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Relationship Framework in Sport Management

Permanent Link: http://ufdc.ufl.edu/UFE0022593/00001

Material Information

Title: Relationship Framework in Sport Management How Relationship Quality Affects Sport Consumption Behaviors
Physical Description: 1 online resource (164 p.)
Language: english
Creator: Kim, Yu
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2008

Subjects

Subjects / Keywords: quality, relationship, spectator, sport
Health and Human Performance -- Dissertations, Academic -- UF
Genre: Health and Human Performance thesis, Ph.D.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: Relationship marketing is such an integral part of modern marketing including sport marketing. Teams are striving to build a good relationship with their fans. The objective of this dissertation is to provide a better understanding of the nature of the relationship between team and sport consumers, and the impact of the relationship on various sport consumption behaviors. Conceptual framework to investigate the research questions were developed based on the relationship quality literature. Sport consumption behavior, relational personality traits, and demographics surveys were conducted both online and face-to-face. Various statistical techniques such as Confirmatory Factor Analysis (CFA), Structural Regression, and Multiple Sample Structural Equation Modeling were employed for data analysis. A five factor model including Trust, Commitment, Reciprocity, Self-Connection, and Relationship Satisfaction was supported to best measure relationship quality between sport consumers and the UF Football team. However, a four factor model incorporating Trust, Commitment, Reciprocity, and Relationship Satisfaction was supported to best represent relationship quality for iPod. Regarding the structural nature of relationship quality, results from both data referent to UF Football Team and iPod provided support for a second-order hierarchical factor model. A sport consumption behavior model, which consisted of Intention for Attendance, Media Consumption, and Licensed Merchandise Consumption, was also best explained by a second-order hierarchical model. In addition, relationship quality significantly influenced sport consumption behaviors related to the UF Football team and purchase intentions for iPod. None of potential moderators influence the relationship between relationship quality and its outcomes. This study extends sport management literature by applying relationship marketing theories to the sport consumer behavior realm. Researchers and sport industry practitioners should further examine the proposed relationship quality model in this study.
General Note: In the series University of Florida Digital Collections.
General Note: Includes vita.
Bibliography: Includes bibliographical references.
Source of Description: Description based on online resource; title from PDF title page.
Source of Description: This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Statement of Responsibility: by Yu Kim.
Thesis: Thesis (Ph.D.)--University of Florida, 2008.
Local: Adviser: Ko, Yong Jae.

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2008
System ID: UFE0022593:00001

Permanent Link: http://ufdc.ufl.edu/UFE0022593/00001

Material Information

Title: Relationship Framework in Sport Management How Relationship Quality Affects Sport Consumption Behaviors
Physical Description: 1 online resource (164 p.)
Language: english
Creator: Kim, Yu
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2008

Subjects

Subjects / Keywords: quality, relationship, spectator, sport
Health and Human Performance -- Dissertations, Academic -- UF
Genre: Health and Human Performance thesis, Ph.D.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: Relationship marketing is such an integral part of modern marketing including sport marketing. Teams are striving to build a good relationship with their fans. The objective of this dissertation is to provide a better understanding of the nature of the relationship between team and sport consumers, and the impact of the relationship on various sport consumption behaviors. Conceptual framework to investigate the research questions were developed based on the relationship quality literature. Sport consumption behavior, relational personality traits, and demographics surveys were conducted both online and face-to-face. Various statistical techniques such as Confirmatory Factor Analysis (CFA), Structural Regression, and Multiple Sample Structural Equation Modeling were employed for data analysis. A five factor model including Trust, Commitment, Reciprocity, Self-Connection, and Relationship Satisfaction was supported to best measure relationship quality between sport consumers and the UF Football team. However, a four factor model incorporating Trust, Commitment, Reciprocity, and Relationship Satisfaction was supported to best represent relationship quality for iPod. Regarding the structural nature of relationship quality, results from both data referent to UF Football Team and iPod provided support for a second-order hierarchical factor model. A sport consumption behavior model, which consisted of Intention for Attendance, Media Consumption, and Licensed Merchandise Consumption, was also best explained by a second-order hierarchical model. In addition, relationship quality significantly influenced sport consumption behaviors related to the UF Football team and purchase intentions for iPod. None of potential moderators influence the relationship between relationship quality and its outcomes. This study extends sport management literature by applying relationship marketing theories to the sport consumer behavior realm. Researchers and sport industry practitioners should further examine the proposed relationship quality model in this study.
General Note: In the series University of Florida Digital Collections.
General Note: Includes vita.
Bibliography: Includes bibliographical references.
Source of Description: Description based on online resource; title from PDF title page.
Source of Description: This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Statement of Responsibility: by Yu Kim.
Thesis: Thesis (Ph.D.)--University of Florida, 2008.
Local: Adviser: Ko, Yong Jae.

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2008
System ID: UFE0022593:00001


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1 RELATIONSHIP FRAMEWORK IN SPORT MANAGEMENT: HOW RELATIONSHIP QUALITY AFFECTS SPORT CONSUMPTION BEHAVIORS By YU KYOUM KIM A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLOR IDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY UNIVERSITY OF FLORIDA 2008

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2 2008 Yu Kyoum Kim

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3 To my wife, Hyun-Ok

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4 ACKNOWLEDGMENTS This dissertation benefited tremendously from my committee. I am truly honored that I have learned from the best committee members. Firs t of all, I would like to give many thanks my advisor, Dr. Galen Trail. I am truly indebted for his advice, en couragement, tremendous support, and opportunities he provided for last four years at the University of Fl orida. I cannot find word to express my wholehearted appreciation for him. I remain in awe of Trail. Next, I would like to give special thanks to Dr. Yong Jae Ko. He ha s been friendly, caring, supportive and helpful in numerous ways. He guided me through tough times. I would also thank other committee members, Drs. Lutz, Pennington-Gray, and Zh ang, who have been really encouraging and supportive. I am also very grateful that I have worked with the be st colleagues at the University of Florida and the College of H ealth and Human Performance. Mo st importantly, I deeply thank my family and friends. I would like to propose a final toast to Hyun-Ok, my wife, friend, and partner. I could not have overcome all the hur dles I have encountered throughout my doctoral studies without her supp orts and sacrifices.

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5 TABLE OF CONTENTS page ACKNOWLEDGMENTS ............................................................................................................... 4 LIST OF TABLES ...........................................................................................................................8 LIST OF FIGURES .......................................................................................................................10 ABSTRACT ...................................................................................................................... .............11 CHAP TER 1 INTRODUCTION .................................................................................................................. 13 Significance of Spectator Sports .............................................................................................13 Need for a Relationship Paradigm ..........................................................................................14 Statement of Problem .......................................................................................................... ...16 Purpose of the Study .......................................................................................................... .....18 2 LITERATURE REVIEW .......................................................................................................21 Relationship Marketing ........................................................................................................ ..21 Relationship Quality Construct ............................................................................................... 23 Trust ......................................................................................................................... ........23 Commitment .................................................................................................................... 25 Relationship Satisfaction ................................................................................................. 25 Self-Connection ...............................................................................................................26 Love .................................................................................................................................27 Intimacy ...................................................................................................................... .....27 Reciprocity ................................................................................................................... ...28 Structural Nature of Relationship Quality .............................................................................. 30 General Relationship Quality Factor Model ....................................................................30 Independent Factor Model ...............................................................................................31 Group Factor Model ........................................................................................................32 Second-Order Hierarchical Model .................................................................................. 33 Modified Second-Order Hierarchical Model ...................................................................34 Predictive Value of Relationship Quality ............................................................................... 35 Behavioral Intention ........................................................................................................ 35 Word of Mouth ................................................................................................................ 37 Media Consumption ........................................................................................................ 38 Licensed Products ............................................................................................................39 Attendance .................................................................................................................... ...39

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6 Moderators of Relationship Qualitys In fluence on Sport Consum ption Behavior ............... 40 Moderator Effects ............................................................................................................ 41 Moderators of Relationship Qualit y-Relationship Outcom e Linkage ............................. 42 Product Category ......................................................................................................43 Psychographic Factors ..............................................................................................44 Summary ....................................................................................................................... ..........45 3 METHODOLOGY ................................................................................................................. 57 Participants and Procedures ................................................................................................... .57 Instrumentation ............................................................................................................... ........59 Item Deve lopm en t ........................................................................................................... 59 Relationship quality .................................................................................................. 59 Relationship quality outcome variables ................................................................... 60 Personality traits .......................................................................................................61 Demographics ........................................................................................................... 62 Expert Review ........................................................................................................................62 Pilot Study ..............................................................................................................................63 Methods ...........................................................................................................................63 Participants and procedure ....................................................................................... 63 Instruments ............................................................................................................... 63 Data analysis ............................................................................................................63 Results and discussion ..................................................................................................... 64 Data Analysis for Main Study ................................................................................................ 66 Descriptive Statistics ....................................................................................................... 67 Data Screening and Test of Assumption .........................................................................67 Measurement Model ........................................................................................................ 68 Structural Model .............................................................................................................. 70 Moderating Effects .......................................................................................................... 70 4 RESULTS ....................................................................................................................... ........83 Descriptive Statistics ........................................................................................................ ......83 Demographics .................................................................................................................. 83 Relationship Quality Variables ........................................................................................ 83 Consumption Variables ................................................................................................... 83 Relationship Style Variables ........................................................................................... 84 Data Screening and Test of Assumptions for Structural Equation Modeling (SEM) ............. 84

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7 Measurement Models ............................................................................................................ ..85 Relationship Quality (UF Football team) ........................................................................ 85 Validation of the measure ........................................................................................ 85 Structure of the relations hip quality constructs ........................................................86 Relationship Quality (iPod) ............................................................................................. 87 Validation of the measure ........................................................................................ 87 Structure of the relations hip quality constructs ........................................................89 Relationship Outcome (UF Football team) ..................................................................... 90 Relationship Outcome (iPod) ..........................................................................................91 Relationship Personality ..................................................................................................92 Structural Models ............................................................................................................. .......92 Moderating Effects ............................................................................................................ .....93 Relationship Development ..............................................................................................93 Relationship Maintenance ...............................................................................................94 5 DISCUSSION .................................................................................................................... ...132 Validation of the Measures ...................................................................................................132 Relationship Quality Constructs (UF Football Team) ................................................... 132 Relationship Quality Constructs (iPod) ......................................................................... 134 Sport Consumption Behaviors and R elationship Style ................................................. 135 Structural Nature of Relationship Quality ............................................................................ 136 UF Football Team .......................................................................................................... 136 iPod .......................................................................................................................... ......139 Sport Consumption Beha viors (UF Football) ................................................................ 139 Outcomes of Relationship Quality ........................................................................................140 Moderators of Relationship Qual ity-Consum ption Association ........................................... 141 Implications of the Research ................................................................................................ 142 Conceptual and Theoretical Implications ...................................................................... 142 Managerial Implications ................................................................................................ 144 Limitations and Future Directions ........................................................................................ 146 Summary ....................................................................................................................... ........147 LIST OF REFERENCES .............................................................................................................149 BIOGRAPHICAL SKETCH .......................................................................................................164

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8 LIST OF TABLES Table page 3-1 Relationship quality (UF Football Team) summary results for m easurement model in pilot study...........................................................................................................................72 3-2 Correlations among relationship quality cons tructs (UF Football Team ) in pilot study ... 73 3-3 Summary results for measurement model of relationship quality (iPod) in pilot study ....74 3-4 Correlations among relationship quality constructs (iPod) in pilot study ..........................75 3-5 Consumption behaviors (UF Football t eam ) summary results for measurement model in pilot study ......................................................................................................................76 3-6 Correlations among sport consumption behaviors constructs in pilot study ..................... 77 3-7 Summary results for measurement model of purchase intention (iP od) in pilot study ...... 78 3-8 Correlations among consumption behavior s constructs (iPod) in pilot study ................... 79 3-9 Summary results for measurement model of relationship style (Initial m odel) ................. 80 3-10 Summary results for measuremen t model of relationship style .........................................81 3-11 Correlations among relational person ality constructs in pilot study ..................................82 4-1 Demographic characteristics of participants ......................................................................95 4-2 Descriptive statistics for re lationship quality (UF Football) .............................................. 96 4-3 Descriptive statistics for relationship quality (iPod) .......................................................... 97 4-4 Descriptive statistics for re lationship outcom es (UF Football) ......................................... 98 4-5 Descriptive statistics for relationship outcom es (iPod) ..................................................... 99 4-6 Descriptive statistics for consum ption behaviors (iPod) ................................................. 100 4-7 Summary results for initial measurement m odel of relationship quality (UF Football, Seven-Factor Model) .......................................................................................................101 4-8 Summary results for measurement mode l of relationship quality (UF Football, Seven-Factor Model) .......................................................................................................102 4-9 Correlations among relationship qua lity constructs (UF Football) .................................. 103

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9 4-10 Summary results for measurement model of relationship quality (UF Football, FiveFactor Model)...................................................................................................................104 4-11 Correlations among relationship qua lity constructs (UF Football) .................................. 105 4-12 Goodness of Fit indices and 2/ df values for the hypothesize d and alternative models (UF Football) ................................................................................................................. ..106 4-13 Summary results for initial measurement m odel of relationship quality (iPod, SevenFactor Model)...................................................................................................................107 4-14 Summary results for measurement model of relationship quality (iPod, Seven-Factor Model) ........................................................................................................................ ......108 4-15 Correlations among relationship quality constructs (iPod) .............................................. 109 4-16 Summary results for measurement model of relationship qualit y (iPod, Four-Factor Model) ........................................................................................................................ ......110 4-17 Correlations among relationship quality constructs (iPod) .............................................. 111 4-18 Goodness of fit indices and 2/ df values for the hypothesized and alternative models (UF Football team) ........................................................................................................... 112 4-19 Summary results for measurement mode l of sport consum ption behaviors (with Word of Mouth) ...............................................................................................................113 4-20 Correlations among consumption behaviors constructs .................................................. 114 4-21 Summary results for measurement m odel of sport consum ption behaviors .................... 115 4-22 Correlations among sport consumption behaviors constructs ......................................... 116 4-23 Goodness of fit indices and 2/ df values for the hypothesized and alternative models for sport consumption behaviors ...................................................................................... 117 4-24 Summary results for measurement model of consum ption behaviors (iPod) with Word of Mouth ................................................................................................................118 4-25 Correlations among consumption behaviors co nstructs (iPod) with W ord of Mouth ..... 119 4-26 Summary results for measurement m odel of purchase behavior (iPod) ..........................120 4-27 Summary results for measuremen t model of relationship style .......................................121 4-28 Correlation between relati onship style constructs ........................................................... 122

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10 LIST OF FIGURES Figure page 1-1 Conceptual framework of relationship qua lity and its effects on sport consum ption behaviors ..................................................................................................................... .......20 2-1 Graphical comparison of intimacy and self-connection .................................................... 47 2-2 General relationship q uality factor model .......................................................................... 48 2-3 Independent factor model .................................................................................................. 49 2-4 Group factor model ........................................................................................................ ....50 2-5 Second-order hierarchical model ....................................................................................... 51 2-6 Modified second-orde r hierarchical model ........................................................................ 52 2-7 Relationship between relationship quality and consum ption behavior ..............................53 2-8 Moderating effects on the relationship qua lity-consum ption behavior association ........... 54 2-9 Relationship style ........................................................................................................ .......55 2-10 Relationship between motives and consum ption behavior ................................................ 56 4-1 Second-order hierarchic al m odel (UF Football) .............................................................. 123 4-2 Second-order hierarchical model (iPod) .......................................................................... 124 4-3 Second-order model for s port consumption behavior ......................................................125 4-4 Structural regression of relationship quality and s port consum ption behaviors ..............126 4-5 Structural regression of relationship quality and s port consum ption behaviors ..............127 4-6 Interaction effect of relationship deve lopm ent on relationship between relationship quality and sport consumption behaviors ........................................................................128 4-7 Interaction effect of relationship deve lopm ent on relationship between relationship quality and purchase intention for iPod ........................................................................... 129 4-8 Interaction effect of relationship main tenance on relationship between relationship quality and sport consum ption behaviors ........................................................................130 4-9 Interaction effect of relationship main tenance on relationship between relationship quality and purchase intention for iP od ........................................................................... 131

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11 Abstract of Dissertation Pres ented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy RELATIONSHIP FRAMEWORK IN SPORT MANAGEMENT: HOW RELATIONSHIP QUALITY AFFECTS SPORT CONSUMPTION BEHAVIORS By Yu Kyoum Kim August 2008 Chair: Yong Jae Ko Major: Health and Human Performance Relationship marketing is such an integral part of modern marketing including sport marketing. Teams are striving to build a good relati onship with their fans. The objective of this dissertation is to provide a bett er understanding of the nature of the relationship between team and sport consumers, and the impact of the rela tionship on various sport consumption behaviors. Conceptual framework to investigate the res earch questions were developed based on the relationship quality literature. Sport consumption behavior, relational personality traits, and demographics surveys were conducted both online and face-to-face. Various statistical techniques such as Confirmatory Factor Anal ysis (CFA), Structural Regression, and Multiple Sample Structural Equation Modeling were empl oyed for data analysis. A five factor model including Trust, Commitment, Reciprocity, Sel f-Connection, and Relation ship Satisfaction was supported to best measure relationship quality between sport consumers and the UF Football team. However, a four factor model incor porating Trust, Commitment, Reciprocity, and Relationship Satisfaction was supported to best re present relationship qual ity for iPod. Regarding the structural nature of relations hip quality, results from both data referent to UF Football Team and iPod provided support for a second-order hier archical factor model. A sport consumption

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12 behavior model, which consisted of Intention for Attendance, Media C onsumption, and Licensed Merchandise Consumption, was also best explai ned by a second-order hierarchical model. In addition, relationship quality signif icantly influenced sport consum ption behaviors related to the UF Football team and purchase intentions for iPo d. None of potential moderators influence the relationship between relationship quality and its outcomes. This study extends sport management literature by applying relationship marketing theories to the spor t consumer behavior realm. Researchers and sport industry pr actitioners should further ex amine the proposed relationship quality model in this study.

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13 CHAPTER 1 INTRODUCTION Significance of Spectator Sports The sport industry is a major segment of the North American economy. The size of sport industry is estimated to be from $213 billion to $560 billion and it is one of the fastest growing industries in the United States (Howard & Crompton, 2005). Sport sp ectating is one of the most popular leisure activities and the sp ectator sport segment represents the largest proportion of the sport industry. Enjoying spectator sports is a virtually ubiquitous phenomenon in North America (Higgs & McKinley, 2005). Attending ones favorit e teams games and supporting the team is an important part of many Americans lives. It would be almost impo ssible to read the newspaper or watch television without coming across some type of sport coverage. People are often more interested in sport triv ia than current economic or political issues. Not surprisingly, Street & Smiths Sports Business Journal (2007) reported the consumer sp ending on spectator sports in the U. S. is estimated at approximately $33 billion a year. More than 170 million Americans attend the games of the four major professional leagues, which includes Major League Baseball, the National Basketball Association, the National Football League, and the National Hockey League (ESPN, 2007) in the 2007 and 2006-2007 season. The National Football League NFL)s broadcasting contract with the three major networks of CBS, Fox, and NBC is worth more th an $2 billion per year or about $70 million per team (Badenhausen, Ozanian, & Settimi, 2007). In addition, the total market value for the 30 Major League Baseball teams and the 30 Nati onal Basketball Associat ion (NBA) teams are estimated to be $12.94 billion and $11.17 billi on respectively in the 2007 fiscal year (Badenhausen et al.). In college sports, the pr osperity of spectator sport is the same. NCAA Division I-A football and basketball attracted 37 million and 27 million spectators in the 2006

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14 season (NCAA, 2007). The National Collegiate Athl etic Association receives about $6 billion over 11 years from their current contract with CBS for the exclusive broadcast of the NCAA mens Basketball Tournament. Average revenue for NCAA Division I schools are over $18 million per year (Fulks, 2005). In sum, the spectator sport segment is eviden tly a significant part of the sport industry and North American industry. Need for a Relationship Paradigm Although sport organizations have been enjoying substantial benefits from the success of the spectator sport segment for the last 30 years, sport organizations ar e recently experiencing a number of significant changes in the sport business environment. Howard and Crompton (2005) emphasized the following critical challenges that both professiona l and collegiate sport organizations should cope with in the current spor t industry: spiraling cost s, a saturated market place, economic disconnect, and emergence of ne w technology. While revenues have increased substantially over the past few years, the cost of running a sport organization has gone up much faster. The average salary in the NBA is more than $4 million a year and the cost of a new stadium for NFL teams now exceeds $1 billion. In addition, average expenses for Division IA programs are greater than 20 million. Competition for spectator dollars is more severe than ever before. In North America, over 600 professional sport teams and 1,000 collegiate athletic programs are vying with each other to attract spectators. Moreover, many working-class and middles-class Americans are feeling marginalized from sport teams because the cost of going to the games has rapidly risen and the traditional wo rking-class and middle class fans cannot afford the cost any more. Rapidly changing and deve loping technologies pose both opportunities and threats to the sport organizations. Facing these challenges, sport marketers fi nd that a paradigm shift to relationship marketing is increasingly necessary and rela tionship marketing has received considerable

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15 attention in sport marketing practice due to th e following reasons. First, under a saturated and highly competitive market climate, sport marketers need to redirect their primary focus from acquisition of new customers to maintenance of existing customers. Creating a new customer is much more difficult and expensive than retaining a current customer (Fornell & Wernerfelt, 1987; Riechel & Sasser, 1990). The in creased importance of customer retention is driving sport marketers to embrace relationship marketing, whic h is mainly concerned with establishing a long-term relationship with customers. It is notew orthy that the series of challenges, which sport organizations confront now, are similar to thos e that were responsible for the development of relationship marketing in many other U. S. indus tries. Sheth (2002) noted that excess capacity, high material cost, and intensified competition on a global basis accounted for emergence of the relationship marketing paradigm. The second reason that a paradigm shift is ne cessary is that sport marketers can take advantage of relationship marketing to repair damaged relationships with middle-class and working-class fans. Sport organizations cannot af ford losing middle-class and working-class fans any longer. Although luxury seating has provided many teams with a primary source of income recently, sport teams cannot rely on luxury seating fo r their sole revenue source because there are only a finite number of people that have the economic capacity and willingness to pay for the luxury suites. In addition, fan apathy will lead to declining overall attendance and TV ratings, which eventually will result in th e decrease of sponsorship, licen sed products sales, broadcast contracts, naming right deals, etc (Howard & Crompton, 2005). Relationship marketing historically was associated with the efforts to nurture relationships with a few key exchange partners (Hunt & Morgan, 1994). However, information technology (IT)-supported customer contact techniques now enable sports marketers to develop some form of relationship not only

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16 with a small number of affluent accounts but also with a large number of sport consumers. Direct marketing and data base building techniques are readily available for sport marketers to develop a customized relationship with many customers, while costing considerably less money than in past years. Finally, similar to a service, the sport produc t is produced, delivered, and consumed at the same time (Gladden & Sutton, 2005). Therefor e, the interaction be tween spectators and constituents of sport teams is considered as part of the product (Aijo, 1996), which means that development of a close relationship between spectato rs and the team is an integral component of the marketing task. This characteristic makes re lationship marketing a more suitable paradigm for sport marketers. In sum, there is evidence that there is a growing need to use the relationship paradigm in sport marketing to overcome the seri ous challenges confronting sport marketers. Statement of Problem Although the amount of th e research on relationship marke ting is continuously increasing in various areas of study and demand for implemen ting relationship marketing is rapidly growing in sport marketing practice, limited amount of rese arch has investigated re lationship marketing in sport. While the current studies on relationship marketing that exist in the sport management realm have yielded valuable insights (Bee & Kahle, 2006; Cousens, Babiak, & Bradish, 2006; McDonald & Milne, 1997; Towe r, Jago, & Deery, 2006), several ar eas of relationship marketing research in sport management need to be expanded and improved. First, previous relationship marketing research in sport management has not sufficiently focused on discovering unique aspects of the te am-sport consumer relationship compared to relationships in the context of the business-to-business market, industrial market, or other consumer markets. Given that a core value of research in applied areas including sport management does not lie in only re plicating the research findings from other disciplines but also

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17 in finding a way to properly appl y the findings to unique situations in the different areas, it will be beneficial to investigate the unique aspects of relationship marketing in the sport consumer market in addition to common features shared in both sport and genera l marketing contexts. Next, the previous relationship marketing research in sport management has seldom considered how individuals psychographic and demographic characteristics influence effects of team-sport consumer relationship on sport consumpti on behaviors. A better understanding of the psychographic and demographic factors that change the associati on between team-sport consumer relationship and sport consumption behavior will provide resear chers with insights to develop more comprehensive frameworks to ex plain sport consumption behavior within the team-sport consumer relationship. Knowledge of the impact of the psychographic and demographic factors will also en able practitioners to effectivel y develop a relationship marketing strategy by segmenting their consumers. Finally, va lidity of the research findings from current literature is questionable due, prim arily, to the lack of the empiri cal evidence in support of the models and results. Therefore, empirical research on relationship marketing in a sport context will be necessary to advan ce the body of knowledge on relationship marketing. Among the various academic and practical i ssues in relationship marketing, I am particularly interested in relationship quality for this dissertation. Relationship quality can be defined as an O verall assessment of the strength of a relationship, conceptualized as a composite or multidimensional construct capturing the different but related facets of a relationship(Palmatier, Dant, Grewal, & Evans, 2006, p138). The concept of relationship quality was introduced by Crosby, Evans, and Cowles (1990) nearly two decades ago based on Dwyer, Schurr, and Ohs (1987) semi nal article on relationshi ps and considerable effort has been devoted to investigating the vari ous topics about relations hip quality since then.

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18 The relationship quality concept is an importa nt research topic for three reasons. First, relationship quality can provide in sight into ways of distinguishing successful relationships from unsuccessful ones. Second, knowledge of relation ship quality helps id entify what kinds of problems exist in relationships and determine how those problems should be addressed. Finally, careful examination of relations hip quality can provide a valuable tool for evaluating the relationship marketing effectiveness as previous re search has shown that relationship quality is a key predicator of company performance such as customer loyalty (De Wulf, OdekerkenSchrder, & Iacobucci, 2001; Hennig-Thurau, Gwinner, & Gremler, 2002; Sirdeshmukh, Singh, & Sabol, 2002), word of mouth (Hennig-Thur au et al., 2002; Reynolds & Beaty, 1999), and expectation of continuity (Crosby et al., 1990; Doney & Cannon, 1997). It is reasonable to believe that sport team and sport consumer also can benefit from a be tter understanding of the relationship quality concept. Alt hough there is a vast amount of relationship quality research, a review of the extant work reveal s some limitations on current literature. First, there seems to be no consensus regarding the central constructs comprising relations hip quality and the structural nature of those constructs. In addition, very l ittle attention has been paid to the issue of relationship quality in sport consumer behavior contexts. Finally, ther e is no tested scale by which both researchers and practitioners in spor t management can measure the quality of teamsport consumer relationship and evaluate the effects of relationship marketing programs. Purpose of the Study The general goal of this di ssertation is to expand our knowledge of spectator sport phenomenon beyond current boundaries by applying re lationship theories to the team-sport consumer context. Particularly, the objective of this dissertation is to provide a better understanding of the nature of the relationshi p between team and sport consumers, and the impact of the relationship on various sport c onsumption behaviors. The following research

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19 questions are investigated thr oughout the dissertation: (1) What primary constructs can best represent the quality of the relationship between team a nd sport consumers? (2) How are relationship quality constructs structured a nd cognitively evaluated? (3) How much do the relationship quality constructs influence sport consumption beha viors? (4) What behavioral aspects of sport consumers are most influenced by the relationship quality? (5) To what extent is the association between relationship quality and sport consumption behaviors different across individuals and contexts? (6) What are the unique aspects of the team-sport consumer relationship compared to the genera l firms-consumer relationship? To answer these questions, first I developed a framework (Figure 1-1).The intent of the framework is to offer a conceptual foundation for applying relationship theo ries to explain sport consumption behaviors. This framework descri bes the primary components of relationship quality and structure of relationship quality c onstructs, the relationship between relationship quality constructs and sport consumption behaviors, and the role of potential moderators on the relationship between relationship quality construc ts and sport consumption behaviors. Next, I designed a multi-phase and multi-method study to em pirically examine the theoretical model of relationship support for the theoretical framewor k while maintaining a focus on the development of psychometrically enhanced instruments to measure relationship quality constructs, sport consumption behavior constructs, and relational personality traits Furthermore I applied recently developed statistical techniques for anal yzing data and testing the model.

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20 Figure 1-1. A conceptual framework of relationshi p quality and its effects on sport consumption behaviors

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21 CHAPTER 2 LITERATURE REVIEW I begin the following section with an overv iew of relationship marketing theory. The definition of relationship marketing is then br iefly discussed. Next, I develop a conceptual framework to investigate the research questions by first reviewing the current literature on relationship quality constructs and the structural nature of the relationship quality, then by discussing the consequences of relationship quality, and finally by exploring potential moderators of the relations hip between relationship qua lity and its outcomes. Relationship Marketing Since Berry (1983) first introduced the term relationship marketing in the services marketing area, relationship marketing has grown tremendously both in practice and academia. The growth of relationship marketing is due to the general belief that relationship marketing efforts can build stronger customer relationships that lead to imp rovement in seller performance outcomes such as sales, market share, and pr ofits (Crosby et al., 1990; Morgan & Hunt, 1984). The domain of relationship marketing research ha s extended to the sub-disciplines of marketing. These include business to business marketi ng (Doney, Barry, & Abratt, 2007; Dwyer et al., 1987; Keep, Hollander, & Dickinson, 1998; Naude & Buttle, 2000), sales management (Boles, Johnson, & Barksdale, 2000; Boorom, Goolsby, & Ramsey, 1998; Brashear, Boles, Bellenger, Brooks, 2003; Smith & Barclay, 1997), brand management (Fournier, 1998; McAlexander, Schouten, Koenig, 2002; Parvatiayar & Sheth, 20 01; Smit, Bronner, & Tolboom, 2007) channel relationship (Nicholson, Compeau, Sethi, 2001 ; Robicheaux & Coleman, 1994; Weitz & Jap, 1995), service marketing (Berry 1995; Evanschitzky, Iyer, Pla ssmann, Niessing, & Meffer, 2006; Hennig-Thurau et al., 2002; Gr onroos 1995; Gwinner, Gremler, & Bitner, 1998; Robert et al., 2003), consumer marketing (Garbarino & Johnso n, 1999; Odekereken-Schrder, De Wulf, &

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22 Schumcher, 2003; OMalley & Pr othero, 2004; Sheth & Parvatiy ar, 1995), and international marketing (Bello & Gilliland, 1997; Sin, et al., 2 005; Pan & Tse, 2000 ). Relationship marketing also has been the focus of research in vari ous industries such as banking (Liang & Wang, 2007; Molina, Martin-Consuegra, & Esteban, 2007; Prince, 1989), information technology (IT) (Eastlick, Lotz, & Warrington, 2006; Gruen, Os monbekov, & Czaplewski, 2006; Sigala, 2006), the automobile industry (De Hildebrand E Grisi & Ribeiro, 2004; Morgan & hunt, 1994), retail business (Fullerton, 2005; Srin ivasan & Moorman, 2005), heal th care (Paul, 1988; Naidu, Parvatiyar, Sheth, & Westgate, 1999; Wrright & Taylor, 2004), advertising (Beltramini & Pitta, 1991; Davies & Palihawadana, 2006; So, 2005), hos pitality (Essawy, 2007; Kim, 2006; Kim & Cha, 2002), nonprofit organizations (Helen & Deborah, 2006; MacMillan, Money, Money, & Downing, 2005; Simon & Colin, 2007), leisure (lvarez, Martin, Casielles, 2007; Morais, Dorsch, & Backman, 2004; Peters, 2004; Tseng & Wu, 2005), and the sport industry (Bee & Kahle, 2006; McDonald & Milne, 1997; Tower et al., 2006). Overall, it seems that relationship principles have essentially superseded the s hort-term exchange scheme in both marketing research and practice (Pal mtier et al., 2006). Definitions of relationship marke ting have been as varied as the disciplines and contexts in which relationship marketing has been researched. Therefore, I briefly discuss the literature on conceptualization of relationship marketing and present the definition of relationship marketing on which I base our conceptual model of rela tionship quality. Berry (1983) suggested that, Relationship marketing is attracting, main taining and--in multi-service organizations-enhancing customer relationships (Berry, 1983, p.25). Since then, many scholars have proposed various definitions to capture the nature of relationship marketing (Gronroos, 1994; Kotler, Bowen, Makens, 1996; Morgan & Hunt, 1984; Sh eth & Parvatiyar, 2000). Although these

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23 definitions vary in perspectives and approaches, they typically identify three fundamental aspects of relationship marketing: process, purpose, and parties (Sheth & Parvatiyar). First, the definitions emphasize the process aspect of relati onship marketing and the prevailing idea is that the process is characterized by establishment, enhancement, and mainte nance of relationships. Next, there is general agreement that the purpose of relationship marketing is to achieve benefit for all parties involved in the relationship. Finally, by its very nature, relationship marketing has entities who participate in relational exchange s with a focal firm a nd the nature of the relationship differs by the type of partners. Morgan and Hunt sugge sted that there were ten types of partners: (1) goods suppliers; (2) serv ice providers; (3) competitors; (4) nonprofit organizations; (5) government; (6) ultimate customer s; (7) intermediate customers; (8) functional departments; (9) employees; and (10) business un its. For the purpose of th e current research, I focus on the ultimate customers, in our case, sport consumers, as relationship partners. Thus, based on the previous literature, I propose th e following: Relationship marketing to sport consumers is a set of marketing activities to establish, enhance, and maintain a relationship with sport consumers for the benefit of both sport team and sport consumers. Relationship Quality Construct Many researchers have offered various lists of relationship quality constructs. After closely reviewing the literature pertai ning to components of relations hip quality I identified seven constructs that are commonly claimed to capture the essential facets of relationship quality. The constructs that I have included in my conceptual model are trust, commitment, satisfaction, love (liking), intimacy, self-connection and reciprocit y. I elaborate on each of these constructs below. Trust Trust typically has been considered as a cr itical component of a successful relationship (Garbarino & Johnson, 1999; Dwyer, et al., 1987; Morgan & Hunt, 1994; Palmatier et al., 2006).

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24 Anderson and Weitz (1989) defined trust as one partys belief that its needs will be fulfilled by actions undertaken by the other party (p. 312). Tr ust was also defined as a willingness to rely on an exchange partner in whom one has confidence (Moorman, Deshpand, & Zaltman, 1993, p. 82). Both definitions emphasized that confidence is an essential part of trust. Morgan and Hunt (1984) suggested that trust is based on a judgment that the relations hip partner is reliable and has high integrity and they defined trust as confid ence in an exchange partners reliability and integrity (p. 23). Trust has been br oadly investigated in the social exchange literature and other areas. Trust has been considered to be the f oundation of cooperation (John, 1984; Nicholson et al., 2001). Morgan and Hunt found that trust re duced opportunistic behavior and conflict in relational exchanges. They also found that trust encouraged c ooperative behavior. Berry (1995) argued that trust can reduce customers perceived ri sk in service, which is inherent because it is difficult for customers to determine quality of serv ice before they experien ce it. In addition, trust has been found to influence various seller performa nce objectives such as ma rket share, sale, and profit (Doney & Cannon, 1997; Reynolds and Bea tty, 1999; Siguaw, Simpson, & Baker, 1998; Palmatier, et al., 2006). Some researchers have te nded to highlight types of trust that can be found in person-to-person relati onships such as employee-employer and salesperson-customer relationships. However, Morgan and Hunt claimed th at trust was critical to all types of relational exchanges. Garbarino and Johnson(1999) also suggested that consume rs trust could be put in an organization as well as a person. Th ey argued that the consumers tr ust in the organization is the consumers confidence in the quality and reliabil ity of service or in the product offered by an organization in the same way as the consumers tr ust in an individual partner is the confidence in quality and reliability of an action taken by indi vidual partners. Therefore, rather than focusing on trust in individuals, I investig ate customers trust in a sport team, which reflects customers

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25 beliefs about the quality and reliability of va rious services provided by the team, following Garbarino and Johnsons approach. Commitment Like trust, commitment has been identified as a vital component of su ccessful relationships (Dwyer, et al., 1987; Garbarino & Johnson, 1999; Morgan & Hunt 1994; Palmatier et al., 2006). Commitment has generally been defined as an exchange partner believing that an ongoing relationship with another is so important as to warrant maximum efforts at maintaining it; that is, the committed party believes that relationship is worth working on to ensure that it endures indefinitely (Morgan & Hunt,1984, p. 23). Levy and Weitz (2004) stated that commitment is one of the major characteristic s that differentiate relational partnerships from functional relationships. Morgan and Hunt found that commitment had a positive influence on acquiescence and cooperative behavior, but commitment had a ne gative influence on propensity to leave. Also, it has been shown that strong commitment results in improvement of sales, market share, and profits (Doney & Cannon, 1997; Reynolds and B eatty, 1999; Siguaw et al., 1998; Palmatier et al., 2006). Relationship Satisfaction Satisfaction with the relationship has been regarded as an important measure of relationship quality (Garbarino & Johnson, 1999; Odekerken-Schorer et al., 2003; Palmatier et al., 2006; Roberts et al., 2003). Relationship satisfaction can be de fined as customers affective or emotional state toward the relationship with a brand or firm based on the overall evaluation of the relationship (Garbarino & Johns on; Odekerken-Schorer et al.; Palmatier et al.; Roberts et al.). Note that relationship sati sfaction in our study reflects cumulative evaluation over the course of relationship rather than tran sactional or encounterspecific evaluation. In addition, relationship satisfaction differs from general satisfaction b ecause the former exclusively refers to the

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26 customers satisfaction with the relationship with a brand or firm but the latter describes the customers satisfaction with the overall exchan ge. Odekerken-Schorer et al. (2003) found that the customers tended to be more satisfied with the relationship with a firm when the customers perceived higher level of the firms customer retention orientation. Crosby et al. (1990) suggested that relationship sati sfaction resulted in high sales effectiveness and more future interaction. In addition, relationship satisfaction has been found to positively influence sales, market share, and profit (Palmatier et al., 2006). Self-Connection Self-connection has been frequen tly recognized as an essential indicator of the relationship quality (Smit et al., 2007; Swaminathan, Pa ge, & Grhan-Canli, 2007; Thorbjrnsen, Supphellen, Nysveen, & Pedersen, 2002). Fournier (1998) stated th at self-connection is a relationship quality facet [tha t] reflects the degree to which the brand delivers on important identity concerns, tasks, or themes, thereby ex pressing a significant aspect of self (p. 364). Strong self-connections guide cu stomers to maintain the rela tionship through developing the protective feelings of uniqueness and dependency (Drigotas & Rusbult, 1992). In addition, high levels of self-connection encourage customers to stay in the relationship when they face adverse circumstance (Lydon & Zanna, 1990). Self-connection to brand or organization parallels team identification. Theoretical origin of both concepts can be traced back to the identity theory (Stryker, 1968), which noted that individuals assume multiple roles (identities) that represent who they are and these identities guide the indi viduals behavior. Although team identification has not been investigated within a relationship quality framework, it has been considered to be a key factor to explain various sport consumer behaviors (Trail, Anderson, & Fink, 2005). Team identification has been found to influence expect ancies for event experience and outcome (Trail, Fink, & Anderson, 2003), intention to attend ga mes (Matsuoka, Chelladurai, & Harada, 2003),

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27 and actual attendance (Laverie & Arnett, 2000 ). Moreover, Sutton, McDonald, Milne, and Cimperman (1997) suggested that highly identified fans were less price-sensitive. Wann (2006) claimed a higher level of identification with a local team positively influenced the psychological health of fans. Love Several researchers have recogni zed that love is an importa nt construct to understand the nature of relationships (Fournier, 1998; Nicholson et al., 2001; Pawle & Cooper, 2006; Smit et al., 2007). Fournier suggested that love is an em otional feeling that embraces warmth, affection, passion, infatuation, and obsession. While some resear chers suggested that a customers love of a company or objects might not be wholly analogo us to interpersonal love (Oliver, 1999), the literature generally supported that a customers love of a company or objects and interpersonal love are fundamentally similar in many contexts (Thompson, MacInnis & Park, 2005; Thorbjrnsen et al., 2002). Love has been consid ered to be a strong motivator for developing and maintaining human relationships (Sternberg, 1986 ). Previous research has shown that love attenuated negative consequences of relationship problems (Rus bult, Verette, Whitney, Slovik, & Lipkus, 1991), influenced judgment on attribut ing blame (Bradbury & Fincham, 1990), and positively biased the perception of the partner (Murray, Holmes, & Griffin, 1996). Intimacy Several researchers have identified intimacy as a fundamental component of relationship quality (Barnes, 1997; Smit et al., 2007; Fl etcher, Simpson, & Thomas, 2000; Monga, 2002). Much of the extant literature has focused on th e intimacy within romantic relationships and the term intimacy often refers to sexual feelings and physical contact, whic h were only experienced in the context of romantic relationships (Gaia, 2002). However, many social psychologists have also recognized and investigated non-sexual dime nsions of intimacy, which can be widely found

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28 in most relationships and they play a critic al role in relationships (McAdams, 2000; Hook, Gerstein, Detterich, & Gridley, 2003; Prager & B uhrmester, 1998). In the current study, I focus on non-sexual dimensions of intimacy and conceptu alize intimacy as the degree of familiarity, closeness, and openness to relati onship partners following Fournier (1998), who defines intimacy in the customer-brand relationship context. My de finition is also consis tent with Sternbergs (1986) definition, which also highlights that clos eness and openness are essential features that constitute intimacy in various relationship contexts Although intimacy might be interrelated with self-connection, intimacy is different from self-connection in that intimacy is a concept focusing on the distance between individuals and an organization while th e focal point of the self-connection concept is the ex tent of the overlap between an individuals self and an organization (Figure 2-1). Fournier emphasized that successful brand relationship was built on the higher level of intimacy between relations hip partners. In addition, intimacy has been considered to foster continuity of relationship by influencing perceptions of relationship partners (Murray et al., 1996), improving the effect of persuasive communica tion efforts, and facilitating conflict resoluti on (Stern, 1997). Reciprocity A strong and successful relationship is also characterized by a high degree of perceived reciprocity between relationship partners (De Wulf et al., 2001; Eyuboglu & Buja, 1993; Miller & Kean, 1997; Schwartz, Trommsdorff, Albert & Mayer, 2005; Uhl-Bien & Maslyn, 2003). According to Gouldner (1960), reciprocity is the generalized moral norm guiding social interaction among individuals and Gouldner stated that the generalized norm of reciprocity evokes obligations toward others on the basis of their past behavi or (p. 170). The principle of reciprocity states that when one benefits from another, the recipi ent should return the favor in proportion to what the other has done for him or he r. Until the recipient r eciprocates the benefit

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29 received from the donor, he or she is obliged or indebted to the giver (Gouldner). The importance of reciprocity as a guiding principle of social behavior has long been recognized. Cicero acknowledged, There is no duty more indispensabl e than that of return ing a kindness (Goulder, p. 161). Cialdini (1998) stated that the rule of reci procity is one of the mo st widespread and vital norms of human culture and society. He also emphasized that the de velopment of various relationships, transactions, and exchanges that are foundations of human society heavily depend on this sense of obligation or indebtedness. He also argued that all members of society learned from childhood that they should abide by the rule or they would be punished with serious social disapproval. Consequently, the reci procity rule often affects the decision to agree to anothers request. Cialdini suggested that giving something to others would be a very useful tactic for persuasion because of the three characteristics of the principle of recipro cation: (1) the principle of reciprocity is exceptionally st rong and it frequently dominates th e impact of other factors that generally influence the decision to comply with a re quest; (2) the principle is in effect even in a situation that the initial favor was not invited by recipient, which li mits an individuals choice in deciding whom he or she wants to owe and allows others to have the choi ce; (3) the principle can stimulate unequal exchanges. An individual often willingly returns a considerably larger favor than the one he or she first was given to be free from uncomfortable feelings of obligation or indebtedness. In general, reciprocity has been considered to be a key factor in pred icting the duration and stability of an exchange rela tionship (Larson, 1992). In addi tion, Gouldner (1960) noted that reciprocity plays a critical role as a star ting mechanism as well as stabilizing function. Reciprocity has frequently been c onsidered as a key variable of in terest in channel relationships (De Wulf et al., 2001). For example, Smith and Barclay (1997) found that perceived reciprocity

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30 in channel members increase perceived task perfo rmance by selling partners reduced barrier of risk, and therefore motivated parties to conti nue the relationship. UhlBien and Maslyn (2003) investigated the reciprocity in manager-subordinate relationships a nd they reported that perception of positive reciprocity in manager-subordi nate work relationships and performance of subordinates was positively associated. In the co nsumer behavior realm, Bagozzi (1995, p175) highlighted reciprocity as the co re of marketing relationship a nd stated that the principle of reciprocity could apply to customer-firm rela tionships as well. He also emphasized that relationship marketing research should furthe r examine the psychological manifestation of reciprocity and the way it serves its role in relational exchanges between consumer and firm. When consumers perceived that they have a recipr ocal relationship with a brand or store, they respond to an unsatisfactory quality of produc t or service by collaborating and compromising (Kaltcheva & Weitz, 1999). Miller and Kean (1997) found that in a rural community, reciprocity was the strongest motivator for maintaining a relationship with local retailers. In a leisure context, Morais et al. (2004) re ported that tourists perceived r eciprocity in tourist-provider relationships encouraged the to urist to resist changing providers when they faced counter persuasion. Structural Nature of Relationship Quality This multi-faceted array of relationship quality factors raises an essential question: How are these constructs evaluated and structured? Th ere might be several possible solutions for the question. In the following section, several types of models that differ by restrictions on the models will be discussed. After the theoretical discussion, four models were empirically tested. General Relationship Quality Factor Model Although I hypothesize that relationship qual ity incorporates the seven distinct constructs, it is possible that relationship quality is one global factor that collapses across the

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31 seven individual aspects: trust, commitment, satisfaction, love (l iking), intimacy, selfconnection, and reciprocity. Acco rding to this explanation, th e individual dimensions of relationship quality do not exist as distinct conceptual constructs. This model is depicted in the Figure 2-2. Although this model can be considered to be a starting point to empirically determine how many common factors are measur ed by all the indicator variable s in an exploratory way, the model is not theoretically plausible because pr evious research genera lly identified the seven factors as distinctive conceptual factors (Fletcher et al ., 2000; Morgan & Hunt, 1984; Fournier, 1998; Roberts et al., 2003). Independent Factor Model The second possibility is that the seven c onstructs of relationship quality (trust, commitment, satisfaction, love (liking), intim acy, self-connection, and re ciprocity) are distinct facets of relationship quality and they are comple tely independent. This m odel is illustrated in Figure 2-3. This model and the general relationship quality factor model are at the opposite ends of the spectrum in terms of uniqueness of the individual domains of relationship quality. The former states that there is no di stinct sub-domain of relationship qua lity and all the indicators are completely accounted for by one global factor of relationship quality. However, the latter suggests that each sub-domain of relationship qu ality represents completely unique aspects of relationship quality. Although the independence or orthogonality of the underlying dimensions is often assumed in certain types of classic exploratory factor analys is, similar to this independent factor model, the model is not theo retically plausible. First, in so cial science, it is unrealistic to hypothesize that all the theoretica l constructs of cons ideration in any st udy are completely uncorrelated. In addition, previ ous research has shown that the seven constructs of relationship quality are correlated to each other (G arbarino & Johnson, 1999; Mogan & Hunt, 1984; Nicholson et al., 2001; Stern, 1997; Uhl-Bien & Maslyn, 2003).

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32 Group Factor Model The third possibility is that the seven constr ucts of relationship quality reflect distinct facets of relationship quality and they are corre lated with each other to a certain extent. However, no higher order relationship quality cons truct is specified. According to this model, individual sub-domains of relati onship quality represent more of a unique aspect of relationship quality than common aspects. This model is s hown in Figure 2-4. This type of model is a reasonable explanation of factor structures when a specific structure that would account for the relationship among the first order factors is not known (Kline, 2005; Rindskopf & Rose, 1988). In addition, this type of model is particularly plausible if there is a theore tical justification that the factors in the analysis are correlated with each other. For example, many researchers have investigated motivational factors for sport consum ption behavior and have developed scales to measure those factors (Milne & McDonald, 1999; Trail & James, 2001; Wann, 1999). They typically have specified that the factors are unconstrained in the c onfirmatory factor analysis and the group factor model has been considered to ex plain the structure of mo tives best because the motives have shown to be correlated with each ot her but a consistent structure that accounts for relationship of the motives has not been found. The breadth and diversity of the motivational factors identified in sport consumption beha vior might account for the finding. The seven constructs of relationship quality have been cons idered to be interrelate d with each other in the previous research (Garbarino & Johnson, 1999; Johnson & Grayson, 2005; Morgan & Hunt, 1984; Nicholson et al., 2001; Sin et al., 2005; Stern, 1997; Uhl-Bien & Maslyn, 2003).The correlation between those constructs vary across the contexts but they typically ranged from .25 to .80. However, there is limited research co ncerning the measuremen t structure of those constructs. Therefore, we propose th at the group factor model, whic h specifies that all factors are

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33 correlated with each other but ar e not represented by a higher orde r factor, is a competing model to explain the structure of relationship quality constructs in cluded in this study. Second-Order Hierarchical Model The next possibility is that the relationship quality constructs ar e manifestations of a global or higher order construct of relati onship quality. This model suggests that each relationship quality construct can be measured by items or observed variables corresponding to one of the seven relationship quality construc ts and these individual constructs reflecting different aspects of relationship quality are indicators of the more general, higher-order latent relationship quality constr uct. This model is depicted in Figu re 2-5. This type of model can be justified when people make evaluative judgments on different but relate d conceptual domains consistently based on a broader conceptual node. For example, Tr ail and Robinson (2005) proposed that an individual might be identified with seven different points of attachments such as the players, the coach, the university, the sport, th e level of the sport (e. g. college opposed to professional), and the community, as well as the team. Later, Kim and Trail (2007) found identification with those different points of at tachment converged to an overall perception of identification. Although there is limited research on the structur e of relationship quality, a few studies suggested that relationshi p quality might be a global cons truct that can be reflected by various sub-dimensional factors. DeWulf et al. (2001) identified relations hip satisfaction, trust, and relationship commitment as primary relationship quality constructs a nd they are specific subdimensions that make up more abstract re lationship quality per ception. Fournier (1994) emphasized that behavioral interdependence, love/passion, personal commitment, self-concept connection, intimacy, partner quality, and nostalgic connection are major facets of relationship quality. Fournier also suggested th at these facets are distinct but interrelated sub-dimensions that homogeneously represented genera l relationship quality, which wa s a higher-order construct.

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34 Similarly, Fletcher et al. (2000) reported that satisfaction, co mmitment, intimacy, trust, passion, and love were critical components of perceived relationship quality and they were consistent reflections of ones overall att itude toward relationship. Base d on the theoretical discussion above, I determined that the second-order hierar chical model provides a plausible account for the structure of the relationship qua lity constructs in our study. Modified Second-Order Hierarchical Model Another possibility is that the relationship quality constructs are manifestations of more than two second-order constructs of relationship quality. This model suggests that first-order relationship quality constructs ta p not one but two or more sec ond-order relationship quality subdimensions. The second-dimensions are correlated but distinct. Thus, no th ird-order relationship quality constructs are specified. Th is model is illustrated in Figure 2-6. This type of model can be a tenable explanation when a psychological concep t refers to a wide range of sub-dimensional constructs and those sub-dimensions do not conver ge to single global dime nsions but to two or more higher-order dimensions (Kline, 2005; Rindskopf & Rose, 1988). For example, Oliver (1997) suggested that attitudina l brand loyalty was divided into three distinct conceptual categories: cognitive, affective, and cognitive doma ins of attitudinal brand loyalty. This is also consistent with general acceptance of the idea th at attitude is multi-dimens ional rather than unidimensional (Ostrom, 1969; Bagozzi & Burnkr ant, 1980). Although there is limited research on second-order dimensions that consist of overall relationship quality pe rception, Fournier (1994) argued that relationship quality could be divided into two main categories (i.e., affective and cognitive/behavioral domains), which is reflected by a lower-order latent factor. Similarly, Smit et al. (2007) reported that bra nd relationship quality was a two-di mensional construct. The first domain contained passionate attachment, in timacy, and connection, while the second domain contained trust, personal commitment, and love. Based on the theoretical discussion above, I

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35 propose the modified second-order model as a co mpeting model. This model hypothesizes that first-order relationship quality constructs tap two correspond ing second-order constructs: cognitive (i.e., trust, commitment, satisfaction, and self-connection) and affective (i.e., love, intimacy, and reciprocity) dimensions. Predictive Value of Relationship Quality Although relationship quality constructs are valu able in their own right, a crucial issue in the research of relationship quality is to examine predictive cap acity of the relationship quality constructs. How well do relationshi p quality constructs predict managerially relevant sport consumption behavior? Literature reveals four behavioral aspects of interest in sport management: Word of Mouth, Merchandise consumption, media consumption, and attendance. After a note on the relationship between intention of behavior and actual behavior, I will present a model to address the question about the rela tionship between relations hip quality and sport consumption behavi or (Figure 2-7). Behavioral Intention The prediction of actual sport consumption beha vior is of principal interest in sport management. However, deciding which specific c onstruct and measure should be used to best predict the actual sport consump tion behavior has been a major issue. Consumers self reported intentions of behavior have been most fr equently employed in academia and practice in marketing. For example, most scholarly works on satisfaction have utili zed repurchase intention as the criterion variable and pr actitioners typically depend on pur chase intention data to make predictions about consumers initi al purchase of new products or the repeat purchase of existing products (Chandon, Morwitz, & Reinartz, 2005). Although it is generally admitted that participants self-reported intentions do not always accurately forecast their future behavior and the strength of relationship be tween self-reported intention and the actual behavior are

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36 considerably influenced by severa l factors (Morwitz, Steckel, & G upta, 2007), using intention as a measure to predict or explain actual behavi or can be justified by following theoretical and practical reasons. First, many theoretical frameworks of consumer behavior have conceptualized that intention is a proximate psychol ogical construct for actual behavi or. For example, Fishbein and Ajzen (1975, p. 368-369) noted, if one wants to know whether or not an individual will perform a given behavior, the simplest thing one can do is to ask the individual whether he intends to perform that behavior. Wars haw (1980) suggested that most conceptual frameworks of consumer behavior characterized intention as a critical mediator between attitude and choice behavior, which indicated that intention was a be tter psychological measure than belief and other cognitive measures. In addition, Mo rwitz et al. (2007), using meta-a nalysis, found that intentions are generally predictive of future behavior and the variation in predictive or explanatory power of intention could be accounted for by types of products and the way that the data was collected. Specifically, Morwitz et al. found the following: Intentions are more correlated with purcha ses (1) for existing products than for new products; (2) for durable products than for non-durable product s; (3) when respondents are asked to provide intentions to purchase specific brands or models than when they are asked to provide intentions to buy at the product category level; (4) when purchase levels are measured in terms of trial rated rather that total market sales; (5) for short time horizons than for long time horizons: and (6) when inte ntions are collected in a comparative mode than when they are collected monadically (p. 361). Based on these findings, Morwitz et al. further suggested that intention could be a useful predictor of future behavior if researchers have knowledge about the contextual factors that affect the strength of the intenti on-behavior relationship and ability to properly interpret intention scores in various situations based on the knowledge of those f actors. In sport consumption behavior context, Trail et al. ( 2005) suggested that beha vioral intention is a preferable predictor of actual sport consumption behavior. In additi on, Trail, Anderson, and Lee (2006) examined the

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37 relationship between spectators intention to at tend a specific teams games in preseason and their actual attendance during the season. Their result showed that preseason attendance intention accounted for 45% of variance in actual attendance, indicating intention to attend sporting events is a significant predicto r of actual attendance. Utilizing intention as a proxy of behavior is also justified beca use it is a practical alternative to actual behavior. Examining the relationship between variables of interest and consumers self-reported behavior al intention is typically more time and cost efficient than investigating relationships between those variable s and the consumers future behavior because the former does not require a longitudinal study. Moreover, there are various forecasting models to convert intentions to actual behavior that are now easily available. For example, Jamieson and Bass (1989) introduced several conve rsion schemes that researcher s and marketers can employ to predict actual purchase behavior from intentions scores. Using previous st udies that have information about the consumers purchase intent ion and then following their actual purchases, Jamieson and Bass attained the conversion rates that were applied to meas ure purchase intentions to estimate future purchases. In addition, Morw itz et al. (2007) described how the conversion rates for intention scores can be modified by the ch aracteristics of the stud ies. Therefore, current studies focus on the relationship be tween relationship quality constr ucts and behavioral intention in lieu of actual behavior. Word of Mouth Word of mouth refers to a behavior in which a consumer informally communicates experience, evaluation, and recomm endation of goods or services with other potential consumers (Anderson, 1998). Word of mouth co mmunication is a highly influe ntial factor in consumers purchasing decisions and often more powerful than other promotional methods that can be used by marketers mainly because personal communica tion is perceived as a more trustworthy and

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38 dependable source than non-personal informati on (Hennig-Thurau et al., 2002; Zeithmal & Bitner, 1996). While consumers product awarene ss is largely improved by mass media, in many occasions word of mouth is more effective in influencing the actual purchasing decision (Bayus, 1985). Previous literature frequently refers to wo rd of mouth as a key outcome of relationship quality constructs. Palmatier et al. (2006) reported that relationship quality explained on average 37% of variance in word of mouth across 17 diffe rent empirical studies in a consumer products context. In a service products context, Hennig-Thurau et al. ( 2002) found that more than 35% of variance in word of mouth was accounted for by relationship quality. Thus, word of mouth can be viewed as a critical outcome of team-spectator relationship quality. Media Consumption One of the unique characteristics of sport consumption is that sport consumers can consume the product through the media such as te levision, radio, and inte rnet. Development of media has changed the way sport is consumed a nd the sport industry. The sport media segment is the financial base of the sport industry. A ccording to Howard and Crompton (2005), U.S. consumers spent almost $13 billion on media sport consumption. Increasing media related consumption of a team is essential for the success of the organization. Established and marketable teams that can attract a large audience can enjoy subs tantial revenue from broadcast rights. In addition, media consumption level is closely related to the teams sponsorship solicitation and licensed product sales (Goff & Ashwell, 2005). Consequently, not only professional organizations but also collegiate athletic programs ha ve become more interested in the level of media consumption. Although no research has directly investig ated the association between relationship quality and level of media consumption, previous research on relationship quality generally suggests that relationship qua lity is a crucial predictor of behavioral dependence (Fournier, 1998). That is, customers who perceived high quality relationship with a

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39 brand or company do not only buy more products from the brand or the company but also expand scope, diversity and freque ncy of brand-related or company-related activities. Hence, I expect that the fans who percei ve a higher level of relationship quality intend to consume sport through media. Licensed Products Sport-related licensed products are any and all products bearing the name or logo of a sports team, which manufactures use, sell, and offer for sale th rough licensing contract with the league or team. Retail sales of sport-related licensed products in the U.S. and Canada were estimated to be worth $13.23 billion in 2005 ( Licensing Letter Survey, 2006). The sale of licensed products has been a majo r area of interest for sport mana gers and marketers due to the following reasons. First, licensi ng is major revenue source for teams and leagues. In the 2005 fiscal year, licensed apparel sales for the Natio nal Football League (NFL) totaled $1.58 billion (Brochstein, 2006). Next, licensing enables teams and leagues to e nhance awareness and interest as well. No research has empirically examined the relationship between relationship quality and level of licensed product consumption. However, it has been shown that a higher level of relationship quality led to positive attitude towa rd brand extension (Park, Kim, & Kim, 2002), implying that consumers who perceive good relati onship quality are more likely to buy products which use the same brand name. In addition, it has been well documented that fans use teamlogoed items to support their teams or to show th eir affiliation with the teams (Cialdini et al., 1976). In line with these research findings, I pr opose that fans who perceive a higher level of relationship quality will intend to buy more licensed products. Attendance Increasing attendance is a primar y objective of sport managers and marketers. Ticket sales account for approximately 20% to 50% of the to tal revenues for professional teams in Major

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40 League Baseball, the National Football League, the National Basketball League, and National Hockey League (Badenhausen et al., 2007). Ev en higher proportions of total revenue are generated from ticket sales for the teams at the collegiate level and minor leagues across various types of sport (Howard & Crompton, 2005). In a ddition, the revenue from the sale of on-site game day concessions, merchandising, and parkin g, which was $8.84 billion a year in the U.S., is also contingent on attendance (Broughton, Lee, & Netheny, 1999). Accordingly, attendance or intention of attendance has been the most fr equently employed outcome variable in sport management research. No researcher has inve stigated how relationshi p quality influences attendance (or intention to attend a sporting event). However, prev ious literature on relationship quality typically indicated that relationship quality had positive influence on consumers intention to purchase. Hennig-Thurau and Klee ( 1997) suggested that relationship quality is a predictor of repeated purchase behaviors. So me empirical evidence has been found as well. Palmatier et al. (2006) reported that relationshi p quality accounted for an average of 52% of variance in purchase intention in the 50 empirical studies in the consumer products context. Moreover, Fournier (1994) argued that brand relati onship quality is a better predictor of purchase intention than brand attitude and satisfaction because brand relationshi p quality explained 61% of variance in purchase intention, whereas bra nd attitude and satisfac tion explained 37% and 52% of variance in purchase in tention respectively. Derived from these findings, I expect that fans who perceive a higher level of relations hip quality intend to attend more games. Moderators of Relationship Qualitys In fluence on Sport Consumption Behavior Once the relationship between the relationshi p quality and the outcome variables is examined, the next question drawing our attentio n is how the direction and association of the relationship changes across many different situati ons. For whom or in which situation is the relationship between relationshi p quality and hypothesized outcome stronger or weaker? To

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41 address this issue, the author will identify a nd empirically examine th e influence of potential moderators on the relationship be tween relationship quality and s port consumption behaviors. In reviewing the literature, we focus on product category as well as psychographics and demographics of sport consumers, which might alter the relationship qua lity-purchase intention linkage. Moderator Effects A moderator is a third variable that change s the nature of the relationship between a predictor and an outcome (Baron & Kenny, 1986). The moderator effect is also called an interaction by which the effect of a predictor variable on an ou tcome variable changes as the value of a third variable changes. Discovering important moderators of relationships between predictors and outcome variables has been a vital theo retical and empirical issue in many social and behavioral science disciplines (Aguinis, Boik, & Pierce, 2001; Judd, McClelland, & Culhane, 1995). In addition, Cohen, Cohen, West, a nd Aiken (2003) stated th at identification of moderators is at the heart of theory in social science. Desp ite this continuing importance of interaction effects, empirical research on hypothesized moderators has been limited. Such scarcity of interaction effects appl ication is not due to a lack of relevant research questions that require examining interaction effects. Rather, th is is due to the difficulties for the applied researchers to properly implement th e statistical technique to test the interaction effects (Frazier, Tix, & Barron, 2004; Marsh, Wen, Hau, 2004; Rigdon, Schumacker, & Wothke, 1998). When both the predictor variable and potential moderator are categorical variables, researchers can easily test interaction effects with traditional analysis of va riance (ANOVA) procedure. When both predictor and potential mediat or are continuous variables, regressi on procedures are preferred over using ANOVA with an artificially dichotomized variable (Cohen et al., 2003). When a predictor variable is a latent conti nuous variable and a poten tial moderator is an

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42 observed categorical variable, a comparison of a m odel with cross-group equa lity constraints to a model without cross-groups equality using st ructural equation modeling (SEM) can provide a test of interaction effects (Klein, 2005). When each predicator and potential moderator is a latent continuous variable, interaction e ffects can be tested by including the latent product variable in the original model and testing if the latent produ ct variable is statistically significant (Algina & Moulder, 2001; Jreskog, 2000; Kenny & Judd, 1984). Despite the widespread use of SEM because of its advantages over traditional stat istical procedures that assume no measurement errors, there have been limited applications of SEM to test interaction eff ects of latent variables in the sport management area. In particular, th ere is a lack of resear ch on latent continuous variable interactions in sport management despite its th eoretical and practical importance. Therefore, better understanding of methods to identify potential moderators and test an interaction effect using SEM will make both a theoretical and practical contribution. Moderators of Relationship Qual ity-Relationship Outcome Linkage As mentioned in the earlier section of th is chapter, academicia ns and practitioners generally suggested that rela tionship quality positively infl uences consumers purchase intentions and purchases (Hennig-Thurau & Kl ee, 1997; Palmatier et al., 2006, Fournier, 1994). However, researchers also recogni ze that the strength of the associations varies with several moderating factors. Anderson and Narus (1991) suggested that exchanges vary across a continuum between pure transactional to pure rela tional. That is, relationships are not equally important in all exchanges and therefore, the influence of the relationship between consumers and sellers on outcomes differs by the importan ce of the relationships for those exchanges. Palmatier et al. identified three contexts in which the relationship is more critical than in other situations for a successful exchange. They stated that the cust omer-seller relationship is more important (1) for service exchanges than fo r product-based exchanges; (2) for exchanges

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43 between channel partners than for seller-customer exchanges (3) for business or industrial markets than for consumer markets. Moreover, they found that relationship quality influences seller objective performance sign ificantly more for service, channels, and business market exchanges than product-based, seller-customer, and consumer market exchanges. In addition, Fournier noted that personality traits such as relationship styl e, interpersonal orientation, and relationship value centrality moderated the strength of brand-consumer relationship. Fournier further added category involvement, gender, age, a nd education as moderators. However, there is limited research that empirically examined the effects of these hypothesized moderators on the relationship between relationship quality and beha vioral outcomes including purchase intentions. Furthermore there is a lack of re search that has explored the pote ntial moderators of relationship quality-behavioral outcome relati onship in sport consumer behavi or contexts. Therefore, an objective of our study is to iden tify and empirically examine the potential factors that might moderate the relationship between relationship qu ality and sport consumption behaviors. Based on the literature, I identified the following pot ential moderators of relationship quality-sport consumption behavior associati ons. This potentially moderating relationship is depicted in Figure 2-8 Product Category I choose classification of products as a poten tial moderator by which the impact of relationship quality on sport consumption behavior s might differ. I differentiate the spectator sport product from typical manufactured goods like toothpaste, computers, automobiles, etc. Gladden and Sutton (2005) stated that spectator sport products are differe nt from manufactured goods in the following ways: (1) spectator sport is less tangible; (2) spec tator sport is more subjective; (3) spectator sport is more experien tial; (4) spectator sport is publicly consumed and spectator satisfaction is influenced by social facilitation; (5) the quality of spectator sport is less

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44 consistent, less predictable, and less controllable; and (6) cons umers are more involved in the production. These aspects are consiste nt with the characteristics th at distinguish services from manufactured products (Zeithmal, Parasuraman, & Berry, 1985). According to Palmatier et al. (2007), the inherent interactions in the production and consumpti on of a service might make the consumer-seller relationship more important fo r services than manufactured products. In addition, the intangibility, inconsistency, and unpredictability of the se rvice offerings make relationship quality a more critical criterion for consumers because evaluation of other aspects is often ambiguous. Thus, I expect that the a ssociation between relationship quality and consumption behaviors, behavioral intentions in my case, will be str onger for spectator sport than general manufactured products. Psychographic Factors To reflect differences among consumers in ps ychological characterist ics which govern the association between relationship quality and sport consumption be haviors, I choose a number of psychographic factors as potential moderators. Operating on Fourni ers (1994) suggestion that an individuals brand relationship is consistently in fluenced by the personality traits that affect the individuals interpersonal rela tionships, I propose relational pers onality traits as potential moderators of relationship quality-sport consump tion behavior associatio ns. Following Fournier, I will include and measure relationship styles, relationship drive, and general interpersonal orientation in the current study. Based on Math ews (1986), Fournier id entified three primary relationship styles: independent, discerning, a nd acquisitive. Individuals who possess the independent relationship style easily start a relationship but main tain a distance and simply discontinue the relationship as the environment around their lives change. Individuals who possess the discerning relationship style selectively and slowly develop new relationships and maintain only a few strong relationships, but re lationships are not easily influenced by the

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45 individuals life circumstances. Finally, the indi vidual with an acquisitive relationship style is readily able to initiate new rela tionships, but also valu es the development of strong relationships and the retention of relationships. Consequently, these individuals tend to enlarge the number of relationships throughout their life-span. Reviewing Mathews (1986) desc riptions of three relationshi p styles reveals that the classification is based on two main characte ristics: relationship development style and relationship maintenance style. Figure 2-9 portrays Mathews re lationship categories in a two dimensional format. The horizontal dimension repr esents relationship development style. People who score high on this dimension t ypically are not afraid of interaction with new people, easily start a new relationship, quickly develop a rela tionship. The vertical dimension is based on relationship maintenance style. People who ar e rated high on this dimension do not easily end any relationship and tend to maintain long and strong relationships with others. Upper-right box, upper-left box, and lower-right box in the matrix represent acqui sitive, discerning, independent relationship style respectively. F ournier (1994) found that relations hip style, relationship drive, and interpersonal orientation influenced the perceived im portance of brand-consumer relationships to the consumers, implying that t hose relational personality traits moderated the impact of relationship quality on behavioral outcome. Similarly, I expect that individuals with different personality traits th at influence the interpersonal relationships carry those same personality traits into the spectator-team rela tionship domain. Therefore, relationship style will moderate associations between relationshi p quality and sport consumption behaviors. Summary In the preceding section, a considerable amount of the literature on relationship marketing and relationship quality has been reviewed. Relationship marketing has grown tremendously both in practice and academia. However, definitions of relationship marketing

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46 have been varied across disciplines and contexts. Therefore, I brie fly discussed the definitions of relationship marketing and proposed a definition of relationship marketing in the sport consumption context. Among the various academ ic and practical issues in relationship marketing, I focus on relationship quality in this study. I selected seven constructs (i.e., trust, commitment, relationship satisfac tion, self-connection, love, intimacy, and reciprocity) as critical components of relationship quality and discusse d possible measurement models (i.e., general relationship quality factor model, independent factor model, group factor model, second-order hierarchical model, and modi fied second-order hierarchical model). Media consumption, licensed-product consumption, and attendance we re discussed as outcomes of relationship quality. Motives were introduced as criterion explanatory variable s to evaluate the predictive value of relationship quality on those outcome variables. Furthermore, I identified product category and relational pe rsonality traits as potential moderators of the association between relationship quality and consumption behavior.

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47 Figure 2-1. Graphical comparison of intimacy and self-connection

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48 Figure 2-2. General relationship quality factor model

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49 Figure 2-3. Independent factor model

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50 Figure 2-4. Group factor model

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51 Figure 2-5. Second-order hierarchical model

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52 Figure 2-6. Modified secondorder hierarchical model

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53 Figure 2-7. Relationship between relations hip quality and consumption behavior

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54 Figure 2-8. Moderating effects on the relationship quality-consump tion behavior association

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55 Figure 2-9. Relationship style

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56 Figure 2-10. Relationship between motives and consumption behavior

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57 CHAPTER 3 METHODOLOGY To obtain empirical data on relationship qual ity, sport consumption behavior, relational personality traits, and demographics surveys were conducted both online and face-to-face. Data analysis was performed using va rious statistical techniques su ch as Confirmatory Factor Analysis (CFA), Structural Regression, and Mul tiple Sample Structural Equation Modeling. This chapter presents the methodology used in this study in the following order: (1) Participants and procedures (2) Instrumentation (3 ) Pilot study (4) Data analysis. Participants and Procedures The target population for this study was people 18 years of age or older who were affiliated with the University of Florida. Potential respondents were selected using the judgmental sampling method. This method is a type of non-pr obability sampling in whic h researchers select a sample to be observed based on the rese archers knowledge and judgment about the population, its elements, and the purpose of the study. This type of sampling method is considered to be a valid alternative to probabi lity samplings when it is unrealistic to obtain a truly random sample (which is true on many o ccasions in social science) and when the researchers reasonably believe that the chosen sa mple is representative of the entire population based on knowledge of the population (Babbie, 2007). Mail, telephone, face-to-face, and online modes are the most frequently used methods in social science research. Each mode has its own strengths and weaknesses in coverage, non-respon se rate, measurement quality, and cost. Mixedmode design is increasingly used as a way to reduce effects or bias of data collection modes on the survey results while balancing cost (G roves, Fowler, Couper, Lepkowski, Singer, & Tourangeau, 2004). The data were collected comb ining two major survey modes: face-to-face self-administered and online self-administered.

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58 Participants in face-to-face surveys were recr uited via visiting undergraduate and graduate classes, dining areas, and recreat ional sport facilities on campuses After agreeing to participate in the survey, participants we re given a brief explanation of the purpose of the study and instructions on filling out the survey. Then partic ipants were asked to complete the questionnaire about demographics, relationship quality, relational personality traits, and several behavioral aspects of sport consumption behavior. In compliance with Institutional Review Boards (IRB) protocol, informed consent process was ensure d. This process involved providing information on planned procedure in language appr opriate to the level of understanding of the participants and then requesting voluntary participation in accord ance with the Code of Federal Regulation. It took approximately 15 minutes for a respondent to complete a surv ey. Data were collected from 356 people who participated in f ace-to-face self-administered survey. Of these, 51 surveys were unusable, leaving a total of 305 usable responses. Online survey participants were recruited by sending an email that co ntained an invitation to participate in the online survey and a li nk to an Internet website on which the survey questionnaire was posted. Email lists were obt ained through class and college List-Serves and university homepages. The purpose of the study, de scription of planned procedure in language appropriate to the level of understanding of the pa rticipants, request of vol untary participation in accordance with the Code of Federal Regulation, and brief instructions for completion of the survey, was included in the first part of the que stionnaire. Informed consent was obtained by the respondents reading the cover letter and choosing to fill out the survey posted on the Web page. The survey was closed one week after the invitation was sent. Participants received a thank you notice after they completed the survey. The data was stored on a server provided by an online survey company and the data was downloaded at the end of data collection. E-mail was sent to

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59 2100 email addresses. Of these 2100 email addresses, 23 e-mails were returned as undeliverable, leaving 2077 effective email addresses. A total of 254 responded, for an effective response rate of 12%. Of these, 63 surveys were unusable, le aving 191 usable responses. Thus, a total of 496 were useable across both the face-to-face and web surveys. Instrumentation The questionnaire was comprised of four main parts: relationship quality constructs, relational personality trai ts, relationship quality outcomes, and demographics. Items in each part were randomly placed in order to avoid response bias from order effect. The instrumentation process included the following steps: (1) item se lection and modification, (2) expert review, and (3) pilot study. Item Development Relying on previous literature, items for meas uring seven relationshi p quality constructs, four relationship outcomes, four relational person ality trait constructs, and demographics were selected and modified. Relationship quality The first part measuring relationship quality consisted of 7 subscales (Trust, Commitment, Relationship Satisfaction, Self-connection, Intim acy, Love, and Reciproc ity) represented by a total of 52 items. Although most of the measures for the relati onship quality constructs examined in this study are available in th e current literature, th e items used to measure the constructs were inconsistent across studies. The items that were believed to be most appropriate for this study and had shown good psychometric properties were initially selected. Then the selected items were modified to suit the spectator sport contex t. Two versions of the relationship quality scale were included in the survey. One version wa s designed to measure consumers perceived

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60 relationship quality regarding a s port team (i.e., the UF Football team) and the other one focused on a brand in the manufactured product industry (i.e., iPod). Three items from Fletcher et al. (2000), 1 it em from MacMillan et al. (2005), and 1 item Morgan and Hunt (1994), respectiv ely, were selected and those items were modified to measure Trust. To measure Commitment, 3 items were c hosen from Fletcher et al. and 2 items were chosen from Fournier (1994). The items were re vised. Three items from Fletcher et al. and 2 items from Spake, Beatty, Brockman, and Crutch field (2003) were select ed and the items were reworded to measure Relationship Satisfaction. Four items from Fournier were adopted and then those were modified to measure Self-connection. Three items from Fletcher et al., 3 items from Fournier, and 3 items from Spake et al. were selected and those were reworded to measure Intimacy. Two items from Fournier and 3 items from Fletcher et al. were chosen and modified to measure the Love factor. In order to measure Reciprocity, 5 items from Uhl-Bien and Maslyn (2003) were modified and 1 item was generate d based on the literatu re on reciprocity. The number of response categories can influence answers (Groves, et al., 2004). When too few options are presented, the rating scale ofte n cannot differentiate among participants with different underlying judgments. Wh en too many options are presented, participants might not be able to accurately discern the difference between categories. Response theory literature generally suggests that seven scale points is the best compromise (Krosn ick & Fabrigar, 1997). Therefore, all items were answered on a 7-poi nt Likert-type scale. Point 1 on this scale demonstrated strong disagreement with a statement, point 7 indicated strong agreement, and point 4 indicated neither agreement nor disagreement. Relationship quality outcome variables The second part measuring rela tionship quality outcome vari ables included 4 subscales with 12 items (Sport Media Consumption, Lice nsed Product Consumption, Attendance, and

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61 Purchase). Measures for these constructs were readily obtainable from the current literature. However, items used to measure the construc ts had varied considerably across studies. Therefore, items that were considered to be mo st suitable for the purpose of this study and have had good psychometric properties in past research were initially selected. Then, the items were reworded to be appropriate to the context of this study. Two items from Johnson and Grayson (2005), 2 items from Kwon, Trail, and James (2007), and 1 item from Fournier (1994) were ch osen and the items were revised to measure Purchase and Attendance Intenti on. In order to measure Licensed Product Purchase, 3 items from Lee and Trail (2007) were adopted. Two items from Fink et al. (2002) and 1 item from Trail et al. (2005) were chosen and those were modified to measure Media Consumption. Despite widespread use of sport media consumption intention constructs in both academic research and practice, of the studies to date that investigated s port consumption behavior through media, few seem to use multiple indicators. Multiple-indicator measures of a construct are preferable because any single-indicator measure is easily influenced by measurement error and using multiple indicators tends to reduce the influe nce of the measurement error (Kline, 2005). Therefore, a multiple-item measure of sport me dia consumption intention were developed and used for this study. All of the relationship quality outcome items were measured using a 7-point Likert-type scale response form at ranging from strongly disagree (1) to strongly agree (7). Personality traits The fourth part measuring re lational personality traits wa s comprised of 2 subscales (Relationship Development Style and Relationshi p Maintenance Style) with 12 items. Mathews (1986) identified three main relationship st yles: independent, discerning, and acquisitive relationship style. Following Math ews distinction, Fournier (1994) developed a scale to measure relationship style. However, Fourniers scale showed inadequate psychometric properties. For

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62 this study, a scale was developed to measure rela tionship style based on Ma thews criteria. One item from Fournier (1994) was selected and 5 items were gene rated to measure Relationship Development Style based on Mathews (1986) framework. Similarly, 2 items from Fournier were selected and 4 items were created to measur e Relationship Maintenance Style according to Mathews. Demographics Items measuring demographic characteristics of participants were also included in the questionnaire. The questions measured gender, age, and ethnicity. Expert Review The items were reviewed by a five-judge panel of scholars who have expertise on both the concepts measured and methodological issues associ ated with survey research. The experts were asked to review the survey items to evaluate whether their content was suitable for measuring the intended constructs and also to identify if items contained the following problems commonly associated with survey questionnaires (Grasse r, Kennedy, Wiemer-Hasti ngs, & Ottai, 1999): (1) complex syntax, (2) working memory overload, (3) vague or ambiguous noun phrases, (4) unfamiliar technical terms, (5) vague or imprecise predicate or relative term, (6) misleading or incorrect presupposition, (7) unclear question cat egory, (8) amalgamation of more than one question category, (9) mismatch between the qu estion category and the answer options, (10) difficult to recall information, (11) respondent unlikely to know answer, and (12) unclear question purpose. The survey quest ionnaire was finalized for a pilo t study after adding new items that were necessary but previously omitted, and refining or eliminating problematic items based on the results of th e expert review.

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63 Pilot Study A pilot study was conducted before the main study for the following purposes (Groves et al., 2004): (1) to test appropriatene ss of the instruments; (2) to assess variability in outcome measures that assisted in determining the sample size for main study; and (3) to identify potential problems associated with proposed data analysis technique. Methods Participants and procedure A total of 154 students enroll ed in sport activity classes participated in the study. The sample consisted of 51% male and 49% female. Th e average age of the participants was 21 years old ( M = 20.52, SD = 2.93) and slightly more than 50% of participants were white/non-Hispanic. Face-to-face self-administered mode was utilized to collect the data. Standard survey procedure was followed in accordance with IRB protocol. It took approximately 15 minutes for a respondent to complete a questionnaire. Instruments The questionnaire consisted of four main part s (relationship quality constructs, relational personality traits, relationship quality outcomes, and demographics) with 23 subscales and 117 items for the pilot study. Data analysis To evaluate the measurement models for re lationship quality constructs, relationship quality outcomes, and relational pe rsonality traits, five separate confirmatory factor analyses were conducted on each group of factors using Mplus 5.1. Among various specialized software packages for SEM, Mplus was used in both th e pilot study and main st udy for the following reasons: (1) Mplus offers several options to hand le categorical (including Likert-type scale) and non-normal data; (2) Mplus incor porates a model-based imputation method to manage missing

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64 data (3) Mplus can model both continuous latent va riables and categorical latent variables; (4) Mplus can analyze multilevel SEM with complex sa mple data; (5) Mplus can correctly analyze a correlation matrix using constrained estimation me thods; (6) Mplus provides factor scores; (7) Mplus offers extensive Monte Carlo facilities both for data generation and data analysis; and (8) Syntax of Mplus is comparatively straightforward. Results and discussion Table 3-1 displays the loadings, Cronbachs alpha, and AVE values of relationship quality constructs for the UF Football team The model fit the data poorly ( 2/ df = 984.26/506 = 1.95, RMSEA = .10, CFI = .80, SRMR = .09, WRMR = 1.12). Five items were dropped based on the assessment of factor loadings and theoretical re levance after the initial CFA. The revised model showed improved fit ( 2/ df = 654.209/356 = 1.84, RMSEA = .09, CFI = .85, SRMR = .08, WRMR = 0.98). The remaining items for the re lationship quality factors showed adequate reliability values in terms of Cronbachs alpha values ( = .79 to .89) and Average Variance Explained (AVE) values (.49 to .69) in the pilot study. Pairwise 2difference tests showed that all correlations between factor s were significantly different from 1.0, providing evidence for discriminant validity. However, squared correlations between some pairs of factors were greater than the AVE score of either factor (Table 3-2) indicating that people co uld not distinguish those factors although those factors were theoretically different. Therefore, discriminant validity of these factors was reexamined with larger sample in the main study. Table 3-3 shows the loadings, Cronbachs alph a, and AVE values of relationship quality constructs for iPod. The model had poor fit for data ( 2/ df = 1020.80/506 = 2.02, RMSEA = .10, CFI = .80, SRMR = .12, WRMR = 1.51). Five item s were dropped after an initial CFA. The remaining items showed good reliability values with Cronbachs alpha values ranging from .78 to .92 and AVE values ranging from .53 to .72. Pairwise 2difference tests showed that all

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65 correlations between factors were significantl y different from 1.0, indicating discriminant validity. However, squared correla tions between some pairs of factors were greater than the AVE score of either factor (Table 3-4), suggesting that people coul d not distinguish those factors although those factors were theore tically different. Therefore, di scriminant validity of these factors was reexamined with a larg er sample in the main study. The measurement model for sport consumption behaviors fit the data well ( 2/ df = 70.56/59 = 1.19, RMSEA = .04, CFI = .99, SRMR = .04, WRMR = 0.50). Cronbachs alpha coefficients for sport consumption behavior s ubscales ranged from .87 to .95 and AVE values ranged from .64 to .87, indicating good internal cons istency and construct reliability (Table 3-5). Table 3-6 displays the correlations between sport consumption behaviors factors. Although pairwise 2difference tests showed that all correla tions between factors were significantly different from 1.0, the squared correlation between Word of Mouth and Media ( r2 = .74) was greater than AVE value for the Word of Mouth factor (AVE = .64). Therefore, discriminant validity of the two factors was r eexamined in the main study. The measurement model for consumption be haviors (iPod) had good fit for data ( 2/ df = 21.68/13 = 1.67, RMSEA = .08, CFI = .98, SRMR = .03, WRMR = 0.40).Word of Mouth ( = .88 and AVE = .66) and Purchase Intention ( = .93 and AVE = .82) also had good internal consistency and good construct relia bility (Table 3-7). Pairwise 2difference tests showed that all correlations between factors were significan tly different from 1.0. However, the squared correlation between Word of Mouth and Purchase Intention ( r2 = .81) was greater than AVE value for the Word of Mouth (AVE = .66) factor (T able 3-8). Therefore, di scriminant of the two factors was reexamined in the main study.

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66 Four items for relationship style subscales we re dropped after an initial CFA. Table 3-9 displays the loadings, Cronbachs alpha, and AVE values of two relationship style constructs. The model fit the data poorly ( 2/ df = 110.78/53 = 2.09, RMSEA = .10, CFI = .87, SRMR = .12, WRMR = 1.45). The revised model achieved good fit for the data ( 2/ df = 30.99/19 = 1.63, RMSEA = .08, CFI = .97, SRMR = .06, WRMR = 0.81). Relationship Development ( = .88 and AVE = .65) and Relationship Maintenance ( = .69 and AVE = .55) subscales showed adequate internal consistency (Table 3-10). Pairwise 2difference test showed that the correlation between Relationship Development and Relationship main tenance was significantly different from 1.0 and AVE values of both factor were greater than squared correlation ( r2 = 21) between the two factors (Table 3-11). Through the pilot study a total 14 items we re dropped based on the assessment of psychometric properties and theoretical relevance of those items. The instrument for the main study had 96 items: 30 items for relationship qua lity of the UF Football team, 30 items for relationship quality of iPod, 20 items for rela tionship quality outcomes, and 6 items for relationship style. Data Analysis for Main Study Data analysis was performed in four stages. Fi rst, descriptive statistics for the variables used in the study was obtained. Second, data from the survey was screened and the critical assumptions underlying the statistical techniques used in study were tested. Third, measurement models for the constructs were analyzed followe d by a structural model for relationship quality and relationship quality outcomes. Finally, inte raction effects of potential moderators were examined.

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67 Descriptive Statistics Various descriptive statistics of the variables used in this study such as measures of central tendency (e. g., mean, m ode, median, etc.) and measures of variability (e. g., range, variance, standard deviati on, etc.) were obtained using SPSS 15.0 to describe the basic characteristics of the data in this study. Data Screening and Test of Assumption Prior to the main analyses, al l the variables were examined using various SPSS programs and Mplus programs for accuracy of data entry, outli ers, and fit between the characteristics of the data and the critical assumptions of vari ous SEM techniques used in this study. Outliers in the variables were evaluated us ing extreme values output from the Explore analysis. Elimination of case or variable, transformation, and score alteration is typically considered to reduce the influence of outliers base d on the nature of the outlier. Normality of the observed variables was assessed through examina tion of histogram and summary descriptive statistics using SPSS Descriptives. Multivariate normality was tested using Mardias (1985) multivariate skewness and kurtosis coefficients and normalized estimates of the coefficients, which were available through PRELIS 2.80. If Ma rdias Normalized Coefficient of both skewness and kurtosis is significant, multivar iate non-normality can be inferred. When the normality assumption is violated enough to cause problems with the SEM analysis, hypothesized models can be estimated with maximum likelihood estimation but tested with Satorra-Bentler scaled chi-square statistic (SB 2, 1994), which has been shown to perform reliably with medium sample sizes (100 < N < 500) under condition of nonnormality (Bentler & Yuan, 1999; Curran, West, & Finch, 1996; Hu, Bentler, & Kano, 1992). Accordingly, model fit indices depend on chisquare statistic should be adjusted based on SB 2.

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68 Linearity of the observed variables was assess ed by examining randomly selected pairs of scatterplots using SPSS Graphs because it was not practical to examine all pairwise scatterplots to evaluate linearity. When linearity assumptions are violated, data transformation can be used as a remedy. The determinant of the input matrix was inspected to identif y multicollinearity and singularity in the data. The determinant of the input matrix is available in SPSS Factor Analysis when it is requested. When serious multicollineari ty or singularity occu rs, the variables causing the multicollinearity or singularity should be deleted or combined into a new composite variable. Measurement Model Separate confirmatory factor analyses were performed on five groups of constructs (i.e., relationship quality constructs for UF Football team and iPod relationship outcomes for UF football team and iPod, and relational personal ity traits) using Mplu s 5.1 to evaluate the measurement models. Goodness of fit indices used to evaluate overall fit of the model in the current study were the CFI in conjunction with standard root mean squared residual (SRMR) following Hu and Bentler (1999). A cutoff-value cl ose to .95 or higher for CFI in combination with a cutoff value close to (less than) .09 for SRMR was recommended (Hu & Bentler). Additionally, the root-mean-square error of approximation (RMSEA), which is thought to reduce problems with incremental fit indices (e.g., CFI) a nd absolute fit indices (e.g., GFI) according to Brown and Cudeck (1992), was used. RMSEA valu es of less than .06 indicate good fit (Hu & Bentler), values of .08 or less would represent r easonable fit and values hi gher than .10 indicate poor fit (Brown & Cudeck). Furthermore, the weighted mean square residual (WRMR), which is more appropriate with categorical data or non-normal continuous data (Muthn & Muthn, 2006), was used. WRMR values under 1.0 indica te good fit and smaller values demonstrate better fit (Yu & Muthn, 2002).

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69 The discrepancy matrix was also examined in conjunction with modification indices (MI) statistics since clear misspecification cannot be discovered by the indexed fit of the composite structural model and it is impossible to decide which elements of the composite hypothesis can be considered satisfactory from the global goodn ess of fit indices alone (McDonald & Ho, 2002). In addition, internal consistency values (Cronbachs alpha coefficients) were utilized to examine how well the items measuring a specif ic subscale were correlated with each other. Values greater than .70 are considered to be adequate (N unnally & Bernstein, 1994). Average Variance Explained (AVE) values were employed to eval uate how well the items on a specific subscale collectively explained the underlying constructs variance. AVE values above .50 indicate that the composite reliability of the construct is adequate (Fornell & Larcker, 1981). Discriminant validity for each of the factors was tested through the procedure that involves 2 difference test between a model in which two indi vidual factors are cons trained to be 1.0 (i.e., the two factors are perfectly correlated) and a model where the correlation between two factors are freely estimated. If the unrestricted mode l without the unity c onstraints fits the m odel fit significantly better, it might be inferred that the two factor s are distinct in the population. AVE values were also used to evaluate discrimi nant validity of the constructs. Results from the each analysis above were considered collectively in reachi ng a final decision regarding which items and factors to retain and which to eliminate. To better understand how the relationship quality constructs were eval uated and structured, the four models (general relati on quality factor model, independe nt factor model, group factor model, and second-order hierarchi cal model) discussed in the prev ious chapter were empirically tested.

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70 Structural Model To examine the relationship between re lationship quality c onstructs and sport consumption behaviors, a struct ural regression (SR) model, which incorporated the five relationship quality constructs (Trust, Commitment, Relationshi p Satisfaction, Self Connection, and Reciprocity) and the three consumption behavi or constructs (Media Consumption Intention, Licensed-Product Consumption Intention, and Attendance Intention) was conducted using Mplus 5.1 Moderating Effects Two basic techniques have been developed to model moderating effects with continuous observed variables using SEM. One approach, wh ich is referred to as the product indicant technique, was introduced by Kenny and Judd (1984). This approach generates a latent interaction variable by multiplying pairs of observed variables and then incorporates the new latent interaction variable in the structural model. Although this technique has provided a valuable means to conduct structural equati on interaction models, th e application of the technique to sport management research has been limited. The dearth of such application might be due to the fact that (1) it is difficult for a pplied researchers to prope rly specify the nonlinear constraints in the matrices and (2) multiplying of all pairs of observed variables to form latent interaction variables possibly re sults in a too large and impr actical model. Jreskog (2000) suggested a technique utilizing latent variable scores to test late nt variable interactions in a structural equation model. This method alleviat ed the problems listed above. Especially, using this method can considerably reduce the number of indicat ors included in the model. Schumacker (2002) compared the new approach to the product indicant approach and reported that the new method yielded sati sfactory parameter estimation.

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71 Relationship Quality was the independent vari able and Sport Consumption Behaviors was the dependent variable in the main relationship. Interaction effects of Relationship Development and Relationship Maintenance which were continuous latent variables, were tested following Jreskogs (2000) latent score approach. Latent scores of the second-order Relationship Quality construct, the second-order Sport Consumption Behaviors construct, and two relationship style constructs were computed and saved through CFA using Mplus 4.21. Then, latent interaction variables were created by multiplying the latent variable scores of Relationship Quality and each relationship style construct. Lastly, multiple pa th analyses with two independent variables (Relationship Quality and one of the relational style constructs), one latent product variable, and Sport Consumption Behaviors were performed. In teraction effects can be inferred if a path coefficient for the direct effect of the product va riable on the dependent va riable is statistically significant.

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72 Table 3-1. Summary results for measurement m odel of relationship quality (UF Football Team) in pilot study Factors and items AVE Trust .793 0.49 I trust the brand 0.718 I can count on the brand 0.661 The brand has integrity 0.694 The brand is reliable 0.735 Commitment .890 0.69 I am dedicated to the brand 0.796 I am faithful to the brand in spirit 0.744 I am devoted to the brand 0.918 I am committed to the brand 0.862 Relationship Satisfaction .858 0.55 My relationship with the brand is favorable 0.853 I am pleased with the relationship that I have with the brand 0.813 I am happy with my relationship with the brand 0.734 I am satisfied with my relationship with the brand 0.534 Self-Connection .855 0.61 The brand's image and my self-image are similar in a lot of ways 0.771 The brand and I have a lot in common 0.788 The brand reminds me of who I am 0.713 The brand is part of me 0.836 Love .891 0.62 I love this brand 0.696 I am passionate about this brand 0.893 I adore the brand 0.782 I am emotionally attached to the brand 0.760 Intimacy .808 0.49 I am very close to the brand 0.827 I am very familiar with the brand 0.587 I know a lot about the brand 0.688 I feel as though I really understand the brand 0.666 Reciprocity .833 0.55 The brand unfailingly pays me back wh en I do something extra for it 0.705 The brand constantly returns the favor when I do something good for it 0.752 The brand places my needs above its own needs 0.744 The brand gives me back equivalently what I have given them 0.711 The brand pays attention to what I get relative to what I give them 0.807

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73 Table 3-2. Correlations among relationship quality constructs (UF Football Team) in pilot study 1 2 3 4 5 6 7 1. Trust 1.00 2. Commitment 0.77 1.00 3. Reciprocity 0.62 .50 1.00 4. Self-Connection 0.67 .89 .69 1.00 5. Love 0.81 .98 .45 .86 1.00 6. Intimacy 0.89 .87 .56 .83 .86 1.00 7. Satisfaction 0.92 .84 .45 .70 .87 .88 1.00

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74 Table 3-3. Summary results for measurement model of relationship quality (i Pod) in pilot study Factors and items AVE Trust .847 0.57 I trust the brand 0.798 I can count on the brand 0.881 The brand has integrity 0.482 The brand is reliable 0.793 Commitment .864 0.60 I am dedicated to the brand 0.798 I am faithful to the brand in spirit 0.728 I am devoted to the brand 0.765 I am committed to the brand 0.817 Relationship Satisfaction .921 0.72 My relationship with the brand is favorable 0.831 I am pleased with the relationship that I have with the brand 0.891 I am happy with my relationship with the brand 0.857 I am satisfied with my relationship with the brand 0.808 Self-Connection .854 0.60 The brand's image and my self-image are similar in a lot of ways 0.806 The brand and I have a lot in common 0.741 The brand reminds me of who I am 0.747 The brand is part of me 0.799 Love .892 0.61 I love this brand 0.662 I am passionate about this brand 0.860 I adore the brand 0.831 I am emotionally attached to the brand 0.749 Intimacy .776 0.53 I am very close to the brand 0.380 I am very familiar with the brand 0.821 I know a lot about the brand 0.914 I feel as though I really understand the brand 0.679 Reciprocity .857 0.58 The brand unfailingly pays me back wh en I do something extra for it 0.816 The brand constantly returns the favor when I do something good for it 0.804 The brand places my needs above its own needs 0.709 The brand gives me back equivalently what I have given them 0.687 The brand pays attention to what I get relative to what I give them 0.793

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75 Table 3-4. Correlations among relationship qua lity constructs (iP od) in pilot study 1 2 3 4 5 6 7 1. Trust 1.00 2. Commitment .76 1.00 3. Reciprocity .52 .75 1.00 4. Self-Connection .60 .94 .71 1.00 5. Love .76 .98 .60 .82 1.00 6. Intimacy .39 .52 .40 .65 .36 1.00 7. Satisfaction .93 .78 .53 .63 .79 .51 1.00

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76 Table 3-5. Summary results for measurement m odel of consumption behaviors (UF Football team) in pilot study Factors and items AVE Word of Mouth .877 0.64 I will tell other people about how good this brand is 0.750 I will encourage my friends and relatives to buy this brand 0.846 I will go out of my way to say posit ive things about this brand 0.738 I will recommend this brand whenever anyone seeks my advice 0.87 Attendance .951 0.87 I intend to attend the Gators Football teams game(s) 0.907 The likelihood that I will attend th e Gators Football teams game(s) in the future is high 0.941 I will attend the Gators Football teams game(s) in the future 0.949 Media .939 0.85 I will watch or listen to the Gators Football teams game(s) through the media (e.g., TV, Internet, Radio, etc.) 0.924 I will support the Gators Football te am by watching or listening to Gators Football teams game(s) through the media (e.g., TV, Internet, Radio, etc.) 0.958 I will track the news on the Gators Football team through the media (e.g., TV, Internet, Radio, etc.) 0.875 Merchandise .950 0.87 In the future, purchasing Gators Football team licensed merchandise is something I plan to do 0.942 I am likely to purchase Gators Football teams licensed merchandise in the future 0.900 In the future, I intend to purchase licensed merchandise representing the Gators Football team 0.950

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77 Table 3-6. Correlations among sport consumpti on behaviors construc ts in pilot study 1 2 3 4 1. Word of Mouth 1.00 2. Attendance .54 1.00 3. Media .50 .86 1.00 4. Merchandise .63 .66 .65 1.00

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78 Table 3-7. Summary results for measurement model of purchase intention (i Pod) in pilot study Factors and items AVE Word of Mouth-iPod .883 .66 I will tell other people about how good this brand is 0.669 I will encourage my friends and relatives to buy this brand 0.888 I will go out of my way to say pos itive things about this brand 0.788 I will recommend this brand whenever anyone seeks my advice 0.879 Purchase Intention-iPod .928 .82 I will buy this brands products in the future 0.869 The likelihood that I will buy this brand in the future is high 0.928 I intend to purchase products from this brand 0.912

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79 Table 3-8. Correlations among consumption behaviors constructs (iPod) in pilot study 1 2 1. Word of Mouth 1.00 2. Purchase .90 1.00

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80 Table 3-9 Summary results for measurement model of relationship st yle (Initial model) Factors and items AVE Relationship Development .881 .56 I start a new relationship casually rather than selectively 0.606 It usually takes only short time fo r me to make a new friend 0.754 I can easily make new friends 0.820 It seems that I develop a new relationship more easily than most people I know 0.796 I feel comfortable with meeting new people 0.838 It seems that I move through my life collecting new relationships all along the way 0.665 Relationship Maintenance .687 .38 I have a strong relationship with most of my friends 0.561 It is difficult for me to end a ny relationship with another 0.164 I continue a relationship with others for a long time 0.720 I can see that my core group of friends will stay close over the course of my life 0.811 It seems that I have more friends than most people I know 0.306 In general, relationships between my friends and me are very close 0.818

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81 Table 3-10. Summary results for measur ement model of relationship style Factors and items AVE Relationship Development .881 0.65 It usually takes only short time fo r me to make a new friend 0.761 I can easily make new friends 0.854 It seems that I develop a new relationship more easily than most people I know 0.790 I feel comfortable with meeting new people 0.810 Relationship Maintenance .687 0.55 I have a strong relationship with most of my friends 0.547 I continue a relationship with others for a long time 0.711 I can see that my core group of friends will stay close over the course of my life 0.837 In general, relationships between my friends and me are very close 0.822

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82 Table 3-11. Correlations among relational pe rsonality constructs in pilot study 1 2 1. Relationship Development 1.00 2. Relationship Maintenance .46 1.00

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83 CHAPTER 4 RESULTS The results of the study are presented in the fo llowing order: (1) Descriptive statistics (2) Data screening and test of assumptions (3) Me asurement models (4) St ructural models (5) Moderating effects. Descriptive Statistics Demographics Demographic characteristics of participants ( N = 496) are depicted in Table 4-1. The majority of the participants were women (64%). The average age of the participants was 25 years old ( M = 24.84, SD = 9.35) and 61% of participan ts were white/non-Hispanic. Relationship Quality Variables Descriptive statistics for relationship quality variables are presented in Tables 4-2 and 43. The means of the relationship quality items fo r the UF Football team ranged from 2.75 to 5.32. Standard deviations ranged from 1.25 to 1.85. The items for Love, Commitment, and Relationship Satisfaction factor ha d the highest means on the 7-point Likert type scale. The items for Reciprocity and Self-Connecti on had the lowest means. The ite m I love the Gators Football team had the highest mean ( M = 5.53, SD = 1.65) and the item The Ga tors Football team pays attention to what I get relative to wh at I give them had the lowest mean ( M = 2.75, SD = 1.46). Consumption Variables Table 4-4 and Table 4-5 display the descri ptive statistics for relationship outcomes. Means of all the items for UF Football we re above 5.00 (4.0 mid-poi nt) and ranged from 5.39 ( SD = 1.56) for the item I will track the news on the Gators Football team through the media (e.g., TV, Internet, Radio, etc.) to 5.91 ( SD = 1.41) for the item I will support the Gators Football team by watching or listening to Gato rs Football teams game(s) through the media

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84 (e.g., TV, Internet, Radio, etc.). Standard devi ations for the items ranged from 1.41 to 1.68. The means of items measurin g Purchase Intention for iPod ranged from 4.53 ( SD = 1.74) for the item I intend to buy iPod products to 4.64 ( SD = 1.63) for the item The likelihood that I will buy iPod products in the future is hi gh. Standard deviations ranged from 1.73 to 1.77. Relationship Style Variables Descriptive statistics for relationship styl e items are shown in Table 4-6. The item In general, relationships between my friends a nd me are very close had the highest mean ( M = 5.71, SD = 1.15) and the item It seems that I devel op a new relationship more easily than most people I know had the lowest mean ( M = 4.40, SD = 1.48). Standard deviations for the items ranged from 1.15 to 1.48. Data Screening and Test of Assumptions for Structural Equation Modeling (SEM) No standardized score for any variable was above 3.29 and no standardized score for any variable was below -3.29, which were the s uggested cut-off values for potential outliers (Tabachnick & Fidell, 2007). There was evidence that both univariate and multivariate normality assumptions for observed variables were violate d. Distributions for fifty three out of seventy observed variables were significantly skewed at p < .01 and the distri butions for 39 of 70 variables showed si gnificant kurtosis at p < .01. Moreover, Mardias No rmalized Coefficient of both skewness ( z = 41.69) and kurtosis ( z = 14.13) was significant, p < .01. For dealing with the non-normality, Satorra-Bentler scaling method (SB 2, 1994) was used for the SEM analyses in the current study. Consequently, model fit indi ces depending on chi-squa re statistic were adjusted based on SB 2. All randomly selected pairs of variables appeared to be linearly related. The determinants of all the matrices used in th is study were much larger than 0, indicating there was no extreme multicollinearity or singularity in those matrices.

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85 Measurement Models Relationship Quality (UF Football team) Validation of the measure The measurement model (Figure 2-4), which specif ied seven latent factors to be correlated with each other, was tested. Six items were drop ped based on the results from the initial CFA, leaving 23 observed variables for 7 latent factor s. Factor loadings, th eoretical relevance and parsimoniousness of the model were considered collectively in reaching a final decision regarding which items to retain and which to eliminate. Table 4-7 s hows factor loadings, Cronbachs alpha coefficients, a nd AVE values for the initial CF A. After the modification, the model showed mediocre fit ( 2/ df = 812.61/209 = 3.89, RMSEA = .08, CFI = .92, SRMR = .06, WRMR = 1.78). Cronbachs alpha coefficients fo r relationship quality factors ranged from .79 for Trust to .93 for Commitment (Table 4-8), indicating good internal consistency according to the suggested cut-off values of .70 (Nunnally, 1978). The AVE values ranged from .55 for Relationship Satisfaction to .81 for Commitment, indicating good construct reliability. Pairwise 2difference tests showed that all correlations between factors were significantly different from 1.0, providing evidence for discriminant validity. However, squared correlation be tween Commitment and Love ( r2 =.94) was greater than the AVE score of both factors ( .81 and .66 respectively). Table 49 displays the correlations between relationship quality factors. Observed variables for Intimacy and Love had the largest standardized residuals in the di screpancy matrix, which indicated the relationships between those variables and other variables were misspecified. In addition, MI statisti cs suggested that the model could be improved most if the constraint that fixed paths from items for Intimacy to other factors to be zero were freely estimated (MI > 20 ), implying that variances in the items were

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86 accounted for by more than one factor. Due to the inadequate psychomet ric properties of the Love and Intimacy scales, those two f actors were dropped from the model. The revised measurement model achieved good fit for data ( 2/ df = 319.65/94 = 3.40, RMSEA = .07, CFI = .95, SRMR = .04, WRMR = 1.24). Factor loadings Cronbachs alpha coefficients, and AVE are reported in Table 4-10. The internal consistency measures for all the factors were greater than .70 with the lowest of .79 for Rela tionship Satisfaction and the highest of .93 for Commitment. The AVE values for all th e factors were also greater than .50 with the lowest of .55 for Relationship Satisfaction and the highest of .81 for Commitment. Pairwise 2difference tests showed that all correlations between factors were significantly different from 1.0. In addition, no squared correlation between two factors was greater than the AVE score of either factor with the exception of the square d correlation between Trust and Self-Connection (r2 =.67), which was greater than AVE value for Tr ust and Self-Connection (AVE = .66 for both) by only third decimal place, indicating discriminant validity. Correlations among latent factors are reported in Table 4-11. Highly in tercorrelated but still distin ct factor structure provided preliminary evidence that the first-order factors converge into a higher-or der relationship quality factor. Structure of the relationship quality constructs In testing the proposed secondorder hierarchical model, co mparisons were made with three alternative models discusse d in the previous chapter. Th e modified second-order factor model was not tested because two factors (i.e., Love and Intimacy), which were hypothesized to tap into a second-order latent variable, Affec tive Relationship Quality, were dropped after the construct validation procedure. Therefore, the hierarchical model specifying two second-order latent factors was no longer a plausible mode l. Model fit information for the second-order hierarchical model and the al ternative models is displaye d in Table 4-12. The hypothesized

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87 second-order hierarchical factor mode l (Figure 2-5) fit the data well ( 2/ df = 380.43/99 = 3.84, RMSEA = .05, CFI = .94, SRMR = .05, WRMR = 1.54) Two alternative models did not pass the desired criteria for fit. The i ndependent factor model that sp ecified the relationship quality factors to be completely uncorrelated with each other had poor fit ( 2/ df = 1435.81/104 = 13.81, RMSEA = .16, CFI = .69, SRMR = .38, WRMR = 11.08) In addition, the general factor model that hypothesized a global relati onship factor that collapsed across all 16 indicators fit the data poorly ( 2/ df = 1080.09/104 = 10.39, RMSEA = .14, CFI = .77, SRMR = .09, WRMR = 2.46). The group factor (measurement) model that a llowed the correlation for all pairs of firstorder factors to be freely estimated achieved good fit as noted above ( 2/ df = 319.65/94 = 3.40, RMSEA = .07, CFI = .95, SRMR = .04, WRMR = 1.24) Figure 4-1 depicted the relationship between first-order relationship quality factors and the second-ord er relationship quality factor. Loadings for the first-order factors on the second order factors were sign ificantly different from zero in every case and all standa rdized loadings were greater than .70 ranging from .71 for Reciprocity to .92 for Self-Connec tion. Relationship Quality (iPod) Validation of the measure The measurement (Figure 2-5) model, which hypothesized seven latent factors to be correlated with each other, was tested. Six items were dropped based on the results from the initial CFA, leaving 23 observed variables for 7 latent factors. A final decision regarding which items to retain and which to eliminate were ma de by taking into accoun t the factor loadings, theoretical relevance and parsimoniousness collectively. Table 413 displays factor loadings, Cronbachs alpha coefficients, a nd AVE values for the initial CF A. After the modification, the model showed marginal fit ( 2/ df = 1023.75/209 = 4.90, RMSEA = .09, CFI = .89, SRMR = .06, WRMR = 1.85). All subscales showed good inte rnal consistency with Cronbachs alpha

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88 coefficients ranging from .81 for Self-Connectio n to .90 for Commitment (Table 4-14). All subscales had good construct reliability with the AVE values ranged from .60 for Trust to .74 for Commitment. Pairwise 2difference tests showed that all correlations between factors were significantly different from 1.0. However, the squared correlation between Commitment and Love ( r2 =.90) was greater than the AVE score of both factors (.81 and .67 respectively). In additi on, squared correlation between Commitment and Intimacy ( r =.92) was also greater than the AVE score of both factors (.81 and .61 respectively). The correlations between relationship quality f actors are presented in Table 4-15. Observed variables measuring Self -Connection and Intimacy contributed to the largest standardized residuals in the discrepa ncy matrix, indicating th e relationship between those variables and other variables was misspecifie d. In addition, on the basis of the MI statistics, the model could be improved most if the paths from items for Self-Connection and Intimacy to other factors were freely estimated (MI > 20), which implied that more than one factor accounted for variance in the items. Therefore, Love, In timacy, and Self-Connection were dropped from the model due to the inadequate psychome tric properties of the subscales. The final model fit data well ( 2/ df = 188.76/59 = 3.20, RMSEA = .07, CFI = .96, SRMR = .05, WRMR = 1.38). Factor loadings, Cronbachs alpha coefficients, and AVE values are presented in Table 4-16. The internal consistency measures for al l the factors exceeded .70 with the lowest of .80 for Trust and the highest of .90 for Commitment. The AVE values for all the factors also exceeded .50 with the lowest of .60 for Trust and the highest of .75 for Commitment. Pairwise 2difference tests showed that all correlations between factors are si gnificantly different from 1.0 and no squared correlation between two factors was greater th an the AVE score of either factor except the square co rrelation of Trust and Commitment ( r2 =.75) and Trust and

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89 Relationship Satisfaction ( r2 =.75). Correlations among latent va riables are reported in Table 417. Structure of the relationship quality constructs Table 4-18 shows model fit information for th e second-order hierarch ical model and the alternative models. The modified second-order factor model was not tested because three factors (i.e., Love, Intimacy, and Self-Connection) we re dropped after the construct validation procedure. Therefore, the hier archical model specifying two s econd-order latent factors was no longer a plausible model. The hypothesized seco nd-order hierarchical factor model achieved good fit (2/ df = 200.53/61 = 3.29, RMSEA = .07, CFI = .96, SRMR = .05, WRMR = 1.48). Two alternative models showed inadeq uate fit. The independent factor model that set the relationship quality factors to be completely uncorre lated with each other fit data poorly ( 2/ df = 1049.03/65 = 16.14, RMSEA = .18, CFI = .71, SRMR = .36, WRMR = 10.44). Similarly, the general factor model that specified a global relationship factor that collapsed across a ll 16 indicators had poor fit as well ( 2/ df = 790.10/65 = 12.16, RMSEA = .15, CF I = .78, SRMR = .10, WRMR = 2.82). The group factor (measurement) m odel that let the correlations for all pairs of first-order factors to be freely estimated showed good fit as noted above ( 2/ df = 188.76/59 = 3.20, RMSEA = .07, CFI = .96, SRMR = .05, WRMR = 1.38). Both th e second-order hierarchical factor model and the group factor model had satisfactory fit. The relationship between first-order relationship quality factors and the second-order relationshi p quality factor is di splayed in Figure 4-2. Loadings for the first-order factors on the second order factors were significantly larger than zero in all cases. With the ex ception of Reciprocity ( = .61), all standardized loadings exceeded .70 ranging from .61 for Reciprocity to .96 for Trust.

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90 Relationship Outcome (UF Football team) Table 4-19 displays factor lo adings, Cronbachs alpha coeffi cients, and AVE values for the initial CFA for sport consumption behaviors. The model showed good fit ( 2/ df = 149.14/48 = 3.11, RMSEA = .07, CFI = .98, SRMR = .03, WRMR = 0.76). The subscales had good internal consistency and good construct re liability with Cronbachs alpha ranging from .82 to 96 and the AVE values ranging from .62 to .89. Pairwise 2difference tests showed that all correlations between factors are significantly different from 1.0. However, the AVE value for Word of Mouth (AVE = .62) was smaller than squared correlation between Word of Mouth and all other factors (Table 4-20), indicating lack of di scriminant validity of the Word of Mouth factor with the other factors in the model. Therefore, Word of Mouth was dropped from the model. Factor loadings, Cronbachs alpha coefficients, and AVE values from the CFA on sport consumption behaviors are presented in Table 4-21. The revised model fit data very well ( 2/ df = 42.52/24 = 1.77, RMSEA = .04, CFI = .99, SRMR = .02, WRMR = 0.40). The results from the CFA also indicated good internal consistency for observed variables with Cronbachs alpha coefficients ranging from .89 for Media to .96 for Attendance and the AVE values ranging from .74 for Media to .89 for Attendance. Pairwise 2difference tests showed that all correlations between factors were significantly different from 1.0 a nd no squared correlation between two factors was greater than the AVE score of either factor provi ding an evidence of discriminant validity for the items. Table 4-22 shows correlations among latent fact ors. It can be inferred that the first-order factors converge into a higher-order factor from the highly intercorre lated but still distinct factor structure in conjunction with the theoretical jus tification discussed in the earlier chapter. Model fit information for the second-order hi erarchical model and the alternative models are reported in 4-23. Hypothesized second-order hierarchical f actor model showed the good fit for data ( 2/ df = 42.52/24 = 1.77, RMSEA = .04, CFI = .99, SRMR = .02, WRMR = 0.40). Two

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91 alternative models demonstr ated inadequate fit based on goodness of fit indices and 2/ df values. The independent factor model that fixed the correlation among the th ree sport consumption variables to be zero had poor fit ( 2/ df = 544.88/27 = 20.18, RMSEA = .20, CFI = .84, SRMR = .42, WRMR = 9.27). Likewise, the ge neral factor model that hypothe sized 9 indicators directly measuring global sport consumption be havior factor fit data poorly ( 2/ df = 958.03/27 = 35.48, RMSEA = .26, CFI = .71, SRMR = .10, WRMR = 1.94). The group factor (measurement) model that was specified to freely estimate the correlation for all pairs of firstorder factors achieved good fit as noted above ( 2/ df = 42.52/24 = 1.77, RMSEA = .04, CFI = .99, SRMR = .02, WRMR = 0.40). Figure 4-3 depicts the relationship between three first-order latent factors and the second-order spor t consumption behavior factor. Loadings for the first-order factors on the second order factors were significantly larger than zero in all cases and all the standard ized loadings were greater than .70 with the lowest of .78 for Attendance and the highest of .89 for Merchandise. Relationship Outcome (iPod) Table 4-24 shows factor loadings, Cronbachs alpha coefficients, and AVE values for the initial CFA for consumption behaviors. The model showed good fit ( 2/ df = 10.87/8 = 1.35, RMSEA = .03, CFI = .99, SRMR = .01, WRMR = 0.25). Word of Mouth ( = .89 and AVE = .74) and Purchase Intention ( = .95 and AVE = .86) subscale s showed adequate internal consistency and construct reliability. Pairwise 2difference test showed th at correlations between Word of Mouth and Purchase Intention are significantly different from 1.0. However, AVE value for Word of Mouth (AVE = .74) was smaller than squared correlation ( r2 = .76) between Word of Mouth and Purchase Intention (Table 4-25), in dicating lack of discriminant validity of the Word of Mouth factor. Therefore, Word of Mouth was dropped from the model. The measurement model consisted of a single factor (Purchase Intention), which was a saturated

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92 model, and thus fit the data perfectly ( 2/ df = 0.00/0 = 0.00, RMSEA = .00, CFI = 1.00, SRMR = 0.00, WRMR = 0.00). Cronbachs alpha value for it ems measuring Purchase Intention was .95 and AVE value was .86, indicating g ood internal consistency and c onstruct reliability (Table 426). Relationship Personality Two items were dropped based on the results from the initial CFA, leaving 6 observed variables for 2 latent factors. The measurement model for relationship style, which consisted of the Relationship Development and Relationship Maintenance factors, yielded a good fit ( 2/ df = 9.12/8 = 1.14, RMSEA = .02, CFI = 0.99, SRMR = 0.01, WRMR = 0.32). Cronbachs alpha coefficients and AVE values for Relationship Development ( = .88 and AVE = .72) and Relationship Maintenance ( = .84 and AVE = .67) were great er than widely used cut-off criteria, indicating that items measuring rela tionship style had good reliability (Table 4-27). Pairwise 2difference tests showed that correlati on between Relationship Development and Relationship Maintenance was significantly diffe rent from 1.0 and the squared correlation between the two factors was great er than the AVE value for eith er factor, providing evidence for discriminate validity. The correl ation between the two factors wa s .44 in the sample (Table 428). Structural Models The hypothesized model that examined the relationship between rela tionship quality and sport consumption for the UF Football team is depi cted in Figure 4-4. The model fit the data well ( 2/ df = 712.66/266 = 2.68, RMSEA = .06, CFI = 0.95, SRMR = 0.06, WRMR = 1.79). The second-order Relationship Qualit y factor significantly influe nced the seco nd-order Sport Consumption Behavior factor (standardized = .82, z = 13.00). Relationship Quality explained 67 % of the variance in Sport Consumption Behaviors.

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93 The hypothesized model that examined the relationship between rela tionship quality and purchase intention for iPod is in Figure 4-5. The model had good fit ( 2/ df = 307.34/99 = 3.10, RMSEA = .07, CFI = 0.96, SRMR = 0.05, WRMR = 1.53). The path coefficient between the second-order Relationship Qualit y factor and the second-order Sport Consumption Behavior factor was significant (standardized = .80, z = 12.50) and Relationship Quality explained 64 % of the variance in Purchase Intention. Moderating Effects Relationship Development The model that represented the hypothesi zed interaction effect of Relationship Development on the relationship between Re lationship Quality and Sport Consumption Behaviors is depicted in Figure 4-6. The model yielded satisfactory fit ( 2/ df = 887.98/364 = 2.43, RMSEA = .05, CFI = 0.95, SRMR = 0.06, WRMR = 1.68). The path coefficient from the product term of Relationship Quality and Rela tionship Development to Sport Consumption behaviors was not significant (standardized = -.02, z = -0.50) and the product term explained less than 1% of variance in Sport Consumpti on Behaviors, which i ndicated no significant interaction effect. The model that examined the interaction effect of Relationship Development on the relationship between Relationship Qu ality and Purchase Intention fo r iPod is presented in Figure 4-7. The model achieved good fit for ( 2/ df = 424.16/161 = 2.63, RMSEA = .06, CFI = 0.96, SRMR = 0.05, WRMR = 1.41). The path coeffici ent from the product term of Relationship Quality and Relationship Development to Purchase Intention was not significant (standardized = -.06, z = -1.1) and the product term explained less th an 1% of variance in Sport Consumption Behaviors. Therefore, no signifi cant interaction effect was found.

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94 Relationship Maintenance Figure 4-8 shows the model that specified the interaction effect of Relationship Maintenance on the relationship between Re lationship Quality and Sport Consumption Behaviors. The model had good fit ( 2/ df = 846.08/364 = 2.32, RMSEA = .05, CFI = 0.95, SRMR = 0.06, WRMR = 1.66). The product term of Relationship Quality and Relationship Maintenance did not significantly influence Sport Consumption Behaviors (standardized = .03, z = -1.07) and less than 1% of variance in Sport Consumption Behaviors was explained by the product term, indicating no si gnificant interaction effect. Figure 4-9 depicts the model that investigat ed the interaction e ffect of Relationship Maintenance on the relationship between Relations hip Quality and Purchase Intention for iPod. The model fit data well ( 2/ df = 354.71/161 = 2.20, RMSEA = .05, CFI = 0.96, SRMR = 0.05, WRMR = 1.39). The product term of Relations hip Quality and Relation Maintenance did not significantly influence Purcha se Intention (standardized = -.09, z = -1.70) and the product term accounted for less than 1% of variance in Pu rchase Intention. Therefore, no significant interaction effect was inferred.

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95 Table 4-1. Demographic characteristics of participants Variable Group n % Gender Male 180 36.29 Female 316 63.71 Age 18-21 269 55.24 22-25 110 22.59 26-30 42 8.62 30+ 66 13.55 Ethnicity American Indian/Alaskan Native 5 1.02 Asian 30 6.10 Black 36 7.32 Hawaiian/Pacific Islander 5 1.02 Hispanic/Non-White 20 4.07 White/Hispanic 83 16.87 White/Non-Hispanic 304 61.79 Other 9 1.83

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96 Table 4-2. Descriptive statistics for relationship quality (UF Football) Factors and items M SD Trust I can count on the Gators Football team 4.39 1.52 I trust the Gators Football team 4.63 1.25 The Gators Football team is reliable 4.14 1.45 Commitment I am committed to the Gators Football team 4.75 1.80 I am devoted to the Gators Football team 4.85 1.78 I am dedicated to the Ga tors Football team 4.83 1.77 Reciprocity The Gators Football team unfailingly pays me back when I do something extra for it 3.27 1.48 The Gators Football team gives me back e quivalently what I have given them 3.61 1.58 The Gators Football team constantly re turns the favor when I do something good for it 3.15 1.42 The Gators Football team pays attention to what I get relative to what I give them 2.75 1.46 Self-Connection The Gators Football teams image and my self -image are similar in a lot of ways 3.31 1.50 The Gators Football team is part of me 4.00 1.85 The Gators Football team and I have a lot in common 3.38 1.57 Love I adore the Gators Football team 4.81 1.70 I am passionate about the Gators Football team 5.11 1.65 I am emotionally attached to the Gators Football team 4.32 1.84 I love the Gators Football team 5.32 1.65 Intimacy I am very familiar with the Gators Football team 5.03 1.62 I know a lot about the Gato rs Football team 4.97 1.56 I am very close to the Gators Football team 3.80 1.73 Relationship Satisfaction I am pleased with the relationship that I have with the Gators Football team 4.78 1.33 My relationship with the Gators Football t eam is favorable 4.90 1.48 I am satisfied with my relationship with the Gators Football team 4.76 1.34

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97 Table 4-3. Descriptive statistics fo r relationship quality (iPod) Factors and items M SD Trust iPod is reliable 5.26 1.26 I trust iPod 4.08 1.62 I can count on iPod 4.27 1.59 Commitment I am committed to iPod 4.15 1.79 I am devoted to iPod 3.47 1.76 I am dedicated to iPod 3.22 1.75 Reciprocity iPod pays attention to what I get relative to what I give them 3.01 1.53 iPod constantly returns the favor when I do something good for it 2.60 1.43 iPod unfailingly pays me back when I do something extra for it 2.55 1.42 iPod gives me back equivalently what I have given them 2.99 1.50 Self-Connection iPod is part of me 2.89 1.75 iPod and I have a lot in common 2.65 1.52 iPods image and my self-image are similar in a lot of ways 2.61 1.49 Love I love iPod 4.08 1.78 I am passionate about iPod 3.31 1.71 I adore iPod 3.33 1.78 I am emotionally attached to iPod 2.68 1.64 Intimacy I am very close to iPod 3.57 1.80 I am very familiar with iPod 4.70 1.72 I know a lot about iPod 4.18 1.77 Relationship Satisfaction I am pleased with the relationship that I have with iPod 4.46 1.47 I am satisfied with my relationship with iPod 4.13 1.61 My relationship with iPod is favorable 4.01 1.51

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98 Table 4-4. Descriptive statistics for relationship outcomes (UF Football) Factors and items M SD Attendance I intend to attend the Gators Football teams game(s) 5.55 1.76 The likelihood that I will attend the Ga tors Football teams game(s) in the future is high 5.67 1.77 I will attend the Gators Football teams game(s) in the future 5.63 1.70 Media I will track the news on the Gators Football team through the media (e.g., TV, Internet, Radio, etc.) 5.39 1.56 I will watch or listen to the Gators Football teams game(s) through the media (e.g., TV, Internet, Radio, etc.) 5.77 1.45 I will support the Gators Football te am by watching or listening to Gators Football teams game(s) through the media (e.g., TV, Internet, Radio, etc.) 5.91 1.41 Merchandise I am likely to purchase Gators Foot ball teams licensed merchandise in the future 5.46 1.63 In the future, purchasing Gators Foot ball team licensed merchandise is something I plan to do 5.47 1.66 In the future, I intend to purchase licensed merchandise representing the Gators Football team 5.45 1.68

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99 Table 4-5. Descriptive statistics for relationship outcomes (iPod) Factors and items M SD Purchase Intention-iPod The likelihood that I will buy iPod pr oducts in the future is high 4.64 1.77 I intend to buy iPod products 4.53 1.74 I will purchase iPod products in the future 4.46 1.73

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100 Table 4-6. Descriptive statistics fo r consumption behaviors (iPod) Factors and items M SD Relationship Development It seems that I develop a new relation ship more easily than most people I know 4.40 1.48 I can easily make new friends 5.32 1.32 It usually takes only short time for me to make a new friend 4.94 1.44 Relationship Maintenance I can see that my core group of friends will stay close over the course of my life 5.32 1.39 I have a strong relationship w ith most of my friends 5.69 1.19 In general, relationships between my friends and me are very close 5.71 1.15

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101 Table 4-7. Summary results for initial measurement model of relationship quality (UF Football, Seven-Factor Model) Factors and items AVE Trust .848 0.59 The Gators Football team has integrity .603 I trust the Gators Football team .840 The Gators Football team is reliable .773 I can count on the Gators Football team .827 Commitment .924 0.76 I am committed to the Gators Football team .912 I am devoted to the Gators Football team .906 I am dedicated to the Gato rs Football team .878 I am faithful to the Gators Football team in spirit .774 Reciprocity .843 0.51 The Gators Football team unfailingly pays me back when I do something extra for it .654 The Gators Football team places my needs above its own needs .574 The Gators Football team gives me back equivalently what I have given them .744 The Gators Football team constantly returns the favor when I do something good for it .849 The Gators Football team pays attenti on to what I get relative to what I give them .779 Self-Connection .877 0.64 The Gators Football team remi nds me of who I am .749 The Gators Football teams image and my self-image are similar in a lot of ways .759 The Gators Football team is part of me .828 The Gators Football team and I have a lot in common .851 Love .908 0.71 I adore the Gators Football team .803 I am passionate about the Gators Football team .898 I am emotionally attached to the Gators Football team .840 I love the Gators Football team .838 Intimacy .876 0.64 I am very familiar with the Gators Football team .836 I know a lot about the Gato rs Football team .814 I feel as though I rea lly understand the Gators Football team .788 I am very close to the Gators Football team .773 Relationship Satisfaction .813 0.52 I am happy with my relationship with the Gators Football team .632 I am pleased with the relationship that I have with the Gators Football team .724 My relationship with th e Gators Football team is favorable .781 I am satisfied with my relationship w ith the Gators Football team .735

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102 Table 4-8. Summary results for measurement mode l of relationship quality (UF Football, SevenFactor Model) Factors and items AVE Trust .856 0.66 I can count on the Gators Football team 0.823 I trust the Gators Football team 0.773 The Gators Football team is reliable 0.843 Commitment .927 0.81 I am committed to the Gators Football team 0.915 I am devoted to the Gators Football team 0.911 I am dedicated to the Gato rs Football team 0.874 Reciprocity .839 0.58 The Gators Football team unfailingly pays me back when I do something extra for it 0.654 The Gators Football team gives me back equivalently what I have given them 0.743 The Gators Football team constantly returns the favor when I do something good for it 0.858 The Gators Football team pays attenti on to what I get relative to what I give them 0.767 Self-Connection .849 0.66 The Gators Football teams image and my self-image are similar in a lot of ways 0.738 The Gators Football team is part of me 0.851 The Gators Football team and I have a lot in common 0.850 Love .909 0.72 I adore the Gators Football team 0.802 I am passionate about the Gators Football team 0.899 I am emotionally attached to the Gators Football team 0.842 I love the Gators Football team 0.839 Intimacy .845 0.67 I am very familiar with the Gators Football team 0.876 I know a lot about the Gato rs Football team 0.850 I am very close to the Gators Football team 0.731 Relationship Satisfaction .792 0.55 I am pleased with the relationship that I have with the Gators Football team 0.684 My relationship with th e Gators Football team is favorable 0.819 I am satisfied with my relationship w ith the Gators Football team 0.711

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103 Table 4-9. Correlations among relationship quality construc ts (UF Football) 1 2 3 4 5 6 7 1. Trust 1.00 2. Commitment 0.77 1.00 3. Reciprocity 0.69 .49 1.00 4. Self-Connection 0.81 .80 .73 1.00 5. Love 0.77 .97 .50 .80 1.00 6. Intimacy 0.60 .80 .40 .70 .81 1.00 7. Satisfaction 0.79 .78 .58 .72 .73 .70 1.00

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104 Table 4-10. Summary results for measurement model of relationship quality (UF Football, FiveFactor Model) Factors and items AVE Trust .856 0.66 I can count on the Gators Football team 0.817 I trust the Gators Football team 0.774 The Gators Football team is reliable 0.847 Commitment .927 0.81 I am committed to the Gators Football team 0.900 I am devoted to the Gators Football team 0.913 I am dedicated to the Gato rs Football team 0.887 Reciprocity .839 0.57 The Gators Football team unfailingly pays me back when I do something extra for it 0.653 The Gators Football team gives me back equivalently what I have given them 0.743 The Gators Football team constantly returns the favor when I do something good for it 0.857 The Gators Football team pays attenti on to what I get relative to what I give them 0.768 Self-Connection .849 0.66 The Gators Football teams image and my self-image are similar in a lot of ways 0.739 The Gators Football team is part of me 0.851 The Gators Football team and I have a lot in common 0.849 Relationship Satisfaction .792 0.55 I am pleased with the relationship that I have with the Gators Football team 0.676 My relationship with th e Gators Football team is favorable 0.828 I am satisfied with my relationship w ith the Gators Football team 0.702

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105 Table 4-11. Correlations among relationshi p quality constructs (UF Football) 1 2 3 4 5 1. Trust 1.00 2. Commitment .78 1.00 3. Reciprocity .69 .48 1.00 4. Self-Connection .82 .80 .73 1.00 5. Satisfaction .78 .79 .57 .73 1.00

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106 Table. 4-12. Goodness of Fit indices and 2/ df values for the hypothe sized and alternative models (UF Football) Model RMSEA CFI SRMR WRMR 2/ df General .14 .77 .09 2.46 1080.09/104 = 10.39 Independent .16 .69 .38 11.08 1435.81/104 = 13.81 Group .07 .95 .04 1.24 319.68/94 = 3.40 Second-Order .08 .94 .05 1.54 380.43/99 = 3.84

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107 Table 4-13. Summary results for initial measurem ent model of relationship quality (iPod, SevenFactor Model) Factors and items AVE Trust .824 0.55 iPod is reliable .618 I trust iPod .808 iPod has integrity .653 I can count on iPod .871 Commitment .904 0.71 I am committed to iPod .807 I am devoted to iPod .850 I am dedicated to iPod .891 I am faithful to iPod in spirit .811 Reciprocity .879 0.60 iPod pays attention to what I get re lative to what I give them .676 iPod constantly returns the favor when I do something good for it .858 iPod unfailingly pays me back when I do something extra for it .780 iPod gives me back equivalently what I have given them .794 iPod places my needs above its own needs .755 Self-Connection .860 0.62 iPod is part of me .725 iPod and I have a lot in common .828 iPod reminds me of who I am .790 iPods image and my self-image are similar in a lot of ways .813 Love .889 0.67 I love iPod .774 I am passionate about iPod .865 I adore iPod .845 I am emotionally attached to iPod .791 Intimacy .864 0.61 I am very close to iPod .821 I feel as though I rea lly understand iPod .706 I am very familiar with iPod .796 I know a lot about iPod .791 Relationship Satisfaction .872 0.63 I am pleased with the relationship that I have with iPod .750 I am satisfied with my relationship with iPod .797 My relationship with iPod is favorable .848 I am happy with my relationship with iPod .768

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108 Table 4-14. Summary results for measurement model of relationship qualit y (iPod, Seven-Factor Model) Factors and items AVE Trust .809 0.60 iPod is reliable 0.627 I trust iPod 0.805 I can count on iPod 0.874 Commitment .898 0.74 I am committed to iPod 0.839 I am devoted to iPod 0.870 I am dedicated to iPod 0.878 Reciprocity .862 0.62 iPod pays attention to what I get re lative to what I give them 0.690 iPod constantly returns the favor when I do something good for it 0.884 iPod unfailingly pays me back when I do something extra for it 0.788 iPod gives me back equivalently what I have given them 0.775 Self-Connection .807 0.61 iPod is part of me 0.742 iPod and I have a lot in common 0.816 iPods image and my self-image are similar in a lot of ways 0.774 Love .889 0.67 I love iPod 0.785 I am passionate about iPod 0.865 I adore iPod 0.843 I am emotionally attached to iPod 0.782 Intimacy .843 0.61 I am very close to iPod 0.861 I am very familiar with iPod 0.736 I know a lot about iPod 0.730 Relationship Satisfaction .829 0.61 I am pleased with the relationship that I have with iPod 0.775 I am satisfied with my relationship with iPod 0.755 My relationship with iPod is favorable 0.819

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109 Table 4-15. Correlations among relations hip quality constructs (iPod) 1 2 3 4 5 6 7 1. Trust 1.00 2. Commitment .87 1.00 3. Reciprocity .54 .56 1.00 4. Self-Connection .72 .82 .84 1.00 5. Love .85 .95 .62 .88 1.00 6. Intimacy .84 .96 .46 .74 .89 1.00 7. Satisfaction .87 .80 .61 .70 .79 .78 1.00

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110 Table 4-16. Summary results for measurement model of relationship qual ity (iPod, Four-Factor Model) Factors and items AVE Trust .809 0.60 iPod is reliable 0.626 I trust iPod 0.803 I can count on iPod 0.876 Commitment .898 0.75 I am committed to iPod 0.851 I am devoted to iPod 0.881 I am dedicated to iPod 0.86 Reciprocity .862 0.62 iPod pays attention to what I get re lative to what I give them 0.694 iPod constantly returns the favor when I do something good for it 0.875 iPod unfailingly pays me back when I do something extra for it 0.788 iPod gives me back equivalently what I have given them 0.783 Relationship Satisfaction .829 0.61 I am pleased with the relationship that I have with iPod 0.77 I am satisfied with my relationship with iPod 0.757 My relationship with iPod is favorable 0.824

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111 Table 4-17. Correlations among relations hip quality constructs (iPod) 1 2 3 4 1. Trust 1.00 2. Commitment .87 1.00 3. Reciprocity .54 .55 1.00 4. Satisfaction .87 .78 .62 1.00

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112 Table. 4-18. Goodness of fit indices and 2/ df values for the hypothesized and alternative models (UF Football team) Model RMSEA CFI SRMR WRMR 2/ df General .15 .78 .10 2.82 790.10/65 = 12.16 Independent .18 .71 .36 10.44 1049.03/65 = 16.14 Group .07 .96 .05 1.38 188.76/59 = 3.20 Second-Order .07 .96 .05 1.48 200.53/61 = 3.29

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113 Table. 4-19. Summary results for measurement model of sport consumption behaviors (with Word of Mouth) Factors and items AVE Word of Mouth .823 0.62 I will encourage my friends and relatives to attend the Gators Football teams game(s) 0.724 I will recommend the Gators Football team whenever anyone seeks my advice 0.737 I will tell other people about how good Gator Football team is 0.895 Attendance .959 0.89 I intend to attend the Gators Football teams game(s) 0.918 The likelihood that I will attend the Gators Football teams game(s) in the future is high 0.971 I will attend the Gators Football teams game(s) in the future 0.940 Media .890 0.74 I will track the news on the Gators Football team through the media (e.g., TV, Internet, Radio, etc.) 0.763 I will watch or listen to the Gators Football teams game(s) through the media (e.g., TV, Internet, Radio, etc.) 0.883 I will support the Gators Football team by watching or listening to Gators Football teams game(s) th rough the media (e.g., TV, Internet, Radio, etc.) 0.928 Merchandise .952 0.87 I am likely to purchase Gators Foot ball teams licensed merchandise in the future 0.911 In the future, purchasing Gators Football team licensed merchandise is something I plan to do 0.937 In the future, I intend to purchase licensed merchandise representing the Gators Football team 0.949

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114 Table 4-20. Correlations among consum ption behaviors constructs 1 2 3 4 1. Word of Mouth 1.00 2. Attendance .80 1.00 3. Media .87 .67 1.00 4. Merchandise .84 .70 .76 1.00

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115 Table. 4-21. Summary results for measuremen t model of sport consumption behaviors Factors and items AVE Attendance .959 0.89 I intend to attend the Gators Football teams game(s) 0.915 The likelihood that I will attend the Gators Football teams game(s) in the future is high 0.974 I will attend the Gators Football teams game(s) in the future 0.938 Media .890 0.74 I will track the news on the Gators Football team through the media (e.g., TV, Internet, Radio, etc.) 0.759 I will watch or listen to the Gators Football teams game(s) through the media (e.g., TV, Internet, Radio, etc.) 0.886 I will support the Gators Football team by watching or listening to Gators Football teams game(s) th rough the media (e.g., TV, Internet, Radio, etc.) 0.928 Merchandise .952 0.87 I am likely to purchase Gators Foot ball teams licensed merchandise in the future 0.911 In the future, purchasing Gators Foot ball team licensed merchandise is something I plan to do 0.938 In the future, I intend to purchase licensed merchandise representing the Gators Football team 0.948

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116 Table 4-22. Correlations among sport c onsumption behaviors constructs 1 2 3 1. Attendance 1.00 2. Media .66 1.00 3. Merchandise .70 .76 1.00

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117 Table. 4-23. Goodness of fit indices and 2/ df values for the hypothesized and alternative models for sport consumption behaviors Model RMSEA CFI SRMR WRMR 2/ df General .26 .71 .10 1.94 958.03/27 = 35.48 Independent .20 .84 .42 9.27 544.88/27 = 20.18 Group .04 .99 .02 .40 42.52/24 = 1.77 Second-Order .04 .99 .02 .40 42.52/24 = 1.77

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118 Table 4-24. Summary results for measurement model of consumption behaviors (iPod) with Word of Mouth Factors and items AVE Word of Mouth-iPod .893 .74 I will recommend iPod whenever an yone seeks my advice 0.810 I will tell other people a bout how good iPod is 0.826 I will encourage my friends and relatives to buy iPods product(s) 0.934 Purchase Intention-iPod .950 .86 The likelihood that I will buy iPod pr oducts in the future is high 0.911 I intend to buy iPod products 0.943 I will purchase iPod products in the future 0.931

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119 Table 4-25. Correlations among consumption behavior s constructs (iPod) with Word of Mouth 1 2 1. Word of Mouth 1.00 2. Purchase .87 1.00

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120 Table 4-26. Summary results for measuremen t model of purchase behavior (iPod) Factors and items AVE Purchase Intention-iPod .95 .86 The likelihood that I will buy iPod pr oducts in the future is high 0.912 I intend to buy iPod products 0.938 I will purchase iPod products in the future 0.936

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121 Table 4-27. Summary results for measur ement model of relationship style Factors and items AVE Relationship Development .879 .72 It seems that I develop a new relati onship more easily than most people I know 0.742 I can easily make new friends 0.920 It usually takes only short time fo r me to make a new friend 0.876 Relationship Maintenance .842 .67 I can see that my core group of friends will stay close over the course of my life 0.671 I have a strong relationship with most of my friends 0.870 In general, relationships between my friends and me are very close 0.892

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122 Table 4-28. Correlation between re lationship style constructs 1 2 1. Relationship Development 1.00 2. Relationship Maintenance .44 1.00

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123 Figure 4-1. Second-order hierar chical model (UF Football)

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124 Figure 4-2. Second-order hier archical model (iPod)

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125 Figure 4-3. Second-order model fo r sport consumption behavior

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126 Figure 4-4. Structural regressi on of relationship quality and sport consumption behaviors

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127 Figure 4-5. Structural regressi on of relationship quality and sport consumption behaviors

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128 Figure 4-6. Interaction effect of relationship development on re lationship between relationship quality and sport consumption behaviors

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129 Figure 4-7. Interaction effect of relationship development on re lationship between relationship quality and purchase intention for iPod

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130 Figure 4-8. Interaction effect of relationship maintenance on re lationship between relationship quality and sport consumption behaviors

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131 Figure 4-9. Interaction effect of relationship maintenance on re lationship between relationship quality and purchase intention for iPod

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132 CHAPTER 5 DISCUSSION The primary purpose of this dissertation was to provide a theoretically-based and empirically tested account of the relationship quality between team and sport consumers and the role of relationship quality in sport consumpti on behaviors. To achieve these goals, first, measurement scales for relationship quality, cons umption behavior, and relationship personality were developed relying on literat ure on relationship quality acro ss various contexts. Second, the measurement scales were tested and validated through assessment of essential psychometric properties of the scales based on results from mul tiple CFAs. Third, the stru ctural nature of the relationship quality and consumption behavior s constructs were explored through model comparisons. Next, the relationship between rela tionship quality and consumption behaviors was examined by conducting structural regression (S R) models. Lastly, the potential moderating effects of relationship personality on relationship quality-cons umption behaviors relationship were tested with SR models that incorporated interaction terms. This section will begin with discussion on the results from the various anal yses throughout the dissertation. Next, conceptual and theoretical contributions of the research findi ngs from this study will be discussed and then managerial implication of relationship framewor k in sport context will be followed. Lastly, limitations of the study will be addressed as well as suggestions for future research. Validation of the Measures Relationship Quality Constructs (UF Football Team) A main goal of this dissertation was to investigate the following research question: How should relationship quality between a team and its sport consumers be conceptualized and measured? This objective has been largely achieve d through developing a scale that measures the relationship quality between team and sport cons umer and initially validating the scale. The

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133 results from this study provide evidence that the final scale (after modifications) possesses adequate psychometric properties: (1) Content validity was established by the review of literature, expert review, and a te st of content validity; (2) Inte rnal consistency values for all constructs were greater than a widely accepted cutoff criterion; (3) Construct reliability was evidenced by high AVE values for all constructs; a nd (4) Significant results from the tests of the difference from unity for all pairs of construc ts suggested adequate discriminant validity. The literature on relationship quality suggested that there are seven relation quality dimensions: Trust, Commitment, Reciprocity, Self-Connection, Relationship Satisfaction, Love, and Intimacy. However, the empirical results from the data referent to the UF Football team provide support for a five-factor model consisti ng of Trust, Commitment, Reciprocity, SelfConnection, and Relationship Satisf action. Love and Intimacy were in itially regarded as distinct dimensions of relationship quality but the re sults indicated that th e two factors lacked discriminant validity. This result is inconsistent with previous research, which typically viewed Love and Intimacy as distinct concepts (B arnes, 1997; Fletcher, Simpson, & Thomas, 2000; Fournier, 1994; Monga, 2002; Nich olson et al., 2001; Pawle & C ooper, 2006; Smit et al., 2007) One primary explanation for the lack of discri minant validity of the two factors lies in a gap between semantic or theoretic al distinction made by research ers and actual distinction made by respondents. This discrepancy might occur because the respondents were not sufficiently involved in the evaluation process to be able to differentiate the items purported to measure distinct concepts or because the respondents were not capab le of making sophisticated distinctions between those concepts as researcher s were. If the discrepancy resulted from the lack of sufficient attention or i nvolvement of participants, it can be reduced by improved survey methods. For example, the number of questions in the survey can be reduced or incentives can be

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134 offered to participants. Then, discriminant validity of the construct should be reexamined. If the discrepancy stemmed from the respondents inherent incapability to differentiate the concepts, it can be concluded that those constructs are redundant in expl aining relationship quality although they might be representing theoretically distinct concepts. Therefore, more empirical studies are needed to identify the so urce of the weak or poor discrimina nt validity for some factors (e.g., Love and Intimacy) proposed in this study and dete rmine the factors that are essential to measure the relationship quality between teams and sport consumers. Relationship Quality Constructs (iPod) The results from the data referent to iPod indi cate that the proposed scale for relationship quality possessed acceptable content validity, in ternal consistency, a nd construct reliability. Initially, a seven-factor model, which incorporated Trust, Commitment, Reciprocity, SelfConnection, Relationship Satisfaction, Love and Intimacy, was proposed. However, the empirical results from the iPod data support a four-factor model, which exclude Love, Intimacy, and Self-Connection; leaving Trust, Commitme nt, Reciprocity, and Relationship Satisfaction. Similar to the data specific to the UF Football team, respondents did not differentiate the items purported to measure Love, Inti macy, and Self-Connection constr ucts from items intended to measure the other constructs. This result is inconsistent w ith previous studies, which rega rded Love, Intimacy, and SelfConnection as distinct concepts (Barnes, 1997; Fletcher, Simpson, & Thomas, 2000; Fournier, 1994; Monga, 2002; Nicholson et al., 2001; Pawle & Cooper, 2006; Smit et al., 2007). Again, this lack of discriminant validity of the thre e factors can be explai ned by the gap between a theoretical distinction made by th e researcher and the actual dis tinction made by the respondents. This disagreement might be caused by the respon dents lack of involve ment or an inherent incapability to distinguish the concepts. Therefore, the source of the discrepancy should be

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135 investigated through more empiri cal studies to determine the e ssential factors to explain the nature of the relationship quality. Interestingly, examination of modification indices (MI) reveals th at the respondents had greater difficulty distinguishing the items inte nded to measure Self-Connection from the items purported to measure the other c onstructs in the iPod case compared to the UF Football team case. In addition, the overall mean score for th ree Self-Connection items in the iPod version was 2.77, which was noticeably lower than the overall mean score for three Self-Connection items ( M = 3.56) in the UF Football team version. Taken to gether, these results s uggest that the SelfConnection concept was more applicable in expl aining the relationship between the UF Football team and sport consumers than the relationship between iPod and consumers. This finding is consistent with the previous research that argued that identification with teams, which paralleled with Self-Connection in this study, was one of main character istics differentiating sport consumption behaviors from general consump tion behaviors (Cialdin i, 1976; Sloan, 1989; Gladden & Sutton, 2008; Madrigal, 1995, 2003; Tra il et al. 2003; Trai l et al., 2005; Wann & Branscombe, 1993). However, only one brand (i .e., UF Football and iPod) from each product category (i.e., sport and general manufactured products) was investig ated in this study. Therefore, the finding should be interpreted wi th caution due to its limited generalizability. Sport Consumption Behavior s and Relationship Style After the initial CFA, the AVE value for Word of Mouth was smaller than the squared correlation between Word of Mouth and all other factors, indicating the lack of discriminant validity of the Word of Mouth factor with the other factors in the model. The lack of discriminant validity and the parsimoniousness of the model were considered collectively in reaching a final decision to eliminate the Word of Mouth construct. The results from this study indicate that the final scale for sport consumption behavior s possessed good content validity,

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136 internal consistency, construct reliability, and di scriminant validity. This result augments the previous attempts (Fink et al., 20022005; Lee & Trail, 2007Trail et al., 2005) in developing scales to measure sport consumption behaviors. The scale measuring relationship style initial ly consisted of 12 items; however, 6 items were dropped based on the assessment of factor loadings and theoretical relevance throughout the pilot study and the initial CFA in the main study. The final scale for re lationship style, which consisted of the Relationship Development a nd Relationship Maintenance factors, had good content validity, internal consistency, constr uct reliability, and disc riminant validity. Structural Nature of Relationship Quality UF Football Team With the scale developed to measure individu al components of relationship quality (Trust, Commitment, Reciprocity, Self-Connection, a nd Relationship Satisfaction) in hand, the structural nature of the constructs was explored by comparing and testing four models (general relationship quality factor model, independent factor model, group factor model, and secondorder hierarchical model), which differed as to how the individual relations hip quality constructs were associated with each other. Although a m odified second-order factor model was initially considered, it was eliminated because two f actors (i.e., Love and Intimacy), which were hypothesized to tap into a secondorder latent variable, Affec tive Relationship Quality, were dropped after the construct valida tion procedure. Therefore, th e hierarchical model specifying two second-order latent factors wa s no longer a tenable model. The results from the data referent to UF F ootball team clearly do not support the general relationship quality factor model, which hypothesized that distinct relationship quality facets did not exist, but a global relationshi p quality factor should represent all individual factors. This is consistent with previous research, which typically identified Trust, Commitment, Reciprocity,

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137 Self-Connection, and Relationship Satisfaction as distinct dimensions of relationship quality (Fletcher et al., 2000; Morgan & Hunt, 1984; Fo urnier, 1998; Roberts et al., 2003). Therefore, the rejection of the general relationship quality fa ctor model is both theoretically and empirically justified. The results also do not provide suppor t for the independent factor model, which proposed that all the relationship quality dimensions were complete ly independent. This result is in line with previous research findings, which reported that the fi ve relationship dimensions were correlated with each other (G arbarino & Johnson, 1999; Mogan & Hunt, 1984; Nicholson et al., 2001; Stern, 1997; Uhl-Bien & Maslyn, 2003). Hence, the independent factor model is excluded from further consideration. The group factor model, which specify that re lationship quality constructs were related to each other but had no higher-order relationship quality construct, fit the data well. This result is consistent with previous research, which viewed that individual relations hip quality constructs were related but still distinct. The second-order hierarchical model, which was a major focus of this study, posited that first-orde r latent relationship quality f actors were indicators measuring underlying higher-order relationship quality factor. The model also fit the data well. The result supports the notion that people make evaluative judgments on individual relationship quality constructs, which were related but different domains, consistently based on a higher-order factor of overall relationship quality (DeW ulf et al., 2001; Fletcher et al., 2000; Fournier, 1994; Lages, Lages, & Lages, 2005). Although the second-order hierarchical factor model and the group factor model fit the data adequately, the second-order model was accepted as the most tenable model for the following reasons. First, the high intercorrelations between the di fferent aspects of relationship quality supported the notion that these individual constructs are i ndicators of a more general,

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138 higher-order latent relationship-qua lity construct. Second, the struct ural part of the group factor model was saturated and always fits the data perfectly. The saturated model is less desirable because it cannot be rejected by data and therefore, there is no way to empirically test or confirm the plausibility of the model (Raykov & Marcoulides, 2000). Next, although one primary interest of this study was to understand the structural na ture of the relationship quality constructs, the group factor model does little to explain how the relationship quali ty constructs are structured. Finally, the hierarchical natu re of the relationship quality constructs na turally cause multicollinearity between individual factors. The multicollinearity can make it difficult to evaluate the contribution of each factor as a relationship quality facet in predicting consumption behavior in the ensuing structural regression anal ysis. When multicollinearity is detected, it is recommended to use a composite measure or scal e (Tabachnick and Fidell, 2007). Therefore, the second-order factor model specifying a second-or der factor, which is a composite measure of first-order relationship quality fact ors, is preferable in addressing the problem associated with the multicollinearity between first order factors. Although the second-order hierarchical model wa s chosen over the group factor model for the ensuing SR analyses in this study, it should be noted that the two models are rather complementary than competitive. In fact, the group factor model only specifies that the first order constructs are correlated with each other to some extent. Du e to the unconstrained nature of the structural specification of the model, the gr oup factor model does not either empirically or theoretically contradict the second-order hierarchical model, which attempts to provide more detailed explanation for the correlation between the first order factors. Thus, the group factor model could be considered as a basic model to ev aluate how well the indivi dual latent constructs are measured by observed variable and initially explore how those constr ucts are structurally

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139 related with each other when a sp ecific structure that would ac count for the relationships among the first order factors are not clearly determined (Kline, 2005; Rindskopf & Rose, 1988). With the basic model in hand, plausible structural sp ecifications based on theory (e.g., second-order hierarchical structure in this study) can be investigat ed to explain the co rrelations among first order factors in a more specific and parsimonious way than the broader specification for a general factor model would do. iPod The results from the data referent to iPod cl early did not support th e general relationship quality factor model and independent factor mode l. This result is consistent with previous research, which viewed that the four relationship quality constr ucts (i.e., Trust, Commitment, Reciprocity, Relationship Satisfactio n) were related but distinct (Fletcher et al., 2000; Morgan & Hunt, 1984; Fournier, 1998; Nic holson et al., 2001; Roberts et al., 2003; Stern, 1997; Uhl-Bien & Maslyn, 2003). Both the second-order hierarchical factor model and the group factor model fit the data well. However, the second-order model was selected as the most tenable model for the same reasons discussed in the previous section. Sport Consumption Behaviors (UF Football) Similar to relationship quality, it is evidenced that the general relationship quality factor model and independent factor mode l did not fit the data well. This finding is in line with the previous research, which regard ed the attendance, media consum ption, and licensed merchandise purchase as related but distinct aspects of sport consumption beha vior (Fink et al., 2002; GarcioHarrolle, 2007; Trail et al. 2003; Trail et al., 20 05). Both the second-order hierarchical factor model and the group factor model yielded the same predicted correlation s and have equal fit statistics including goodness of fit indices and model chi-square value. Therefore, it cannot be determined which model should be preferred over the other based on the model fit. In the current

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140 study, the second-order model was chosen as th e most suitable model over group factor model for the same tenets given as a basis for the decision regarding which model to be accepted among the alternative models for relationship quality. Outcomes of Relationship Quality One of the main objectives of this dissertati on is to answer the following question: Does relationship quality significantly and meaningfully explain spor t consumption behaviors? To achieve this objective, first the measurement s cale for relationship quality was developed and tested as discussed in the earlie r section. Then, the predictive capaci ty of relationship quality was assessed using intentions for three sport consumer behaviors of interest (i.e. Attendance, Media Consumption, and Licensed Merchandise Purchase) as dependent variables. As expected, results from the SR model (for the data referent to UF Football team) indicated that the second-order latent Relationship Quality factor significantly influenced the second-order latent Sport Consumption Behaviors factor, expl aining 67% of its variance. This result was consistent with the Fourniers (1994) finding that relationship quality was a major pred ictor of behavioral dependence. Fournier found that customers who perceived a hi gh quality relationship with a brand or company did not only purchase more produc ts from the brand or the company but also expand scope, diversity and fre quency of brand-related or comp any-related activities. This behavioral dependence might expl ain the finding from the current study that showed the fans who perceived a higher level of relationship qua lity intended to consume sport through media. Next, the result is also in line with the Park et al.s (2002) finding th at a higher level of relationship quality resulted in positive attitude toward brand ex tension. That is, consumers who perceived good relationship quality were more lik ely to buy products which used the same brand name. Accordingly, the current study showed that sport consumers who perceived good relationship quality intended to buy more team licensed products. Finally the result from this

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141 study supports the authors propo sition that sport consumers who perceive a higher level of relationship quality intend to attend more games. This result is in agreement with previous research, which found that relationship quality wa s a salient predictor of various aspects of consumption behaviors. Hennig-Thurau and Kl ee (1997) suggested that relationship quality significantly influenced repeat purchase behaviors. Some empi rical evidence has been reported as well (Reynolds & Beaty, 1999). Palmatier et al. (2006) found that relationship quality explained an average of 52% of variance in pu rchase intention in a meta-analysis using 50 empirical studies in the consumer products context. In addition, Fournier (1994) suggested that brand relationship quality was a superior predic tor of purchase intention to brand attitude and satisfaction because brand rela tionship quality accounted for 61% of variance in purchase intention, while brand attitude and satisfaction accounted for 37% and 52% of variance in purchase intention. The relationship between relati onship quality for iPod and Purchase Intention was also assessed. Similar to the results from the data refe rent to the UF Football team, Purchase Intention for iPod was significantly affected by the second-o rder latent Relationship Quality factor and a large proportion of the variance (64%) in Purchase Intention was accounted for by Relationship Quality. This result confirms previous liter ature, which found a str ong association between relationship quality and various consumption behavi ors of interest (Crosby et al., 1990; De Wulf et al., 2001; Doney & Cannon, 1997; Hennig-Thurau et al., 2002; Sird eshmukh et al, 2002; Palmatier et al., 2006; Reynolds & Beaty, 1999). Moderators of Relationship Qu ality-Consumption Association Once a significant relationship between rela tionship quality and consumer behavior intentions had been found, the following question was raised: Does the nature of association between relationship quality a nd intentions differ by the psyc hographic characteristics of

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142 consumers? Relationship Development style and Relationship Maintenance style were selected as potential moderators and th e influence of the two constr ucts on the linkage between relationship quality and consumption be haviors intention was investigated. The strength of the associations between relationship quality and sport consumption behaviors intention did not vary with the proposed moderators. This is inconsistent with Fourniers (1994) finding that re lational personality trai ts moderated the influence of relationship quality on behavioral outcomes. The lack of an interaction effect might provide an evidence that relationship quality is an impor tant predictor of sport consum ption behavior regardless the psychographic characteristics of sport consumers. However, the finding could be sample specific and should be interpreted with caution. Theref ore, the finding from this study should be replicated with samples varying in dem ographic, psychographic, and socioeconomic characteristics. Similarly, the association between the Relationship Quality and Purchase Intention was not moderated by Relationship Maintenance and Relationship Development. Implications of the Research The present research has both academic and practical implications. In this section, conceptual and theoretical implications are di scussed. Then managerial implications follow. Conceptual and Theoretical Implications In this dissertation, a relationship quality fr amework for sport consumption behavior was proposed for a better understanding of the relatio nship between sport consumers and sport teams. This study makes a contribution to the curr ent literature in a number of ways. First, the author investigated the nature of relationship quality perceived by sport consumers and developed a conceptual model cons isting of five critical constructs in sport consumption context: Trust, Commitment, Reciprocity, Self-Connecti on, and Relationship Satisfaction. There are few studi es that incorporate the constr ucts under relationship quality

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143 framework. Therefore, the development of th e conceptual model will help researchers understand the nature of the relationship between sport consumers and the team with more comprehensive ideas of relationship quality. Mo reover, this study extended sport management literature by applying relati onship marketing theories to the spor t consumer behavior realm. Both relationship marketing and sport management res earch can benefit from the validation of the current knowledge about relati onship marketing within sport consumption contexts and the integration of new research findings from this study. Second, this study provides an empirical examination of the relationship quality framework in the sport consumption context. While the current studies on relationship marketing that exist in the sport management area have advanced the conceptual understandings of relationship marketing (Bee & Kahle, 2006; Cousens et al., 2006; McDonald & Milne, 1997; Tower et al., 2006), few studies empirically examine re lationship marketing th eories applied to the relationship between sport organizations and th eir relationship partners. This study collected empirical evidence for what were previously on ly assumptions suggestin g that the relationship metaphor was applicable to sport consumer beha viors and suggesting that relationship quality was a critical predictor of sports consumption behaviors. Th ese empirical findings extend our understanding of relationship marketing in a sport consumption context beyond a mere argument or grounded theory. Next, this study attempts to develop and te st a scale to measure relationship quality perceived by sport consumers. A review of the extant work reveals that there are numerous scales to measure relationship quality in various contexts. However, no scale was developed to measure the quality of sport consumer-team rela tionship. A relationship quality scale for sport consumption behavior was developed through a ri gorous scale development process including an

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144 extensive review of literature, expert review, a content validity check, and a pilot study. Then, the scale was initially validated, showing that the scale exhibited good c ontent validity, internal consistency, and construct reliability. A psycho metrically sound scale developed in this study will help researchers move forward in their understanding of the relationship between sport consumers and teams in particular. Managerial Implications Sport managers are now more interested in developing and maintaini ng relationships with their consumers. In addition, sport consumers are willing to engage in relationship with teams. However, relationship marketing practices in spor t teams are still rudimentary. The findings from this dissertation also have so me managerial implications. For sport managers, the findings from this study validate the widely-held assumption in practice that good relationships with sport consumers is a critic al factor for a successful sport business. Managerial decisions based on the allocation of resources for relationship marketing depends on evidence of its capability to yiel d meaningful performance outcomes. Sport managers need to know the payoff to be obt ained from the investment on cultivating the relationship with their consumers is valuable. This study showed that when sport consumers perceive that they have a good relationship with a sport team, they are more willing to attend games, buy team licensed merchandise, and consum e sport contents related to the team through media. Moreover, the strength of the associ ation between relationship quality and sport consumption behaviors was substantial. In sum, the findings from this study demonstrate the value of establishing good relationships with sport consumers, which are crucial factors in managerial decision making, and ther efore justify the considerable efforts to build and maintain strong consumer relationships.

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145 The relationship quality framework and th e developed scale for relationship quality constructs can serve a number of essential purposes in the sport ma nagement context. First, using the instrument, sport managers can identify level of quality of relationship with the consumers and develop relationship management strategies based on the information. Next, the modified measure developed in this study, which demons trated good reliability and validity, can be a useful tool to appraise the effectiveness of the relationshi p marketing campaign. Measuring effectiveness of marketing campaigns is essentia l for sport marketer to understand how well their marketing programs are performing in terms of achieving the marketing objectives and what adjustments need to be made to enhance performance. Although measuring the effectiveness of a marketing campaign is difficult and expensive, the benefits obtained from the efforts are typically much greater than thes e costs. By storing and tracking relationship quality regularly with the aid of the now readily available database management system, sport managers can determine whether their relationship marketing actions are effectively enhancing or, instead, worsening the relationships. Furthermore, the proposed scale, which consisted of multiple subcomponents of relationship quality, provides a dia gnostic tool to discover which aspects of the relationship are damaged such that remedial actions should be taken. For example, although reciprocity was found to strongly affect the intention for sport consumption behaviors in this study, the participants of this study did not percei ve their relationship with the UF football team to be reciprocal. This is the type of information on which sport marketers and managers of the team need to focus to improve the relationship wi th the sport consumers and eventually increase the consumption of the teams products. Lastly, this also provides sport managers with essential insights for human resource management. Due to the nature of the sport pr oduct as a service, the interactions between

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146 employees and sport consumers play a major role in determining the quality of the teams relationship with their customers. For this r eason, when hiring personnel, managers need to consider if the candidates have the capability to properly and socially interact with their consumers. By incorporating the relationship marketing framework in training programs, the managers can help staff understand the importan ce of the relationship with the consumers and perform the activities related to relationship deve lopment. In addition, managers need to keep motivating their employees to actively engage in the process to deve lop and maintain the relationship with consumers. Limitations and Future Directions Although this dissertation has provided valuable insight into understandin g relationship quality, there are some limitations that should be considered for future research. The first limitation is related to the sample used in this study. Although da ta was not collected entirely from students, the majority of the participants in this study were college students. This might limit the generalizability of the findings from th is study. In addition, the context of this study, a college football team, might also limit the ge neralizability of the findings. Therefore, the generalizability of the findings could be impr oved by using broader and wider sampling frames in various sport contexts (e.g., professional football and womens basketball) for future studies. Second, cross-sectional data were utilized in this research. Al though the causal relationship was hypothesized based on theory, the time sequence of the relationship between relationship quality and intentions for consumption behaviors cannot be confirmed by the data used in this study. Therefore, longitudinal studies can provide stronger evidence for the model developed and tested in this research. Next, the scale developed and in itially validated in this study requires further refinement. The scale exposed a problem with some constructs regarding discriminant validity as mentioned in earlier sections. In addition, relatio nship quality constructs included in this study

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147 might not be the full range of possible components. Hence, further empirical testing with a more comprehensive set of distinct relationship qua lity constructs will help fully understand the relationship between sport consumers and teams. The extant literature and research findings from this study identify several interesting avenues for the future research. These avenues of inquiry provide sport management researchers ample opportunities. These include, but are not limited to, investigation of the following questions: Is there a sequential order among re lationship quality constructs? If the sequential order exists, how are the relationship quality constructs are grouped and arranged in the hierarchy What are the most effective strategies to improve relationship quality? What are potential mediators intervening rela tionship between relati onship quality and its outcomes? What are the antecedents and other outcomes of relationship quality? How does the nature of the linkage betw een relationship quality and consumption behaviors vary for people across different cultures and countries? Summary In summary, a five factor model includ ing Trust, Commitment, Reciprocity, SelfConnection, and Relationship Sati sfaction was supported to best measure relationship quality between sport consumers and the UF Football team However, a four factor model incorporating, Trust, Commitment, Reciprocity, and Relationshi p Satisfaction was supported to best represent relationship quality for iPod. Regarding the structur al nature of relationshi p quality, results from both data referent to UF Football Team and iPod provided support for a second-order hierarchical factor model. A sport consumption behavior model, which consisted of Intention for Attendance, Media Consumpti on, and Licensed Merchandise C onsumption, was also best

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148 explained by a second-order hierarchical model. In addition, relationshi p quality significantly influenced sport consumption behaviors related to the UF Football team and purchase intentions for iPod. None of potential moderators influen ce the relationship between relationship quality and its outcomes. Finally, research ers and sport industry practitione rs should further examine the proposed relationship quality model in this study.

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BIOGRAPHICAL SKETCH Yu Kyoum Kim earned his Doctor of Philos ophy degree in health a nd human performance (sport management) from the University of Florida in August 2008. He received his Master of Science degree (sport management) from Seoul National University in February 2004. He received his Bachelor of Science in physical education from Seoul National University in February 1998. The goal of his research is to improve both the quantity and quality of the understanding of sport consumer behavior and to build a bridge between academia and the sport industry. Beyond his relationship marketing resear ch agenda, he has been pursuing research projects on how constraints, motives, and identifi cation influence various behavioral aspects of sport consumption such as media and mercha ndise consumption and event attendance. In addition, he is interested in development and application of statistic al methods for sport management research. His accomplishments in the research areas above include (1) two referred publications, (2) seven manuscripts that are currently under review in the most prestigious journals including the Journal of Sport Management, Sport Marketing Quarterly, and Leisure Science, (3) 10 research presentations, two abstracts under review. The presentations have been presented or will be presented at conferences for the North American Society for Sport Management (NASSM), Sport Marketing Association (SMA), International Conference on Sport and Entertainment Business (ICSEB), and International Conference on Service Management. He has taught various undergraduate courses such as Administration of Sp ort and Physical Activities, Introduction to Sport Management, Basketball, Conditioning, and Jogging. Beginning fall 2008, he will serve as Assistant Professor of Spor t Management at the Florida State University.