may raise or lower attitudes toward an online advertising format was the purpose of Study 1. Study 2 developed and tested a model of online advertising attitudes that specified the antecedent s of attitudes toward online advert i sing formats and the effect of attitude toward online ad formats on attitude toward the ad. Finally, Study 3 collected descriptive data on attitudes toward different online ad formats In Study 1 depth interviews with experienced Web surfers and online advertising experts identified 15 perceptions of online advertising forrnats. The interview s also

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173 determined six online advertising formats worthy of future study including banners pop up ads, skyscrapers, large rectangles, floating ads, and interstitials. A survey with a student sample was used in Study 2 to test a portion of the modified attitude-toward-the-ad model to determine the influence of attitude toward the format on Aad in an online context and to understand the factors that influence attitude toward the online ad format. The primary determinant of attitude toward the online ad format was hypothesized to be ad format perceptions, such as the perceived information and entertainment provided by the ad format. \ttitude toward the Internet, attitude toward online advertising, and attitude toward the Web site in which the ad appeared were also examined for correlations with attitude toward the online ad format. The hypothesis that online ad perceptions are related to attitude toward the f orn1at was supported for all six online ad formats tested in Study 2. The formats differed, however, in terms of the specific perceptions that were significantly correlated with attitude toward each format. The other hypothesized predictors of attitude toward the online ad format were either found to be significantly correlated for only certain formats or not significantly correlated. While attitude toward online advertising and attitude toward the site were significantly related to attitude toward the format for just one format each, attitude toward the Internet was not signifii::antly related to attitude toward any format. Another key relationship tested in the model was that between the independent variables of attitude toward the online ad format and attitude toward online advertising and the dependent variable of attitude toward the ad. The regression equation revealed that while attitude toward online ad fortnat was a significant predictor of Aad, attitude

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174 toward online advertising was not. The influence of A ro rm a t on Aad is particularly important given that A a d is a documented precursor of brand attitude, brand choice and purchase intention s (Gardner, 1985; Ho1ner 1990; MacKenzie & Lutz, 1989 ; MacKenzie, Lutz, & Belch 1986; Miniard, Bhatla & Rose, 1990; Mitchell & Olson 1981 ). Study 3 produced descriptive data on Web user attitudes toward variou s online advertising formats using a nationwide survey of adults. Study 3 also determined how each format rated on the perceptual dimen s ions and te s ted the ability of perceptions to predict attitude toward online ad fortnats. The data supported the three hypotheses of this study. Web users possess significantly different attitudes across formats. Users also hold a varied combination of perceptions about each format. Furthermore, tl1e three perceptions of entertainment annoyance and information have a significant impact on attitude toward the online ad format. Future Re se arch Future re se arch could manipulate the entertainment, annoyance and information attributes in stimulus ads to deterrnine whether these manipulations i1rlluence consumers attitudes toward an online ad format For example, manipulating the va1iable of annoyance might involve adjusting the length of time an ad is presented or the u se of so und or animation. Information could be manipulated by increasing or reducing the amount of copy. Entertainment could be manipulated by using humor or games. Future re se arch could determine how the attitude toward the ad impacts brand attitude and consumer behavior in an online context. Attitude toward the online ad format

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175 could also be examined within the entire Aad model, rather than using a limited number of variables from the model as was done in this study. Other important formats that were not addressed in this stt1dy include e-mail marketing, st 1rr ound sessions, and s ponsor ships. E-mail is expected to grow to a $7 .3 billion market in 2003, up from $164 million in 1999 (Pastore, 2000). The innovative surround sessions u sed by the New York Times Digital, which highlight only one advertise r during a user's visit, would be another interesting format in future studies. The significant contribution of sponsorship dollars to the total online advertising revenue suggests the importance of this format These formats are complicated by a number of different variables and likely deserve individual studies. Another interesting area for future r esearch would be a tracking study of attitudes toward online advertising over time. Will consumers become more tolerant of online advertising and accept it as they do co1nmercial breaks during television programs? Buchwalter and Martin addressed this issue: Despite their intrusiveness, there is some thing to be sa id about ha ving an ad that gets right in the user's face. Surfers may co1nplain, but TV viewers over the yea r s have become used to commercials that interrupt content for about two minutes during their favorite shows. (2003, p. 32) Exploring whether surfing the Internet is such an inherently different experience that it precludes the consumer from accepting such intrusions would be a related re search question. Additional research could explore l1ow online advertising fits into the lives of different constuner segments. A case study of consumers could focus on understandi11g how people rea ct and respond to online adve11ising under different conditions. Paralleling the rise of advertising on the Internet Americans have witnessed advertising in other media moving outside the constraints of a commercial break or the

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176 edges of the newspaper. Many television stations now have the technology to produce an advertising crawl along the bottom of the sc reen during program s. Promotional ads pop up in the corners of the screen to highlight an upcoming show. Graphics-over-programs resemble online banner ads placed at the bottom of the television screen. Research ha s yet to be conducted to s tudy the impact of the se new formats of television advertising on viewer attitudes. Conclusion The future of the online advertising industry i s promising After over two years of declining online advertising revenue s, the fourth quarter of 2002 showed the first consecutive quarterly increa se ( IAB 2003). A 2001 s tudy by Nielsen//NetRatings reported that online advertising spe nding by traditional advertisers surpassed spending by dot-corns for the fir s t time (Saunders, 2001a). Furthermore, a number of the top ten cross media advertisers increased their online exposure in 2002, namely DaimlerChry s ler Verizon Communications, John son & John so n Ford Motor Company, Walt Di s ne y, and AOL Time Warner (Martin & Ryan 2003). The 20% U.S. broadband penetration makes more rich media technologie s feasible for advertisers (Patsuris, 2003). The promi se of the online advertising industry means re se arch in this field is extremely beneficial and u sefu l to advertisers and Web publishers. Furthermore, if research studies focus on understanding consun1er attitudes toward online advertising, the results may shape the futm e of this industry for the benefit of consumers.

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APPENDIX A INTERVIEW GUIDE FOR ONLINE ADVERTISING EXPERTS Screener Introduction My name is Kelli Burns and I am a doctoral student at the University of Florida working on a dissertation on the topic of online advertising. I located yotrr name ( cite source) and would very much appreciate your assistance with some preliminary work I am doing. I have a couple of questions to ask you to find out if you are the right person for me to talk to and if not, perhaps you will point me in the right direction. Screening Que st ions Do you work directly with clients servicing their online advertising needs ? Yes [ASK CLIENT-RELATED QUESTIONS IN INTERVIEW] No [DO NOT ASK CLIENT-RELATED QUESTIONS] Do you consider yourself to be knowledgeable about current and emerging formats of online advertising ? Yes [CONTINUE] D No [SAY: ''Would you provide me with the name of a person in your organization who works directly with clients and is knowledgeable about current and emerging formats of online advertising?''] Good. I would very much like to set up an appointment to talk about online advertising. In the meantime, I need to send you an infotrned consent form. You do not need to sign this but just plea se read it before our interview. Informed Cc11sent Protocol title. Attitude Toward the Online Advertising Format: A Re-examination of the Attitude Toward the Ad Model in an Online Advertising Context 177

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178 Ple ase read tllis consent document carefully before you decide to parti ci pate in this study. This s tud y i s being conducted by Kelli Burns graduate s tudent at the Univers i ty of Florida, and supervised b y Dr. Richard Lutz, professor at the University of Florida. Purpo se of the research stu dy This s tudy in vo lves research to under s tand th e forn1at s of o nline advertising that are c urrently popular with yo u and/or your clients th e formats that ma y b eco me m o re important in the future and the c riteria yo u and your clients u se to differentiate among formats. What you will be a s ked to do in the stu dy. If you agree t o participate I will be asking you to answer a numb e r of que stio n s about online adverti s ing Time required 20 minute s Risks and benefits. This s tudy in vo l ves no anticipated ri s k s or potential benefits to you. Compensation. You will not be compensated for your participation but you may reque s t a copy of the results from thi s phase of my r esea rch Confidentiality. Your identity will be kept confidential to the extent provid ed b y law. Your name will not be t1 se d in any report Voluntar y participation Your participatiou in thi s s tudy i s completely voluntary. There is no penalty for not participatin g. Right to withdraw from the study. You have the rigl1t to withdraw from the s tud y at anytime without consequence. Whom t o contact i f you have que s tion s about the s tudy Kelli Burn s, Graduate Stt1dent College of Journali s m and Communications, University of Florida 408 Fellers Lane, Smyrna TN 37167, (6 15 ) 223-9043, ksburns71@hotmail.com, Richard J Lutz,

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179 Ph.D., Warrington Co ll ege of Business, University of Florida, P.O. Box 115515 Gainesville, FL 32611-5515 (352) 392-4646, lutz @ dale.cba.ufl.edu Whom to contact about your rights as a res earch participant in the study. UFIRB Office Box 112250 University of Florida, Gai11esville FL 32611-2250, (352) 392-043 3 Your completio11 of the telephone s urvey indicates your voluntary consent to participate. Interview Guide Name ______________________ Affiliation ______________________ Phone ________________ Email ________ Thank you for agreeing to this interview. I l1ave a number of questions to ask you about online advertising. 4 What is your opinion of online advertisiI1g in general? (i.e. effectiveness consumer reaction s to it ) 5. The rest of this survey focuses on online advertising formats. It would be helpful at this point to list some of those formats. You may want to write these down s o that you can easily refer to them. 6. What is your opinion of or reaction to each of these online advertising formats ? 7. [FOR RESPONDENTS WHO WORK WITH CLIENTS] What forrnats of online adverti s ing are your clients interested in ? Are there any formats they are steering away from ? Why ? 8. [FOR RESPONDENTS WHO WORK WITH CLIENTS] What formats of online advertising are you encouraging your clients to use? What formats do you sugge s t they should stay away from? Why? 9. Which online ad forrnats do you think are particularly important to include in a study of consumer attitudes toward different f ortnats? 10. What online advertising formats do we know the least about, and we should know more about ? 11. What current online advertis in g fonnats do you think will become more important in the future ? 12. What online adverti s ing format s do you think wi ll emerge in the future ?

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180 13. Let 's go back to the current format s yo u previously listed What current online advertising formats would yo u say are most similar to one another? Group 1: Group 2: Group 3: 14. How would you describe the feature s or dimen s ions of the frr s t group of online ad for1r1ats that distingui s h it from other groups? 15 How would you describe the feature s or dimen s ions of the second group of online ad formats that di s tingt1i s h it from other groups? 16. How would you describe the features or dimensions of the third group of online ad formats that distinguish it from other groups? 17. What knowledge about online ad formats do you think would be particularly useful to the online advertising industry ? That concludes our interview. Thank you for time and have a nice day

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APPENDIXB INTERVIEW GUIDE FOR EXPERIENCED WEB SURFERS Screener Thank you for your i11terest in participating in this research study. Before we set up an interview I just need to ask you a few questions to make sure you qualify to participate in this study. Not including reading or writing emails, how many hours per week would you say you spend surfing the Internet? Less than 3 [TERMINATE] 3 or more [CONTINUE] Name up to three Web sites that you have visited recently. Name up to three Web sites from which you have made an online purchase Name up to three formats of online advertising you have seen, or if you don't know the exact name of the format of advertising, describe what it looks like. [TERMINATE IF RESPONDENT CANNOT NAME OR DESCRIBE AT LEAST THREE FORMATS OF ONLINE ADVERTISING.] You have qualified to participate in this study. Let's set up a time and place to meet for the interview, which will last about an hour. In return for your time, you will be paid $25. 181

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182 Infortned C011sent Protocol title. Attitude Toward the Online Advertising Format: A Re-examination of the Attitude Toward the Ad Model in an Online Advertising Context Please read this consent document carefully before you decide to participate in this study. This study is being conducted by Kelli Burns, graduate student at the University of Florida, and supervised by Dr Richard Lutz, professor at the University of Florida. Purpose of the research study. This study involves research to understand your opinions about online advertising, different formats of online advertising, and advertisers and Web sites that use certain types of online advertising. What you will be asked to do in the study. If you agree to participate I will be asking you to answer a number of questions about online advertising I will also be using a laptop computer to illL1strate these various types. For a couple of questions I will ask you to write your answers. Time required. One hour Risks / benefits. This study involves no anticipated risks or potential benefits to you. Compensation. $25 cash payment Confidentiality. Your identity will be kept confidential to the extent provided by law. Your name will not be used in any repo1i. Voluntary participation. Your participation in this study is completely voluntary. There is no penalty for not participating. Right to withdraw from the study. You have the right to withdraw from the study at anytime without consequence. Whom to contact if you have questions about the study. Kelli Bums, Graduate Student, College of Journalism and Co1nmunications, University of Florida, 408 Fellers

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183 Lane, Smyina, TN 37167, (615) 223-9043 ksbw11s71 @ hotmail.com, Richard J. Lutz, Ph.D., Warrington College of Business, University of Florida P.O Box 115515 Gainesville, FL 32611-5515, (352) 392-4646, lutz @ dale.cba.ufl.edu Whom to contact about your rights as a research participa11.t in the study. UFIRB Office, Box 112250, University of Florida, Gainesville, FL 32611-2250 (352) 392-0433 Agreement. I have read the procedure described above. I volUI1tarily agree to participate in the procedure and I have received a copy of this description. Participant: _______________ Date: _______ Principal Investigator: __________ Date: _______ Interview Guide Introductory Questions The purpose of this interview is to learn what and how you think about online advertising. Let me start out by asking: 1. What words f1rst come to mind when I say ''online advertising ? '' 2 How many different fonnats of online advertising can you name or describe? 3 Which of the following fo1mats of on line advertising have you ever noticed ? (Show respondents examples of online ad formats ) 4. Considering all these forn1ats of ads, what is your general opinion of online advertising? 5. What formats of online advertising do you like most? Why? What formats of online advertising do you like least ? Why? Consider one ad format you like and one you dislike and describe the differences between them. (For the next section, choose up to five for1nats of ads that the respondent is familiar with and ask the following questions for each format of ad.)

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184 Ad Format I Let's talk specifically about (AD FORMAT 1). I will show you some examples of (AD FORMAT I). Your task is simply to exami11e the ad in front of yo11 and form an evaluation of it As you look at the advertiseme11t, please remember that I am interested in your evaluation this format of ad, rather than the product being advertised. (Respondent will look at three ads of this forrnat for two minutes. After two minutes, respondent will be given a forrn to record thought-listing responses and will s e e the following instructions.) 6. In the space provided please list all the thoughts, reactions, and ideas that went through your mind while you were looking at the advertisements Please record any thoughts, no matter how simple, complex, relevant, ')r irrelevant they may seem to you. Record everything that you thought of. There are no right or wrong answers. Do not worry about grammar, spelling, or punctuation. Remember, list all thoughts that occurred to you during the time you were looking at the advertisements. 7. What do you like about (AD FORMAT l)? 8. What do you dislike about (AD FORMAT I)? 9. What do you think about advertisers who use (AD FORMAT 1)? If you really liked the advertiser, would your opinion of them change in any way if they used this for1nat of ad? If you saw this format of ad, but weren't familiar with the advertiser, what kind of opinion would you have of that advertiser ? 10. What do you think about Web sites that use (AD FORMAT 1)? If you really liked the Web site, would your opinion change if they used this fortnat of ad? If you saw this format of ad, but weren't familiar with the Web site, what kind of opinion would you have of that Web site? Ad Fo11nat 2 Let's talk specifically about (AD FORM.AT 2). I will show you some examples of (AD FORMAT 2). Your task is simply to examine the ad in front of you and form an evaluation of it As you look at the advertisemer1t, please remember that I am interested in your evaluation this format of ad, rather than the product being advertised.

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185 (Respondent will look at three ads of tl1is format for two minutes. After two minutes, re spondent will be given a forrn to record thought-listing responses and will see the following instructions.) 11. In the space provided please list all the thoughts, reactions and ideas that went through your mind while you were looking at the advertisements. Please record any thoughts, no matter how simple, complex, relevant, or irrelevant they may seem to you. Record everything that you thought of. There are no right or wrong answers. Do not worry about grammar, spelling, or punctuation Remember, li st all thoughts that occurred to you during the time you were lookin g at the advertisements. 12. What do you like about (AD FORMAT 2)? 13. What do you dislike about (AD FORMAT 2)? 14. What do you think about advertisers who use (AD FORMAT 2)? If yo u really liked the advertiser, would your opinion of them change in any way if the y used this fonnat of ad? If you saw this fonnat of ad, bt1t weren't familiar with the advertiser, what kind of opinion would you have of that advertiser? 15. What do you think abot1t Web sites that use (AD FORMAT 2)? If you r eally liked the Web site, would your opinion change if they used this format of ad? If you saw this format of ad, but weren't familiar with the Web site, what kind of opinion would you have of that Web site? Ad Format 3 Let's talk specifically about (AD FORMAT 3). I will sho,v you some examples of (AD FORMAT 3). Your task is simp ly to examine the ad in front of you and form an evaluation of it As you look at the advertisement, please remember that I am interested in your evaluation this format of ad, rather than the product being advertised. (Respondent will look at three ads of this format for two minutes. After two minutes, r espondent will be given a fo11r1 to record thought-listir1g responses and will see the following instructions.) 16. In the space provided please list all the tl1oughts, reactions, and ideas that went through your mind while you were looking at the advertisements. Please record any thoughts, no matter how simple, complex, relevant, or irrelevant they may

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186 seem to you. Record everything that you thought of. There are no right or wrong answers Do not worry about granunar, spelling, or punctuation Remember list all thoughts that occurred to you during the time you were looking at the advertisements. 17 What do you like about (AD FORMAT 3)? 18. What do you dislike about (AD FORMAT 3)? 19 What do you thi11k about advertisers who u se (AD FORMAT 3)? If you really liked th e advertiser, would your opinion of them change in any way if the y u sed this fo11nat of ad? If you saw this format of ad, but weren't familiar with the advertiser, what kind of opinion wot1ld you have of that advertiser? 20. What do you think about Web sites that use (AD FORMAT 3)? If you really liked the Web site, would your opinion change if they used this format of ad? If you saw this format of ad, but weren't familiar with the Web site, what kind of opinion would you have of that Web site? Ad Format 4 Let's talk specifically about (AD FORMAT 4) I will show you some examples of (AD FORMAT 4). Your task is simply to examine the ad in front of you and form an evaluation of it As you look at the advertisement, please remember that I am interested in your evaluation this forrnat of ad, rather than the product being advertised. (Respondent will look at three ads of this format for two minutes. After two minutes respondent will be given a form to record thought-listing responses and will see the following instructions.) 21. In the space provided please list all the thoughts, reactions and ideas that went through yot1r mind while you were looking at the advertisements. Please r eco rd any thoughts, no matter how simple, complex, relevant, or in levant they may seem to you. Record everything that you thought of There are no right or wrong answers Do not worry about grammar, spelling, or punctuation. Remember list all thoughts that occurred to you during the time you were looking at the advertisements 22. What do you like about (AD FORMAT 4) ? 23. What do you dislike about (AD FORMAT 4)?

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187 24. What do you think about advertisers who use (AD FORMAT 4)? If you really liked th e advertiser, would your opinion of them change in any way if they used this format of ad? If yot1 saw this for1r1at of ad but weren't familiar with the advertiser what kind of opinion would you have of that advertiser? 25. What do you think about Web sites that use (AD FORMAT 4) ? If you really liked the Web site, would your opinion change if they used this forrnat of ad? If you saw this format of ad, but weren't familiar with the Web site, what kind of opinion would you have of that Web site? Ad Format 5 Let's talk specifically about (AD FORMAT 5). I will show you some examples of (AD FORMAT 5). Your task is simply to examine the ad in front of you and form an evaluation of it As you look at the advertisement, please remember that I am interested in your evaluation this fo1mat of ad rather than the product being advertised (Respondent will look at three ads of this format for two minutes. After two minutes respondent will be given a form to record thought-listing responses and will see the following instructions.) 26. In the space provided, please list all the thoughts, reactions, and ideas that went through your mind while you were looking at the advertisements. Please re c ord any thoughts, no matter how simple, complex, relevant, or irrelevant they may seem to you. Record everything that you thought of. There are no right or wrong answers. Do not worry about grammar, spelling, or punctuation. Remember, list all thoughts that occurred to you during the time you were looking at the advertisements. 27. What do you like abot1t (AD FORMAT 5) ? 28. What do you dislike about (AD FORMAT 5)? 29. What do you think about advertisers who use (AD FORMAT 5)? If you really liked the advertiser, would your opinion 0f them change in any way if they used this format of ad ? If you saw this format of ad, but weren't familiar with the advertiser, what kind of opinion would yot1 have of that advertiser? 30. What do you think about Web sites that use (AD FORMAT 5)? If you really liked the Web site, would your opinion change if they used this format of ad? If you saw this format of ad, but weren't familiar with the Web site, what kind of opinion would you have of that Web site?

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188 Comparing F onnats 31. What do you see as the difference between AD FORMAT 1 and AD FORMAT 2? (Select a few combinations of ads for demonstration.) 32 If you were a consultant for a company who wanted to advertise online, which of these five formats of online advertisements would you suggest that they use? Why? Are there any other forrnats of online advertising that you would recommend? Wl1y? 33. List adjectives to describe the onJine advertising you have seen. 34. Are there certain time s when you are more likely to pay attention to ads ? Are there certain Web sites where you are more likely to pay attention to ads? 35. What about online advertising attracts your attention? 36. When you see an online ad, do you ever seek more information about the product or service advertised? What was it about an online ad that motivated you to seek more information? Demographics 3 7. Record gender 38. Record race 39. What is your age? 40. What is yo ur occupation? 41. What is the highest level of education you have completed? 42 Not including e-mail and instant messaging how many hours per week do you spend surfing the Internet? 43 Wllat is the connection speed for your primary computer?

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Introduction APPENDIXC ONLINESURVEYSFORSTUDY2 Version A Welcome to the Online Advertising Survey Conducted by Kelli Burns University of Florida. Thank you for your interest in participating in this research. Your responses are very important so please consider them carefully. This survey will take about 10 minutes to complete. INSTRUCTIONS: Use the Next and Prev buttons at the bottom of the page to move forward or backward in the survey. You can change any of your previous answers by using the Prev button to return to that page. DO NOT USE YOUR BROWSER S FORWARD OR BACK BUTTONS. This survey is best viewed using INTERNET EXPLORER. If you have accessed it using Netscape, please change to Internet Explorer if that browser is available to you. Inf armed Consent Please read this info1med consent document carefully before you decide to participate in this study. This study is being conducted by Kelli Bums graduate student at the University of Florida, and supervised by Dr. Richard Lutz, professor at the University of Florida. Purpose of the research study. Tl1is study involves research to understand attitudes toward online advertising. 189

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190 What you will be asked to do in the study. If you agree to participate you will view Web pages witl1 online advertising. You will respond to questions pertaining to this online advertising by using an online survey. Time required 10 minutes Risks and benefits. Risk is minimal and no deception is involved. The online advertisements you will see are not offensive, threatening, or in poor taste Compensation. You will receive one credit ( out of a total of four possible). Maximum extra credit comprises approximately 1.5% of your final grade. Confidentiality. Your responses will be anonymous Voluntary participation. Participation is strictly vo luntary and you will not have to answer any question you fmd offensive or threatening. There is no penalty for not participating. Right to withdraw from the study. You have the right to withdraw from the study at any time without consequence Whom to contact if you have questions about the study Kelli Burns Graduate Student, College of Journalism and Communications, University of Florida, P.O. Box 16041, Winston-Salem, NC 27115, (615) 579-3663, ksburns71 @ hotmail.com. Richard J. Lut z, Ph.D ., Warrington College of Business, University of Florida, P O Box 115515 Gainesville, FL 32611-5515, (352) 392-4646, lut z@ dale.cba ufl .e du. Whom to contact about your rights as a research participant in the study. UFIRB Office, Box 112250 University of Florida, Gainesville, FL 32611-2250, (352) 392-0433. Clicking through on the NEXT button below indicates your voluntary consent to participate

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191 Extra Credit Please enter the last four digits of your Social Security number to receive extra credit for participating in tllis study __ Please mark the class for whicl1 you will receive extra credit by participating in this study. MAR 3023 (Principles of Marketing) QMB 3250 (Quantitative Methods for Business) Surfing the Web Think for a moment about surfing the Web a11d respond to the following statements : Strongly Agree Neither Disagree Strongly Agree Agree nor Disagree Disagree I feel confident in my ability to surf the Web. Surfing the Web is a good way to spend my ttn1e. I am satisfied with the sites I visit on the Web. Advertising on the Web When you are surfing the Web you are likely to see advertising for an array of products and services. Tlunk about the advertising you see 01tline and respond to the following: Strongly Agree Neither Disagree Strongl y Agree Agree nor Disagree Disagree Advertising on the Web is a good thing My opinion of advertising on the Web is unfavorable.

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192 Strongly Like Neither Dislike Strongly Like Like nor Dislike Dislike Overall, do you like or dislike the advertising you see on the Web? First Online Ad The first ad you will view is for the Gap and will be located at the top of the Web page Spend about one minute on the Web site looking at the ad and considering your opinion of it and then looking at the Web site in which the ad appears After one minute has passed close the browser window and hit the NEXT button to move to the next page. To view the ad, click the link below. If you were not able to view the ad, click here. My overall reaction to the advertisement for the Gap is: [To answer this question, if you agree 100% with the adjective on the left, mark the circl e below it. If you agree 100 3/ o with the adjective on the right, mark the circle below it. If you fall somewhere in between, mark the appropriate circle.] Good 0 0 Unpleasant 0 0 0 0 Favorable 0 0 0 0 0 0 Bad 0 Pleasant 0 Unfavorable 0 The questions on the next two pages ask your opinion of the format of the ad you just saw. The format refers to the way the ad is shaped or delivered not the product or se1-vice advertised in the ad The Gap ad format was a banner ad. A banner ad is a rectangular-shaped ad and is often found at the top of Web page.

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193 To an s wer these questions con s ider the range of banner advertising you see while surfing the Web and not necessarily the banner ad you just saw. If you have never seen a banner ad before, base your assessment on the ad you just saw In general banner ads are: [ROTATED RESPONSES] Strongly Agree Neither Agree Disagree Strongly Agree nor Dis a gree Disagre e Amusing Annoying Attractive Beneficial Different Disruptive Elaborate Entertaining Eye-catching Informative l.Imovative Intrusive Overbearing Sophisticated Useful

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194 Compared to other formats of online advertising how would you describe banner ads ? Liked by me 0 0 0 One of the wor s t 0 0 0 0 0 An excellent format 0 0 0 0 I hate it 0 0 0 0 Disliked by m e 0 One of the best 0 A poor for1nat 0 I love it 0 Think for a moment about the Web site you just visited and respond to the following statements: Strongly Agree Neither Disagree Strongly Agree Agree nor Disagre e Disagree I like this Web site. It is a good Web site It is a nice Web site. How familiar would you say you are with banner advertising? Very familiar (I've seen banner ads a lot.) Somewhat familiar Somewhat unfamiliar Very unfamiliar (I've never seen a banner ad before.) Have you ever clicked throt1gh on a banner ad to get more info1n1ation about the product or service advertised in the banner ad? Yes No How many times have you clicked through on a banner ad in the past 1nonth? None 1-2 3-4 5-6 7 or more

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195 Has a banner ad ever prompted you to later visit the advertised Web site? Yes No Second Online Ad The second ad you will view is for Nikon and will pop-up when you go to th e requested Web page Spend about one minute on the Web site l0oking at the ad and considering your opinion of it and then looking at the Web site in which the ad appears. After one minute has passed, close the browser window (by clicking on the X in the top right comer of the browser) and hit the NEXT button to move to the next page To view the ad, click the link below. PLEASE IGNORE ANY OTHER ADS THAT MAY APPEAR WHEN VIEWING THE PAGE. (You can view the pop-up ad again by hitting the replay button.) If you were not able to view the ad, click here. My overall reaction to the advertisement for Nikon is: [To answer this question, if you agree 100% with the adjective on the left, mark the circle below it. If you agree 1 OO o/ o with the adjective on the right, mark the circle below it. If you fall somewhere in between mark the appropriate circle ] Good 0 0 Unpleasant 0 0 0 0 Favorable 0 0 0 0 0 0 Bad 0 Pleasant 0 Unfavorable 0 The questions on the next two pages ask your opinion of the format of the ad you just saw. The format refers to the way the ad is shaped or delivered not the product or

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196 service advertised in the ad. The Nikon ad for1nat was a pop-up ad. A pop-up ad appears in a separate window when you are on a Web page. To answer these questions, consider the range of pop-up advertising you see whil e surfing the Web and 11ot necessarily the pop-up ad you just saw. If you have never seen a pop-up ad before base your assessment on the Nikon ad you just saw In general, pop-up ads are: [ROT A TED RESPONSES] Strongly Agree Neither Disagree Strongly Agree Agree nor Di sagree Disagree Amusing Annoying Attractive Beneficial Different Disruptive Elaborate Entertaining Eye-catching Informative Innovative Intrusive Overbearing Sophisticated Useful

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197 Compared to other for1nats of online advertising how would you describe pop-up ads? Liked byme 0 0 0 One of the wor s t 0 0 0 0 0 An excellent format 0 0 0 0 I hate it 0 0 0 0 Disliked by me 0 One of tl1e best 0 A poor format 0 I love it 0 Think for a moment about the Web site you just visited and respond to the following statements: Stron g ly Agree Neither Disagree Strongly Agree Agree nor Disa g ree Disagree I like this W eh site. It is a good W eh site. It is a nice W eh site. How familiar would you say you are with pop-up advertising? Very familiar (I ve seen pop-t1p ads a lot.) Somewhat familiar Somewhat unfamiliar Very unfamiliar (I've never seen a pop-up ad before ) Have you ever clicked through on a pop-up ad to get more infonnatio11 about the produ c t or service advertised in the pop-up ad? Yes No How many times have you clicked through 011 a pop-up ad in the past month ? None 1-2 3-4 5-6 7 or more

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198 Has a pop-up ad ever prompted you to later visit the advertised Web site? Yes No Third Online Ad The third and final ad you will view is for Best Buy. You will see this ad along the right hand side of the Web page. Spe11d about one minute on the Web site looking at the ad and considering your opinion of it and then looking at the Web site in which the ad appears. After one minute has passed, close the browser window (by clicking on the X in the top right corner of the browser) and hit the NEXT button to move to the next page To view the ad, click the link below If you were not able to view the ad, click here. My overall reaction to the advertisement for Best Buy is: [To answer this question, if you agree 1003/o with the adjective on the left, mark the circle below it. If you agree 100% with the adjective on the right, mark the circle below it. If you fall somewhere in between, mark the appropriate circle.] Good 0 0 Unpleasant 0 0 0 0 Favorable 0 0 0 0 0 0 Bad 0 Pleasant 0 Unfavorable 0 The questions on the next two pages ask your opinion of the format of the ad you just saw. The for1nat refers to the way the ad is shaped or delivered not the product or service advertised in the ad. The Best Buy ad format was a skysr;raper ad. A skyscrape1 ad is a tall, thin ad that appears along the side of a Web page.

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199 To answer these questions consider the range of skyscraper advertising you see while surfmg the Web and not necessarily the skyscraper ad you just saw. If you have never seen a skyscraper ad before base your assessment on the ad you just saw In general skyscraper ads are : [ROTATED RESPONSES] Strongly Agree Neither Disagree Strongly Agree Agree nor Disagree Disagree Amusing Annoying Attractive Beneficial Different Disruptive Elaborate Entertaining Eye-catching Inforrnative Innovative Intrusive Overbearing Sophisticated Useful

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200 Compared to other formats of online advertising, how would yot1 describe skyscraper s? Liked by me 0 0 0 One of the worst 0 0 0 0 0 An excellent format 0 0 0 0 I hate it 0 0 0 0 Disliked by me 0 One of the be s t 0 A poor for1nat 0 I love it 0 Think for a moment about the Web site you just visited and respond to the following statements: Strongly Agree Neither Disagree Strongly Agre e Agree nor Disagree Disagree I like this Web site. It is a good Web site. It is a nice Web site. How familiar would you say you are with skyscraper advertising? Very familiar (I've seen skyscraper ads a lot.) Somewhat familiar Somewhat unfamiliar Very unfamiliar (I ve never seen a skyscraper ad before.) Have yot1 ever click e d through on a skyscraper ad to get more information about the product or service advertised in the skyscraper ad ? Yes No How many times have you clicked through on a skyscraper ad in the past month ? None 1-2 3-4 5-6 7 or more

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201 Has a skyscraper ad ever prompted you to later visit the advertised Web site? Yes No Demographics Please provide some background information to help categorize your responses. Which of the following best describes your primary connection to the Internet? 28.8 Kbps modem 56 Kbps moden1 ISDN Cable Modem DSL Tl or better Do not know but high speed Do not know Other (please specify Excluding email and instant messaging, how many hours a week do you spend on the Internet? In what year did you start using the Internet on a regular basis? Are you .. ? Male Female In what year were you born? What is your employment status? Employed full time Employed part time Self-employed Not employed Other Have you ever made an online purchase? Yes No How rnany online purchases have you made during the past six months? None 1-2 3-4 5-6 7 or more

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202 Conclusion THANKS! You have reached the end of the survey. I greatly appreciate your time and participation Kelli Burns, University of Florida, ksburns71 @ hotmail.com Please contact me at the above e-mail address if you have any comments or feedback about tlus survey, particularly if the survey malfunctio11ed. Version B Introduction Welcome to the Online Advertising Survey Conducted by Kelli Burns University of Florida Thank you for your interest in participating in this research. Your responses are very important so please consider them carefully. This survey will take about 10 minutes to complete INSTRUCTIONS: Use the Next and Prev buttons at the bottom of the page to move forward or backward in the survey. You can change any of your previous answers by using the Pr ev button to return to that page. DO NOT USE YOUR BROWSER S FORWARD OR BACK BUTTONS. This survey is best viewed using INTERNET EXPLORER. If you have accessed it using Netscape, please change to Internet Explorer if that browser is available to you. Informed Consent Please read this informed consent document carefully before you decide to participate in this study. This study is being conducted by Kel li Burns graduate student at the University of Florida, and supervised by Dr. Ricl1ard Lutz, professor at the University of Florida.

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203 Purpose of the research study. This study involves research to understand attitudes toward online advertising. What you will be asked to do in the study. If you agree to participate, you will view Web pages with online advertising. You will respond to questions pertaining to tlus online advertising by using an online survey. Time required. 10 minutes Risks and benefits. Risk is minimal and no deception is involved. The online advertisements you will see are not offensive, threatening, or in poor taste Compensation. You will receive one credit ( out of a total of four possible). Maximum extra credit comprises approximately 1.5% of your final grade. Confidentiality. Your responses will be anonymous. Voluntary participation. Participation is strictly voluntary, and you will not have to answer any question you find offensive or threatening. There is no penalty for not participating. Right to withdraw from the study. You the right to withdraw from the study at any time without consequence. Whom to contact if you have questions about the study. Kelli Burns, Graduate Student, College of Journalism and Communications, University of Florida, P.O. Box 16041, Winston-Salem, NC 27115, (615) 579-3663, ksbums7l@hotmail.com. Richard J. Lutz, Ph.D., Warrington College of Business, University of F l orida, P.O. Box 115515, Gainesville, FL 32611-5515, (352) 392-4646, lutz @ dale.cba.ufl.edu. Whom to contact about your rights as a research participa..,t in the study. UFIRB Office, Box 112250 University of Florida, Gainesville, FL 32611 2250, (352) 392-0433

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204 Clicking througl1 on the NEXT button bel0w indicates your voluntary con s ent to participate Extra Credit Please enter the last four digits of your Social Security number to receive extra credit for participating in thi s study. __ Please mark the class for which you will receive extra credit by participating in this stL1dy. MAR 3023 (Pri11ciples of Marketing) QMB 3250 (Quantitative Methods for Business) Surfing the Web Think for a moment about surfing the Web and respond to the following statements: Strongly Agree Neither Disagree Strongl y Agree Agree nor Disagree Disagree I feel confident in my ability to surf the Web Surfing the Web i s a good way to spend my tune. I am satisfied with the sites I visit on the Web Advertising on the W eh When you are surfing the Web, you are likely to see advertising for an array of products and services. Think for a moment about the advertising you see on the W e b and respond to the following statements :

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205 Strongly Agree Neither Disagree Strongly Agree Agree nor Disagree Disagree Advertising on the Web is a good thing. My opinion of advertising on the Web is unfavorable. Strongly Lik e Neither Dislike Strongly Like Like nor Dislike Dislike Overall do you like or dislike the advertising you see on the Web? First Online Ad The first ad you will view is for Handspring and will be located in the middle of the Web page wrapped by the text of the article. Spend about one minute on the Web site looking at the ad and considering your opinion of it and then looking at the Web site in which the ad appear s. After one minute has passed close the browser window (by clicking on the X in th e top right comer of the browser) and hit the NEXT button to move to the next page. To view the ad click the link below. SCROLL DOWN SO THAT YOU CAN VIEW THE AD WHILE THE PAGE IS LOADING. If you were not able to view the ad click here.

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206 My overall reaction to the advertisement for Handspring is: [To answer this question, if you agree 100% with the adjective on the left, mark the circle below it If you agree 100% with the adjective on the right, mark the circle below it. If you fall somewhere in between, mark the appropriate circle.] Good 0 0 Unpleasant 0 0 0 0 Favorable 0 0 0 0 0 0 Bad 0 Pleasant 0 Unfavorable 0 The questions on the next two pages ask your opinion of the format of the ad you just saw. The fo1mat refers to the way the ad is shaped or delivered not the product or service advertised in the ad. The Handspring ad format was a large rectangle ad. A large rectangle ad is often found in the middle of Web page wrapped by text. As the name implies, the ad is both large and rectangle in shape. To answer these questions, consider the range of large rectangle advertising you see while surfing the Web and not necessarily the large rectangle ad you just saw. If you are unfamiliar with large rectangles, base your assessment on the ad you just saw.

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207 In general, large rectangle ads are: [ROT A TED RESPONSES] Strongly Agree Neither Disagree Strongly Agree Agree nor Disagree Disagree Amusing Annoying Attractive Beneficial Different Di s ruptive Elaborate Entertaining Eye-catchi11g Informative Innovative Intrusive Overbearing Sophisticated Useful Compared to other forrnats of online ads, how would you describe large rectangles? Liked byme 0 0 0 One of the worst 0 0 0 0 0 An excellent fonriat 0 0 0 0 Disliked by me 0 One of the best 0 A poor fo1 rnat 0

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I hate it 0 0 0 0 I love it 0 208 Think for a moment about the Web site you just visited and respond to the following statements: Strongly Agree Neither Disagree Strongly Agree Agree nor Disagree Disagree I like this Web s ite. It is a good Web site. It i s a nice Web site. How familiar would you say you are with large rectangle ads ? Very familiar (I've seen large rectangle ads a lot.) Somewhat familiar Somewhat unfamiliar D Very unfamiliar (I've never seen a large rectangle ad before.) Have you ever clicked through on a large rectangle ad to get more information about the product or s ervi ce advertised in the ad? Yes No How many times have you clicked throu g h on a large rectangle ad in the past month ? None 1-2 3-4 5-6 7 or more Has a large rectangle ad ever prompted you to later visit the advertised Web site? Yes No Second Online Ad The second ad you will view is for Saturn. This ad will "drive" across the page a few moments after you go to the requested Web page. Spend about one minute on the

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209 Web site looking at the ad and considering your opinion of it and then looking at the Web site in which the ad appears. After one minute has passed, close the browser window (by clicking on the X in the top right comer of the browser) and hit the NEXT button to move to the next page. To view tl1e ad, click the link below YOU MAY NEED TO MAXIlv1IZE YOUR BROWSER TO FULL-SCREEN TO COMPLETELY SEE THE AD D If you were not able to view the ad, click here. My overall reaction to the advertisement for Saturn is : [To answer this question, if you agree 100 % with the adjective on the left mark the circle below it. If you agree 100 % with the adjective on the right, mark the circle below it. If you fall somewhere in between, mark the appropriate circle.] Good 0 0 0 Unpleasant 0 0 0 Favorable 0 0 0 0 0 0 Bad 0 Pleasant 0 Unfavorable 0 The questions on the next two pages ask your opinion of tbe format of the ad you just saw. The forrnat refers to the way the ad is shaped or delivered not the product or service advertised in the ad. The Satt tm ad format was a floating ad. A floating ad moves across the page when you are on a Web page. To answer these questions consider the range of floating ads you see while surfing the Web and not necessari l y the floating ad yot1 just saw If you have never seen a floating ad before base your assessment on the Saturn ad you just saw.

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210 In general floating ads are : [ROTATED RESPONSES] Strongly Agree N e ither Disagree Strongly Agree Agree nor Disagree Disagre e Amu s ing Annoying Attractive Beneficial Different Disruptive Elaborate Entertaining Eye-catching Infortnative Innovative Intrusive Overbearing Sophisticated Useful Compared to other formats of online advertising how would you describe floating ad s? Liked bym e 0 0 0 One of the worst 0 0 0 0 0 An excellent format 0 0 0 0 Disliked b y me 0 One of the best 0 A poor format 0

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I hate it 0 0 0 0 I love it 0 211 Think for a moment about the Web s i te you just visited and respond to the following statements : Strongly Agree Neither Disagree Strongly Agree Agree nor Disagree Disagree I like this Web site It is a good Web site. It is a nice Web site. How familiar would you say you are with floating ads? Very familiar (I ve seen floating ads a lot ) Somewhat familiar Somewhat unfamiliar Very unfamiliar (I'v e never seen a floatin g ad before.) Have you ever clicked through on a floating ad to get more information about the product or service advertised in the floating ad ? Yes No How many times have you clicked throt1gh on a floating ad in the past month? None 1-2 3-4 5-6 7 or more Has a floating ad ever prompted you to later visit the advertised Web site? Ye s No Third Online Ad The third and fmal ad you will view is for Travelocity. This ad will appear before you arrive at the r e quested Web pa g e Watch the ad as the requested page loads and consider your opinion of it Then sp e nd about one minute looking at the Web site

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212 After one minute has passed, close the browser window (by clicking on the X in the top right comer of the browser) and hit the NEXT button to move to the next page. To view the ad, click the link below. PLEASE IGNORE ANY OTHER ADS THAT MAY APPEAR WHEN VIEWING THE PAGE. D If you were not able to view the ad click here. My overall reaction to the advertisement for Travelocity is: Good 0 0 Unpleasant 0 0 0 0 Favorable 0 0 0 0 0 0 Bad 0 Pleasant 0 Unfavorable 0 The questions on the next two pages ask your opinion of the format of the ad you just saw. The format refers to the way the ad is shaped or delivered not the product or service advertised in the ad. The Travelocity ad format was an interstitial ad. An interstitial ad appears when you are moving between two Web pages. When the requested page has loaded, the interstitial ad goes away. To answer these questions, consider the range of interstitial ads you see while surfing the Web and not necessarily the interstitial ad you just saw. If you have never seen an interstitial ad before, base your assessment on the ad you just saw.

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213 In general, interstitial ads are: [ROTATED RESPONSES] Strongly Agree Neitl1er Disagree Strongly Agree Agree nor Disagree Disagree Amttsing Annoying Attractive Beneficial Different Disruptive Elaborate Entertaining Eye-catching Informative Innovative Intrusive Overheating Sophisticated Usefu l Compared to other formats of online advertising, how would you describe interstitial ads ? Liked byme 0 0 0 One of the wor s t 0 0 0 0 0 An excellent forrnat 0 0 0 0 Disliked by me 0 One of the best 0 A poor format 0

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I hate it 0 0 0 0 I love it 0 214 Think for a moment about the Web site yot1 just visited and respond to the following statements : Strongly Agree Neither Disagree Strongly Agree Agree nor Disagree Disagree I like this Web site It is a good Web site It is a nice Web site How familiar would you say yot1 are with interstitial ads ? Very familiar (I ve seen interstitial ads a lot.) Somewhat familiar Somewhat unfamiliar Very unfamiliar (I've never seen an interstitial ad before ) Have you ever clicked through on an interstitial ad to get more information about the product or service advertised in the ad? Yes No How many times have you clicked through on an interstitial ad in the past month? None 1-2 3-4 5-6 7 or more Has an interstitial ad ever prompted you to later visit the advertised Web site ? Ye s No

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215 Demographics Please provide some backgrotmd inforrnation to help categorize your responses. Which of the following best describes your primary connection to the Internet ? 28 8 Kbps modem 56 Kbps modem ISDN Cable Modem DSL Tl or better Do not know but high speed Do not know Other (please s pecify Excluding email and instant messaging, how many hours a week do you spend on the Internet? In what year did you start using the Internet on a regular basis ? Are you ... ? Male Female In what year were you born? What is your employment status? Employed full tim e Employed part time Self-employed Not employed Other Have you ever made an online purchase? Yes No How many online purchases have you made dt1ring the past six mo11ths? None 1-2 3-4 5-6 7 or more

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216 Conclusion THANKS! You have reached the end of tlie survey. I greatly appreciate your tlme and participation. Kelli Burns, University of Florida, ksbums71@hotmail.com. Please contact me at the above e-mail address if you have any comments or feedback about this survey particularly if the survey malfunctioned.

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APPENDIXD ONLINE SURVEY FOR STUDY 3 Invitation It flashes blinks, pops, hides zooms, and bu zzes. What is it? Internet advertising. You may like it hate it, not notice it or always look at it. Whatever you think about it your valuable input is needed. Here is your chan~e to voice your opinion about Internet advertising! This research is being conducted by a doctoral student working on the final stages of her dissertation. I hope that you will consider helping her out with a questionnaire on the topic of Internet advertising You will see various forrnats of Internet advertising and be asked to comment on them. I think you will enjoy participating in this study. The questionnaire only takes about 15 minutes to complete. Please access it using INTERNET EXPLORER. Please click here to get started: http: // www.surveymonkey.com If you encounter any technical difficulties while comp l eting this survey, send an email to ufl2003 @ hotmail.com We look forward to hearing your opinio11s. Survey Introduction Welcome to the Online Advertising Survey Thank you for your interest in participating in this re se arch 217

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218 INSTRUCTIONS : 1 Use the Next and Prev buttons at the bottom of the page to move forward or backward in the survey. 2. You can change any of yotrr previous answers by t1sing the Prev button to rettrm to that page. 3. This survey is be st viewed using INTERNET EXPLORER. If you have accessed it using Netscape, please change to Internet Exp l orer if that browser is available to you. 4 Please click on this link to read the Informed Consent Document before you decide to participate in tl1is study. This will open in a separate browser window. Close the window by clicking on DONE 5. If you must exit the survey, you can return to the place you left off by clicking through on the link again. Clicking NEXT indicates your acceptance and understanding of the Informed Consent Document. Inf orrned Consent Please read this informed cor1sent document carefully before you decide to participate in this study. This study is being conducted by Kelli Burns, graduate student at the University of Florida, and supervised by Dr. Richard Lutz, marketing professor at the University of Florida, and Dr. John Sutherland advertising professor at the University of Florida. Purpose of the research study. This study involves research to understand attitudes toward online advertising. What you will be asked to do in the study. If you agree to participate, you will view Web pages with online advertising You will respond to questions pertaining to this online advertising by using an online survey. Time required 15-20 minutes

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219 Risks and benefits. Risk is minimal and no deception is involved The online advertiseme11ts you will see are not offensive, threatening, or in poor taste. Compensation. No compensation will be provided for participating in this study. Confidentiality Your responses will be anonymous and not associated with the user ID provided Voluntary participation. Participation is strictly voluntary, and you will not have to answer any question you find offensive or threatening. There is no penalty for not participating. Right to withdraw from the study You have the right to withdraw from the study at any time without consequence Whom to contact if you have questions about the study Kelli Bums, Graduate Student, College of Journalism and Conununications, University of Florida P.O. Box 16041 Winston-Salem, NC 27115 ufl2003 @ hotmail com. Richard J. Lutz Ph D ., Warrington College of Business University of Florida, P.O. Box 115515, Gainesville FL 32611-5515 Whom to contact about your rights as a research participant in the study UFIRB Office Box 112250 University of Florida, Gainesville FL 326 112250, (352) 392-0433. Esearch.com ID Please enter your esearch.com user ID \Vhich can be found at the top of your mail invitation. --Adverti s ing on the Web When you are surfing the Web you are likely to see advertising for an array of products and services Think for a moment about the advertising you see on the Web and respond to the following statements:

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220 Strongly Agree Neither Disagree Strongly Agree Agree nor Disagree Disagree Advertising on the Web is a good thing My opinion of advertising on the Web is unfavorable Strongly Like Neither Dislike Strongly Like Like nor Dislike Dislike Overall, do you like or dislike the advertising you see on the W eh? Format Introduction The next part of this survey will ask your opinion of various formats of on line advertising. The format of an online ad refers to the way the ad appears on the Web pag enot the product or service advertised. As you proceed tlrrough the survey, you will view examples of six formats of online advertising and then will be asked your opinion of each format These formats include banner ads pop-up ads, skyscrapers (vertical banners) large rectangle ads floating ads (like animation over your screen) and interstitials (which appear when moving between two pages). Click the NEXT button to see the first online ad format.

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221 First Online Ad Format The first online ad format is a BANNER AD. These ads are often located at the top of the Web page. Spend about one minute looking at the ads and considering your opinion of them. Imagine that you ha ve encountered tl1ese ads while surfing the Web. After you have looked at the first ad, close the browser window and then look at th e second ad. After looking at the second ad, close the browser window. Then hit the NEXT button to move to the next page To view the ads, click the links below. If you were not able to view at lea st one of the ads click here. The questions on the next three pages ask your opinion of the format of the ads you just saw. The format refers to the way the ad appears on the Web page not the product or service advertised in the ad. The ads you just saw are called banner ads. A banner ad i s a rectangular-shaped ad and i s often found at the top of Web page To answer these questions consider the range of banner advertising you see whil e surfing the Web and not necessarily the banner ads you just saw. If you have never seen a banner ad before base your assessment on the ads you just saw. In general, banner ads are: [ROTATED RESPONSES] Strongly Agree Neither Disagree Strongly Agree Agree nor Disagree Disagree Annoying Beneficial Different Disruptive Entertaining

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222 Inf orrr1ati ve Innovative Intrusive Usefi1l Compared to other fortnats of online advertisiI1g, how would you describe banner ads ? [To answer thi s question if you agree 100 /o with the statement on the left, mark the circle below it. If you agree 100% with the state.r1ent on the right mark the circle below it. If you fall somewhere in between, mark the appropriate circle ] Liked byme 0 0 0 One of the worst 0 0 0 0 0 An excellent format 0 0 0 0 I hate it 0 0 0 0 Disliked by me 0 One of the best 0 A poor f or1nat 0 I love it 0 How familiar would you say you are with banner ads? Very familiar (I've seen banner ads a lot.) Somewhat familiar Somewhat unfamiliar Very unfamiliar (I've never seen a banner ad before.) Have you ever clicked througl1 011 a banner ad to get 1nore infonnation about the product or service advertised in the banner ad ? Yes No How many times have you clicked through on a banner ad in the past month? None 1-2 3-4 5-6 D 7 or more

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223 Has a banner ad ever prompted you to later visit the advertised Web site? Yes No Second Online Ad Format The next online ad fo1mat is a POP-UP AD. These ads will pop up when yo11 go to the requested Web page Spend about one minute looking at the ads and considering your opinion of them Imagine that you have encountered these ads while surfing the Web. After you have looked at the first ad, close the browser window and then look at the second ad. After looking at the seco nd ad, close the browser window Then hit the NEXT button to move to the next page. To view the ads, click the links below. If you were not able to view at least one of the ads, click here. The questions on the next three pages ask your opinion of the format of the ads you just saw. The format refers to the way the ad appears on the Web page ~ not the product or service advertised in the ad. The ads you just saw are called pop-up ads A pop-up ad appears in a separate window when you are on a Web page. To answer these q11estions consider the range of pop-up advertising you see while surfing the Web and not necessarily the pop-11p ads yot1just saw. If you have never seen a pop-up ad before, base your assessment on the ads you just saw. In general, pop-up ads are: [ROTATED RESPONSES] Strongly Agree Neither Disagree Strongly Agree Agree nor Disagree Disagree Annoying D D D D D Beneficial D D D D D Different D D D D D

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224 Disruptive Entertaining Informative Innovative Intrusive Usefu l Compared to other formats of online advertising how would you describe pop-up ads? Liked byme 0 0 0 One of the worst 0 0 0 0 0 An excellent format 0 0 0 0 I hate it 0 0 0 0 Disliked by me 0 One of the best 0 A poor format 0 I love it 0 How familiar would you say you are with pop-up advertising? Very familiar (I've seen pop-up ads a lot.) Somewhat familiar Somewhat unfamiliar Very unfamiliar (I've never seen a pop-up ad before.) Have you ever clicked through on a pop-up ad to get more information about the product or service advertised in the pop-up ad? Yes No How many times have you clicked through on a pop-up ad in the past month ? None 1-2 3-4 5-6 7 or more

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225 Has a pop-up ad ever prompted you to later visit tl1e advertised Web site ? Yes No Third Online Ad Forrnat The next online ad fortnat is called a SKYSCRAPER AD. These ads are located along the side of a Web pa g e Spend about one minute looking at the ads and considering your opinion of them Imagine that you have encount e red the s e ads while surfing the Web. After you have looked at the first ad clo s e the browser window and then look at the second ad. After looking at the second ad close the browser window Then hit th e NEXT button to move to the next page To view the ad s click the links below. If you were not able to view at least one of the ads click here The que s tions on the next three pages ask your opinion of the format of the ads you just saw. The format refers to th e way the ad appears on the Web page. The ads you ju s t saw are called sky s craper ads A skyscraper ad js a tall thin ad that appears along the sid e of a Web page To answer these questions, consider the range of skyscraper ads you see while surfing the Web and not necessarily the skyscraper ads you just saw. If you have never seen a skyscraper ad before, ba s e your assessment on the ads you just saw In general skyscraper ads are: [ROTATED RESPONSES] Strongly Agree Neither Disagree Strongly Agree Agree nor Disagree Disagree Annoying Beneficial

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226 Different Disruptive Entertaining Infortnative Innovative Intrusive Useful Compared to other formats of online advertising, how would you describe skysc raper ads? Liked by me 0 0 0 One of the worst 0 0 0 0 0 An excellent fonnat 0 0 0 0 I hate it 0 0 0 0 Disliked by me 0 One of the best 0 A poor format 0 I love it 0 How familiar would you say you are with skyscraper ads ? Very fanuliar (I've seen skyscraper ads a lot .) D Somewhat familiar Somewhat unfamiliar Very tmfamiliar (I've never seen a skyscraper ad before ) Have you ever clicked through on a skyscraper ad to get 1nore information about the product or service advertised in the skyscraper ad? Yes No How many times h ave you clicked tlrrough 011 a skyscraper ad in the pa st month ? None 1-2 3-4 5-6 7 or more

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227 Has a skyscraper ad ever prompted you to later visit the advertised Web site? Yes No Progress Report You're already halfway to the end! Just three more ad formats to go. Fourth Online Ad Fo11nat The next online ad format is called a LARGE RECTANGLE AD. These ads are located in the middle of the Web page wrapped :,y the text of the article. Spend about one minute looking at the ads and considering your opinion of them. Imagine that you have encountered these ads while surfing the Web. After you have looked at the first ad, close the browser window and then look at the second ad. After looking at the second ad, close the browser window. Then hit the NEXT button to move to the next page. To view the ads, click the links below. D If you were not able to view at least one of the ads, click here. The questions on the next three pages ask your opinion of the format of the ads you just saw The format refers to the way the ad appears on the Web page The ads you just saw are called large rectangle ads. A large rectangle ad is often found in the middle of a Web page wrapped by text. As the name implies, the ad is both large and rectangular in shape. To answer these questions, consider the range of large rectangle ads you see while surfing the Web and not necessarily the ads you just saw If you have never seen a large rectangle ad before, base your assessment on the ads you just saw.

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228 In general large rectangle ads are: [ROTATED RESPONSES] Strongly Agree Neither Disagree Strongly Agree Agr~e nor Disagree Disagree Annoying Beneficial Different Disruptive Entertaining Inf 01 rnati ve Innovative Intrusive Useft1l Compared to other formats of online advertising, how would you describe large rectangle ads? Liked byme 0 0 0 One of the worst 0 0 0 0 0 An excellent f 01 rr1at 0 0 0 0 I hate it 0 0 0 0 Disliked by me 0 One of the best 0 A poor format 0 I love it 0 How familiar would yo u say you are with large rectan gle ads? Very familiar (I've seen large rectangle ads a lot .) Somewl1at familiar D Somewhat unfamiliar D Very unfamiliar (I've never seen a large 1ectangle ad before.)

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229 Have you ever clicked through on a large rectangle ad to get more information about th e product or servi c e advertised in the ad ? Yes No How many times have you clicked through on a large rectangle ad in the past month? None 1-2 3-4 5-6 7 or more Has a large rectangle ad ever prompted you to later visit the advertised Web site ? Yes 0 No Fifth Online Ad Format The next online ad format is called a FLOATING AD These ads appear on the page a few moments after arriving at the requested Web page Spend about one minute looking at the ads and considering your opinion of them Imagine that you have encountered these ads while surfmg the Web. After you have looked at the first ad, close the browser window and then look at th e second ad. After looking at the second ad, close the browser window. Then hit the NEXT button to move to the next page. To view the ads click the links below. YOU MAY NEED TO MAXIMIZE YOUR BROWSER TO FULL-SCREEN TO COMPLETELY SEE THE ADS. If you were not able to view at least one of the ads, click here. The questions on the ne x t three pages ask your opinion of the format of the ads you just saw The fo1mat refers to the way the ad appears on the Web page. The ads you just saw are called floating ads A floating ad moves across the page when you are on a Web page

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230 To answer these questions, consider the range of floating ads you see while surfing the Web and not necessarily the floating ads you just saw If you have never seen a floating ad before, base your assessment on the ads you just saw. In general floating ads are: [ROTATED RESPONSES] Strongly Agree Neither Disagree Strongly Agree Agree nor Di s agree Disagree Annoying Beneficial Different Disruptive Entertaining Informative Innovative Intrusive Useful Compared to other formats of online advertising, how would you describe floating ads? Liked by me 0 0 0 One of the worst 0 0 0 0 0 An excellent format 0 0 0 0 I hate it 0 0 0 0 Disliked by me 0 One of the best 0 A poor format 0 I love it 0

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231 How familiar would you say you are with floating ads? Very familiar (I've seen floating ads a lot.) Somewhat familiar Somewhat unfamiliar Very unfamiliar (I've never seen a floating ad before.) Have you ever clicked through on a floati11g ad to get more information about the product or service advertised? Yes No How many times have you clicked through on a floating ad in the past month ? None 1-2 3-4 5-6 7 or more Has a floating ad ever prompted you to later visit the advertised Web site? Yes No Sixth Online Ad Fo11nat The next online ad format is called an INTERSTITIAL AD. These ads appear before you arrive at the requested Web page Watch the ads as the requested page loads and consider yotrr opinion of them hnagine tl1at you have encountered these ads while surfing the Web. After you have looked at the first ad, close the browser window and then look at th e second ad. After looking at the second ad, close the browser window. Then hit the NEXT button to move to the next page. To view the ads, click the links below If you were not able to view at least one of the ads, click here The questions on the next three pages ask your opinion of the format of the ads you just saw. The for1nat refers to the way the ad appears on the Web page. The ads you just saw are called interstitial ads. An interstitial ad appears when you are moving between two Web pages. When the requested page has loaded, the interstitial ad goes awa y

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232 To answer these questions, consider the range of interstitial ads you see while surfing the Web and not necessarily the interstitial ads you j11st saw. If you have never seen an interstitial ad before base your assessment on the ads you just saw. In general interstitial ads are: [ROTATED RESPONSES] Strongly Agree Neither Disagree Strongl y Agree Agree nor Disagree Disagree Annoying Beneficial Different Disruptive Entertaining Informative Innovative Intrusive Usefu l Compared to other formats of on1ine advertising, how would you describe interstitial ads ? Liked byme 0 0 0 One of the worst 0 0 0 0 0 An excellent for1nat 0 0 0 0 I hate it 0 0 0 0 Disliked by me 0 One of the best 0 A poor format 0 I love it 0

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233 How familiar would you say you are with interstitial ads? Very familiar (I've seen interstitial ads a lot.) Somewhat familiar Somewhat unfanuliar Very unfamiliar (I've never seen an i11terstitial ad before.) Have you ever clicked through on an interstitial ad to get more information about the product or service advertised? Yes No How many times have you clicked through on an interstitial ad in the past month? None 1-2 3-4 5-6 7 or more Has an interstitial ad ever prompted you to later visit the advertised W eh site? Yes No Demographics Please provide some background information to help categorize your responses. Which of the following best describes your primary connection to the Internet? 28.8 Kbps modem D 56 Kbps modem ISDN Cable modem DSL Tl or better D Do not know but high speed Do not know D Other (please specify) Excluding email, gaming and instant messaging, how many hours a week do you spend surfing the Internet? What year did you start using the Internet on a regular basis? Have you ever made an online purchase? D Yes No

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234 How many online purchases have you made during the past six months? None 1-2 3 -4 5-6 7 or more Just a few more questions to help categorize your responses. Are you ... ? Male Female What year were you born? What is your marital status? Married Single, never married Divorced Separated D Widowed D Living with partner What is the highest level of education you have completed or the highest degree you have received? Less than high school Completed some high school High school graduate or equivalent ( e.g GED) Completed some college, but no degree Two-year college degree Four-year college degree Completed some graduate school, but no degree Graduate degree (e.g., M.S., M.A., J.D. Ph.D.) What is your employment status ? Employed full time Employed part time Self-employed Homemaker D Student Retired Not employed, but looking for work Not employed and not looking for work Other

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235 Which of the following best represents your total 2002 household income before taxes? Less than $15,000 $15 000 to $24,999 $25,000 to $34,999 $35,000 to $49,999 $50,000 to $74,999 $75,000 to $99,999 $100,000 to $124,999 $125,000 to $149,999 $150,000 to $199,999 $200,000 to $249,000 $250,000 or more Decline to answer In what state do you currently reside? With which of the following racial groups do you most closely identify? White Black/African American Asian or Pacific Islander Native American or Alaskan native Decline to answer Other (please specify) Conclusion THANKS! You have reached the end of ttc survey. Your time and paiticipation are greatly appreciated If you have any comments or feedback about this survey or encountered any technical difficulties, please send an e-mail to ufl2003 @ hotmail.com.

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APPENDIXE FACTOR ANALYSES FOR PERCEPTUAL AND ATTITUDINAL MEASURES BY ONLINE AD FORMAT Analyses for Banner Ads Table E-1. Rotated Component Matrix of Perceptual Items for Banner Ads Perceptual Item Overbearing Disruptive Intrusive Annoying Entertaining Amusing Attractive Different Eye-catching Useful Beneficial Innovative Informative Sophisticated Elaborate Factor I: Annoying .87 .82 .77 .75 -.14 -.19 31 10 .16 .50 -.52 .09 -.26 -.13 .33 Factor II: F acto1 III: Entertaining Informative/Different -.02 -.25 .14 -.23 .85 .83 .47 .01 .45 .09 .10 .46 .23 .04 .36 .02 .08 -.13 -. 01 .10 .21 .36 .72 .59 .57 .53 .52 .51 18 .01 Note. Bold items indicate items loading on each factor. 236 Factor IV: Fancy .02 -. 06 .30 .26 .21 .07 .45 .04 -.09 .37 .45 .23 17 .81 .70

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237 Table E-2. Means, Standard Deviations, and Alphas for Banner Ad Factors Measure Annoying E11tertaining Infonn/Different Fancy M SD n 2.95 95 .85 102 2.89 76 81 102 Table E-3 Factor Analysis of A ad for Banner Ads Item A ad Factor Loadings Good/bad .90 Pleasant/Unpleasant .84 Favorable/Unfavorable 91 M 3 42 SD 88 a .86 3.08 67 75 102 Table E-4 Factor Analysis of A rormat for Banner Ads Item A rorm a t Factor Loading s Like/Dislik e Best/Worst Excellent/Poor Love/Hate M SD a 92 .92 87 91 3.25 1 00 92 2.57 72 58 102

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238 Table E-5. Factor Analysis of A si te for Banner Ads Item Factor Loadings M SD I like this Web site. It is a good Web site. It is a nice Web site. A site 90 .95 .93 3.43 .72 .91 Analyses for Pop-up Ads Table E-6. Rotated Component Matrix of Perceptual Items for Pop -u p Ads Perceptual Item Elaborate Sophisticated Amusing Innovative Entertaining Eye-catching Different Inf onnati ve Beneficial Useful Attractive Factor I: Entertaining .80 .75 .73 .67 .63 .57 .48 .20 .18 .32 .46 Factor TI: Informative 03 23 .30 .49 .33 .45 .48 .76 .72 .71 .59 Factor III: Annoying 03 -.18 -.29 -.05 -.29 .12 02 -.04 -.40 -.30 -.22 (Table E-6 continues)

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(Table E-6 continued) Factor I: Perceptual Item Entertaining Disruptive Annoying Intrusive Overbearing -.30 -.05 -.04 -.06 239 Factor II: Informative .04 -.34 .001 -.33 Note. Bold items i11dicate items loading on each factor. Factor ill: Annoying .8 3 8 0 .77 75 Table E7. Means, Standard Deviations, and Alrhas for Pop-up Ad Factors Measure Entertaining Informative Annoying M SD a n 2.95 80 .87 102 2.64 .84 .83 102 Table E-8. Factor Analysis of A ad for Pop-Up Ads Item Factor Loadings M SD a Good/bad Pleasant/Unpleasant Favorable/U1uavorable A ad .93 94 .97 2.86 1.19 .94 4.19 .90 .84 102

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240 Table E-9. Factor Analysis of A ronnat for Pop-up Ads Item Factor Loading s Like/Dislike Be s t/Worst Excellent/Poor Love/Hate M SD a A rormat .93 .96 91 .97 1 .8 5 1 07 .95 Table E-10. Factor Analysis of A site for Pop-up Ads Item Factor Loading s M SD a I like thi s Web s ite It is a good Web site. It is a nice Web site. A site .94 .96 94 3.44 .89 95

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241 Analyses for Skyscraper Ads Table E-11. Rotated Component Matrix of Perceptual Items for Skyscraper Ads Perceptual Item Useful Informative Eye-catching Entertaining Attractive Beneficial Disruptive Intrusive Overbearing Annoying Innovative Sophisticated Different Elaborate Ainusing Factor I: Inform/Entertain .80 .76 .76 .69 .59 .58 23 .07 07 33 .22 .30 -.05 31 .49 Factor II: Annoying 24 28 -.04 05 -.37 41 .87 .85 .82 .80 09 13 .10 .10 -.11 Note. Bold items indicate items loading on each factor. Factor III: Different .14 .14 15 .44 .49 31 -.02 06 -.05 03 .70 .68 .65 .58 .53 Table E-12. Means, Standard Deviations, and AJphas for Skyscraper Ad Factors M SD a tl Measure Inform/Entertaining Annoying Different 3 46 .67 87 97 2.23 70 .88 97 3 12 .60 72 97

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242 Table E-13. Factor Analysis of Aad for Skyscraper Ads Item Factor Loadings M SD a Good/bad Pleasant/Unpleasant Favorable/Unfavorable A a d .94 .96 .95 4 05 .87 94 Table E-14 Factor Analysis of A ro rma t for Skyscraper Ads Item A ro rma t Factor Loadings Like/Dislike Best/Worst Excellent/Poor Love/Hate M SD a .92 .92 .88 90 3.83 82 .92

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243 Table E-15. Factor Analysis of A site for Skyscraper Ads Item Factor Loadings M SD a I like this Web site It is a good Web site. It is a nice Web site. A s i te .89 .95 .90 3.62 .72 90 Analyses for Large Rectangle Ads Table E-16. Rotated Component Matrix of Perceptt1al Items for Large Rec Ads Perceptual Item Innovative Different Elaborate Entertaining Eye-catching Amusing Sophisticated Disruptive Intrusive Annoying Overbearing Attractive Factor I: Entertaining .76 .74 .73 .68 .68 .63 .58 12 -.09 -.20 20 .42 Factor TI: Factor III: Annoying Inforrnative -.20 -.17 .09 -.27 -.06 -.31 -.22 87 .86 .8~ .75 -.53 .21 .07 .26 .18 -.01 .17 42 -.22 -.13 15 25 .37 {Table E-16 continues)

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244 (Table E-16 continued) Factor I : Factor II: Perceptual Item Entertaining Annoying Informative 12 10 Useful .19 -.31 Beneficial 29 -.38 Note. Bold items indicate items loading on each factor. Factor ill: Informative .82 .74 .72 Table E-17. Means, Standard Deviations, and Alphas for Large Rec Factors M SD a N Measure Entertaining 3.18 .69 .86 117 Annoying 3.02 .67 .62 117 Table E-18. Factor Analysis of Aa d for Large Rec Ads Item Factor Loadings M SD a Good/bad Pleasant/Unpleasant Favorable/Unfavorable A ad .92 .88 .93 3 90 .83 .89 Informative 3 47 .72 .81 117

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245 Table E-19 Factor Analysis of A ronnat for Large Rec Ads Item Factor Loading s Like/Di s like Best/Wor s t Excell e nt/Poor Love/Hate M SD a A ronnat .9 0 9 2 90 89 3 36 92 92 Table E-20. Factor Analysis of A site for Large Rec Ads Item Factor Loading s M SD a I like this Web site. It is a good Web site. It is a nice Web site. A site 92 97 94 3.59 .72 .93

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246 Analyses for Floating Ads Table E-21. Rotated Componen t Matrix of Perceptual Items for Floating Ads Perceptual Item Intrusive Disruptive Overbearing Annoying Attractive Entertaining Beneficial Amusing Usefu l Innovative Different Eye-catching Elaborate Sophisticated Informative Factor I: Annoy/Entertain/ Usefu l .89 .89 .88 .8 7 -.64 -.62 .61 -.57 -.57 -.04 -.13 .20 .34 -.10 -.51 Factor II: Different .08 14 .02 -.06 .53 .51 23 .33 .16 .84 .71 .69 11 .45 -.06 Note. Bold items indicate item s loading on each factor. Factor ill : Informativ e / Fancy -.05 .03 .03 .08 16 .22 .47 .25 .53 -.01 .14 .15 .75 .59 .56

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247 Table E-22. Means, Standard Deviations, and Alphas for Floating Ad Factors Measure Annoy / Entertain/Useful Different Informative/Fancy M SD a n 3.69 .41 .25 76 4.44 .49 .69 76 Table E-23. Factor Al1a l ysis of A ad for Floating Ads Item Factor Loadings M SD a Good/bad Pleasant/Unpleasant Favorable/Unfavorable A a d .96 .96 .97 3.40 1.35 .96 Table E-24. Factor Analysis of A rormat for Floating Ads Item Ar o rm at Factor Loadings Like/Dislike Best/Worst Excellent/Poor Love/Hate M SD a 96 .97 .93 .96 3.07 1.41 .97 3.40 68 .50 76

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248 Table E-25. Factor Analysis of A site for Floating Ads Item Factor Loadings M SD a I like this Web site. It is a good Web site. It is a nice Web site. A site 93 96 .94 3.88 .78 94 Analyses for Interstitial Ads Table E-26 Rotated Component Matrix of Perceptual Items for Interstitial Ads Perceptual Item Elaborate Amusing Entertaining Sophisticated Innovative Different Attractive Eye-catching Useful Beneficial Infortnative Factor I: Info11native/Entertaining 84 79 77 77 .73 .69 66 .57 .56 .55 .43 Factor II: Annoying -.02 -.27 -.23 -.07 01 09 47 .16 -.52 -.53 37 (Table E-26 continues)

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249 (Table E-26 continl1ed) Factor I: Perceptual Item Informative / Entertaining Disruptive Annoying Overbearing Intrusive -.05 -.03 -.001 .03 Note. Bold items indicate items loading on each factor. Table E-27. Means, Standard Deviations, and M SD a n Alphas for Interstitial Ad Factors Measure Inform/Entertain Annoying 3 42 68 .90 81 3.18 1.09 95 81 Table E-28 Factor Analysis of A a d for Interstitial Ads Item Factor Loadings M SD a Good/bad Pleasant/Unpleasant Favorable/Unfavorable A ad 96 .94 .97 3.53 1.19 95 Factor II: Annoying .94 .93 .92 .88

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250 Table E-29. Factor Analysis of A rormat for Interstitial Ads Item Factor Loadings Like/Dislike Best / Worst Excellent/Poor Love/Hate M SD a A rormat .93 .9 5 .90 .93 3.29 1 .0 6 95 Table E-30 Factor Analysis of A site for Interstitial Ads Item Factor Loadings M SD a I like this Web si te It is a good Web s ite It is a nice Web site. A site .90 .94 .92 3 .6 5 .72 .91

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BIOGRAPHICAL SKETCH Kelli Suzanne Bums was born in Tampa, Fla ., on Jan. 4, 1971, to Will and Astrid Staples. Raised in Dade City, Fla., she attended St. Anthony School in San Antonio for eight years and then graduated from Berkeley Preparatory School in Tampa in 1988. At Vanderbilt University, Kelli majored in n1athematics and minored in business administration. During her senior year, Kelli served as the editor of the award-winning 1992 Commodore yearbook. Kelli received a Master of Science degree from Middle Tennessee State University in 1998 and a Doctor of Philosophy degree from the University of Florida in 2003. Her professional experience includes positions in marketing communications with Manulife Financial and in market research with Prince Market Research and Harris Interactive. Kelli has taught in the School of Communications at Elon University, the College of Mass Communication at Middle Tennessee State University, and the College of Journalism and Communications at the University of Florida Kelli is married to Corey Adam Burns and is the mother of Griffin Spencer Bums. 264

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I certify that I have read this study and that in my opinion it conforms to acceptable standards of scholarly presentation and is fully adequate, in scope and quality, as a dissertation for the degree of Doctor of Philo so phy C. hn C. Sutherland Chair Profes so r of Journalism and Communications I cert ify that I ha ve read this s tud y and that in my opinion it confo 1m s to acceptable s tand a rd s of scholarly pre se ntation and i s fully adequate in sco pe and quality as a di sse rtation fo r the degr ee of Do c tor of Philo so phy. Ri c hard J. Lutz, Cochai Profe sso r of Marketing I certify that I h ave read thi s s tud y and that my opinion it confo11ns to acceptable sta nd ar d s of sc holarly pre se ntation di fully adequate, in scope ann--nuality as a di sse rtation for the de g ree of Do c tor of P ilo s G-thy. P, ofessor of Journali s m and Communications I ce r t ify th a t I ha ve read thi s s tudy and that in my opinion it conforms to acceptable sta ndard s of sc holarl y pre se nt a tion and i s fully adequate, in sc ope and quality as a di sse rtation for the de g re e of Do ctor of Philo so phy. Marilyn S. Roberts A ssoc iate Profe ss or of Journalism and Communications I ce rtify t hat I h ave read tl1is st ud y and that in my opinion it co nforrn s to acceptable sta ndard s of sc hol ar l y pre se ntation and is f ully adequate, in sco pe and quality a s a di sse rtation fo r the de g r ee of Do c tor of Ph ophy. csd~ wt.....-<-. B a rton A. Weitz J .C. Penney Eminent Scholar of Marketing

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Thi s di ssertatio n was s ubmjtted to the Graduate Faculty of the College of Journali s m and Communications a nd to the Graduate School and was accepted as partial fulfillment of th e requirements for the de g ree of Doctor of Philosophy. Augu s t 2003 e College of J oumalism and Communications Dean Graduate School

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