Internet adoption in post-communist countries

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Internet adoption in post-communist countries a proposed model for the study of internet diffusion
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by Daniela V. Dimitrova.
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INTERNET ADOPTION IN POST-COMMUNIST COUNTRIES:
A PROPOSED MODEL FOR THE STUDY OF INTERNET DIFFUSION














By

DANIELA V. DIMITROVA


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

UNIVERSITY OF FLORIDA


2003














ACKNOWLEDGMENTS

I greatly appreciate the guidance and support of Dr. Sylvia Chan-Olmsted, my

dissertation chair. Thanks are also due to all of my other committee members. Professor

Wayne Wanta, now at the University of Missouri, was instrumental to the beginning of

this project, and his guidance with the requisite job search at the end was invaluable. Dr.

Kurt Kent was always available for help and advice, both related and unrelated to my

dissertation research. Professor Mindy McAdams believed in my success and contributed

to my development as a teacher and scholar. Last but not least, I want to thank my

external member, Dr. Rich Beilock, who led me to my dissertation idea and also kept me

on my toes, helped with the data collection, offered valuable methodological assistance,

all with a sense of humor.

I thank my mentor, Dr. Lynda Lee Kaid, who was always there for me and whose

passion for research served as a wonderful example.

I would like to thank my parents, Velitcka Ivanova Boytcheva and Vesselin

Dimitrov Boytchev, for their endless support and encouragement in all my endeavors.

Their love for learning and belief in my success is my deepest inspiration.

Thanks go to all my dear friends here in Gainesville and around the world.

Finally, I wish to thank Alexander, who firmly stood by me all the way through this

challenging process. His love and support are invaluable.















TABLE OF CONTENTS
Page

ACKN OW LEDGM ENTS................................................................................................... ii

LIST OF TABLES ........................................................................................................ vi

LIST OF FIGURES...................................................................................................... vii

ABSTRACT ..................................................................................................................... viii

1 INTRODUCTION ............................................................................................................ 1

Internet Significance.................................................................................................... 1
Econom ic Contributions.............................................................. ......................2
Political Contributions.......................................................................................... 3
Technological Contributions................................................................................. 4
Social Contributions ....................................................................... ................... 5
Other Contributions .............................................................................................. 6
Post-com m unist Countries...................................................................... .................. 7
Transition Progress ...............................................................................................7
Geographic Regions.............................................................................................. 9
Economic Inequalities........................................................................................... 9
Need for Research of Internet Diffusion............................................................. 10
Research M ethod........................................................................................................ 16
Dissertation Outline ................................................................................................... 17

2 INTERNET AND SOCIETY ......................................................................................... 18

Developm ent of the Internet ...................................................................................... 18
The Invention of the Internet.............................................................................. 18
Internet Growth and G lobal Expansion.............................................................. 21
Internet and Political Developm ent............................................................................ 25
Dem ocracy and the Internet................................................................................ 26
Free Press and the Internet.................................................................................. 29
Internet and Economic Developm ent......................................................................... 31
Lower Production and Distribution Costs.......................................................... 32
The Internet Econom y ........................................................................................ 33
Global M markets ................................................................................................... 34
Leapfrogging....................................................................................................... 35




iii








3 LITERATURE REVIEW ............................................................................................... 37

Diffusion of Innovations ............................................................................ .......... 37
Basic Generalizations ....................................................................... ............. 38
Technology Innovation Attributes...................................................................... 39
Cluster Innovations............................................................................................. 42
Types of Adopters...............................................................................................43
Other Comm unication Technologies.................................................................. 46
Levels of Internet Adoption................................................................................48
Other Considerations for Internet Adoption ....................................................... 49
New M edia Technologies Research........................................................................... 50
Econom ic Factors ............................................................................................... 51
Political Climate and Policy ............................................................................... 57
Technology/Infrastructure .................................................................................. 66
Audience Characteristics ....................................................................................69
Cultural Factors............................................................................... .................72
Conceptual Fram ework.............................................................................................. 76
Further Thought ......................................................................................................... 77

4 M ETHODS..................................................................................................................... 82

Research Design......................................................................................... ........... 82
Data Collection ................................................................................................... 84
Operational Definitions....................................................................................... 85
Economic variable................................................................................... 85
Political clim ate and policy variables.......................................................... 86
Technology/Infrastructure variable............................................................. 88
Audience variables ...................................................................................... 89
Cultural variable .......................................................................................... 90
Dependent variable...................................................................................... 90
The M odel........................................................................................................... 95
Statistical Procedures................................................................................................. 96
M multiple Regression Technique.......................................................................... 96
Stepwise Regression ........................................................................................... 99
Hypotheses............................................................................................................... 100
Proposition 1 ..................................................................................................... 100
Proposition 2..................................................................................................... 100
Proposition 3..................................................................................................... 101
Proposition 4..................................................................................................... 101
Proposition 5..................................................................................................... 102
Proposition 6..................................................................................................... 102
M ethodological Notes.............................................................................................. 102

5 RESULTS..................................................................................................................... 107

Descriptive Analysis................................................................................................ 107
Internet Users.................................................................................................... 107








Gross National Product..................................................................................... 109
Dem ocratization................................................................................................ 110
Telecomm unications Privatization ................................................................... 111
Teledensity............................................................ ............................................ ll
Education.......................................................................................................... 112
Religion............................................................................................................. 112
Bivariate Correlations ....................................................................................... 112
Regression Results................................................................................................... 113
Statistical Assum options ......................................... ............................................ 113
Hypotheses Testing ........................................................................................... 115
Final M odel ....................................................................................................... 119
Tobit Estim ates........................................................................................................ 124

6 DISCUSSION .............................................................................................................. 126

Overview .................................................................................. ................................ 126
Discussion of Descriptive Analysis ......................................................................... 128
Regional Variations .......................................................................................... 128
Growth of Internet Use..................................................................................... 130
Discussion of Hypotheses 2 through 6 ................................. .................................... 134
National Incom e...................................................................................... . .......... 134
Dem ocratization................................................................................................ 136
Telecomm unications Privatization ................................................................... 138
Infrastructure..................................................................................................... 140
Education .................................................... ...................................................... 142
Religion ............................................................................................................. 144
Refined Conceptual Fram work ..................................... ......................................... 147

7 CONCLUSION .............................................................. .............................................. 151

Conclusions.............................................................................................................. 151
Im plications.............................................................................................................. 153
Theoretical Implications ................................................................................... 153
Applied Im plications................. ............................................................... ........ 155
Limitations............................................................................................................... 159
Validity........................................................................................ ..................... 160
Internal validity.......................................................................................... 160
External validity ........................................................................................ 163
Reliability.......................................................................................................... 164
Suggestions for Future Research.............................................................. ................ 165

LIST OF REFERENCES .................................................................................... .............. 169

BIOGRA PHICAL SKETCH ...................................................... .................... ............... 184














LIST OF TABLES


Table pae

1-1. Internet Hosts per 10,000 population in 1995 and 1999.......................................... 15

4-1. Definition of variables in the proposed model of Internet diffusion ....................... 83

4-2. Correlation matrix for the continuous independent variables ............................... 105

5-1. Internet users per 10,000 people in 1999............................................................... 109

5-2. Descriptive statistics of variables .......................................................................... 110

5-3. Pearson correlations between dependent and independent variables .................... 113

5-4. Regression results for Internet users...................................................................... 116

5-5. Summary of hypothesis testing.............................................................................. 118

5-6. ANOVA Table for Complete M odel ..................................................................... 120

5-7. ANOVA Table for M odel 2................................................................................... 121

5-8. ANOVA Table for M odel 3................................................................................... 122

5-9. ANOVA Table for Model 4................................................................................... 123

5-10. Tobit estimates for final model.............................................................................. 125














LIST OF FIGURES

Figure page

1-1. Internet hosts across world regions ...................................................................... 12

2-1. Internet timeline....................................................................................................... 21

2-2. Total number of Internet hosts............................................................................... 22

3-1. Internet hosts across income regions ...................................................................... 53

4-1. Graphic model ................................................................................ ...................... 95

5-1. Distribution of Internet users across countries ...................................................... 114














Abstract of Dissertation Presented to the Graduate School
of the University of Florida in Partial Fulfillment of the
Requirements for the Degree of Doctor of Philosophy

INTERNET ADOPTION IN POST-COMMUNIST COUNTRIES:
A PROPOSED MODEL FOR THE STUDY OF INTERNET DIFFUSION

By

DANIELA V. DIMITROVA

May 2003

Chair: Dr. Sylvia Chan-Olmsted
Major Department: Mass Communication

This dissertation proposed and tested a five-dimensional theoretical framework to

explain the variations in Internet use across the post-communist countries. The

framework included economic, political climate and policy, technology/infrastructure,

cultural, and audience factors. Three factors emerged as critically important: economic,

political, and infrastructure factors. Cultural factors seemed to have partial impact. These

findings suggest that the traditional country-level indicators of economic wealth and

technological infrastructure remain important determinants of Internet use in the

countries of Eastern Europe and the former Soviet Union. The most significant

determinant, however, was level of democratization.

The results of the multiple regression analysis reported in this study indicate that

democratization, teledensity, and GNP per capital were the three most important factors

positively related to Internet use in the post-communist countries. Being predominantly

Muslim had a negative effect on Internet use while being Western Christian (Protestant or








Catholic) seemed unrelated to Internet adoption. Neither length of telecommunications

privatization nor education level appeared significant in this analysis.

Thus, the results of this study shed light on the macro-level indicators that affect

Internet adoption in the post-communist countries. These have important implications for

policy makers at the local, national, and international level. The proposed Internet

diffusion model may be applicable to other regions, but this analysis focused only on the

28 post-communist countries.













CHAPTER 1
INTRODUCTION

Human history has witnessed the rise and fall of many new technologies. The

Internet is often described as the most revolutionary new technology ever and its growth

in every country around the globe is remarkable as well as irreversible. The Internet is not

just a technological innovation; it is a unique, fascinating, multifaceted network that

transcends national boundaries. It affects people, communities, organizations, and

countries around the world. In this dissertation, Internet adoption is examined in a unique

region of the world--the post-communist countries.' The dissertation proposes a five-

dimensional analytical framework to account for differences in Internet diffusion in those

countries. Testing the five-dimensional framework identifies the main determinants of

Internet adoption and illustrates how these determinants affect Internet use in the post-

communist countries.

Internet Significance

The Internet constitutes "at once a world-wide broadcasting capability, a

mechanism for information dissemination, and a medium for collaboration and

interaction between individuals and their computers without regard for geographical

location" (Leiner et al., 1997). The Internet has affected society in a variety of ways as a

SThe post-communist countries are defined as the countries of Eastern Europe, the
former Soviet Union, and Mongolia. Specifically, the study examines Albania, Armenia,
Azerbaijan, Belarus, Bosnia and Herzegovina, Bulgaria, Croatia, Czech Republic,
Estonia, Georgia, Hungary, Kazakhstan, Kyrgyzstan, Latvia, Lithuania, Macedonia
(FYROM), Moldova, Mongolia, Poland, Romania, Russia, Slovak Republic, Slovenia,
Tajikistan, Turkmenistan, Ukraine, Uzbekistan, and Yugoslavia (Serbia and
Montenegro).








result of its multidimensional functions (Castells, 1996; ITU, 1999; Newhagen & Rafaeli,

1996; OECD, 1998b). One of the most fascinating aspects of Internet diffusion is its

impact on a global scale. The Internet has exercised a tremendous impact on the

economic, political, technological, and social development of countries (IMF, 2000a;

Mitchell, 1995; World Bank, 2001). The positive contributions of Internet adoption in

each of these four areas are reviewed below.

Economic Contributions

One of the more compelling arguments made to encourage global Internet

diffusion is that countries (developing countries in particular) can improve their

economic status with the adoption of this technology (Hanson & Narula, 1990). Clearly,

the Internet affects the economic situation in a country as it facilitates international trade,

lowers production and distribution costs, optimizes productivity within and between

companies, and offers leapfrogging possibilities for less developed countries.

The Internet facilitates international trade and thus allows nations to increase

exports and imports of goods to and from other countries (The new economy, 2000). It

allows better integration of national markets both internally and

externally/internationally, and also increases possibilities for economic decentralization

(Maddock, 1997). With the improvement of Internet security, e-commerce is expected to

increase and more national exports and imports will be likely (DePrince & Ford, 1999).

In addition, the Internet lowers production and distribution costs (DePrince &

Ford, 1999; Guthrie & Austin, 1996; The new economy, 2000). These lower costs can

have a positive effect on the internal economic situation. The Internet intensifies price

competition among producers, which leads to lower prices for consumers (Guthrie &








Austin, 1996). Labor productivity is increased, and searching, distribution, and

transaction costs tend to drop (DePrince & Ford, 1999).

It has been argued that the Internet optimizes productivity within and between

companies (Maddock, 1997; Malecki, 1997, 2000). The development of a better

telecommunications infrastructure in general, Maddock (1997) argues, increases

productivity and competitiveness of local companies. In addition, telecommunications

development facilitates economic growth by increasing market efficiency (Maddock,

1997). Finally, better telecommunications can improve management within corporations

(Daly & Miller, 1998; Maddock, 1997).

Another economic impact of higher Internet penetration is the leapfrogging effect.

Leapfrogging is the ability of countries that are technologically behind suddenly to skip

generations of intermediate technology and adopt the latest one. The adoption of the

latest technology is seen as beneficial to countries as they can succeed in catching up

economically with more technologically advanced societies (Singh, 1999).

Political Contributions

In addition to the economic benefits, the Internet can serve as a tool for enhancing

democratic governance worldwide. A number of scholars have discussed how the Internet

can affect the political situation within a country (Ahmann, 1998; Godwin, 1998; Poster,

1995). From the early days of the ARPANET (Advanced Research Projects Agency

Network), people envisioned the Internet's expansion to a worldwide, borderless network

(Rogerson & Thomas, 1998). This global network can strengthen democracy in at least

two ways: first, people can stay better informed and thus can make better choices;

second, the Internet offers citizens a global forum for free expression and exchange of

ideas (Perrit, 1999; Poster, 1995, 2001).








The Internet provides citizens in any country with the opportunity to stay better

informed and thus learn more about options for political action and democratic

governance. The information available online is rich and is difficult to censor. The

sources of information are also numerous, ranging from established media corporations to

independent journalists to regular citizens publishing online. People can find an

enormous amount of information on any topic that interests them. Better informed

citizens, arguably, can make better decisions in society and more informed political

choices.

Another way in which the Internet can strengthen democracy on a global level is

by offering citizens a forum for free expression and exchange of ideas with like-minded

people. In most countries, people are free to go online and express their views to a global

audience. They can also search for and communicate with like-minded people around the

globe. Such online communication and uncensored expression reaches a large number of

people and extends individual freedom. It also allows citizens to organize collective

action and thus influence public policy.

It is important to note that control of the Internet by one government or corporation

is unlikely. Even though regulation can limit the use of the Internet to some degree, it is

quite difficult to enforce such regulation on a global scale.

Technological Contributions

Furthermore, the Internet brings technological growth to a country as it can

strengthen its overall telecommunications development. Maddock (1997) argues that

telecommunication causes development progress in several ways. First, it leads to the

creation of at least one leading sector of the economy in the country. Second, it

accelerates diffusion of other technologies and thus allows faster catch-up for less








developed countries. In today's day and age, it is hardly questionable that the Internet is

critical for the technological advancement of a nation and has become an indispensable

part of the modem telecommunications infrastructure.

Social Contributions

The Internet also brings about social change. With the advent of the Internet, we

may be coming closer to what Marshall McLuhan conceived as "the global village"

(McLuhan & Powers, 1989). This is another reason why it is important to research

Internet diffusion. The emergence of a global community is facilitated by the Internet.

People from all nationalities and various backgrounds can form communities online.

Boundaries and distances between countries shrink in the virtual world. Thus, the Internet

(through email, chats, and bulletin boards) brings people closer, regardless of geographic

location. These online applications redefine social relationships within countries. The

effect of virtual communities can increase since email remains one of the most popular

Internet activities.

Winner (1997) discusses the idea that technological innovations lead to social,

cultural, and political transformation. He argues that "technical innovations of any

substantial extent involve a reweaving of the fabric of society, a reshaping of some of the

roles, rules, and relationships that comprise our ways of living together." New

technologies, then, should be studied closely and not only at one point in time. Their

effect on the relationships in society should also be examined and their long-term impact

followed, if we are to understand adequately the whole diffusion process and its

consequences.








Other Contributions

In addition to the benefits noted above, the global expansion of the Internet is

beneficial to countries in the areas of education and health (ITU, 1999; World Bank,

2001). The Internet as an unlimited and readily accessible information resource can be

useful for data retrieval on a global level (Sadowsky, 1993). It can also facilitate better

service delivery and learning through distance education (World Bank, 2001).

Finally, intellectual curiosity makes it a worthwhile effort to study the expansion of

the global network of networks. Press has put it well (1997):

Tracking the diffusion of the Internet is a daunting task because it is growing
rapidly, is global, and expands organically, at the edges and internally, without
central control. Still, business people, policy makers, and capacity planners are
better off with approximate data than none at all.... Over the years, busy humanity
has covered the globe with cities linked by railroads, highways, telephone lines,
power grids, canals, and so forth, and we are now weaving digital communication
links--the nervous system. I suspect that curiosity and aesthetics motivate the
people tracking the global diffusion of the Internet as much as profit.

In this dissertation, the challenging task of tracking and explaining Internet

adoption in a unique region of the world is pursued. The study examines Internet

adoption in the countries of Eastern Europe and the former Soviet Union and analyzes the

multivariate relationships to explain their levels of adoption. The dissertation proposes a

five-dimensional conceptual framework to account for the differences in Internet

diffusion in the post-communist countries. The study draws on research from the United

States, Western Europe, and Latin America as well as cross-country Internet diffusion

literature. It proposes and tests a comprehensive five-dimensional theoretical model.

Based on the results, a refined conceptual framework is retrieved. Discussion shows how

that refined model can be employed in predicting and modifying future Internet adoption

at the country level. The rest of this chapter briefly describes the post-communist








countries and then outlines the significance of region-specific research on Internet

diffusion.

Post-communist Countries

The post-communist countries examined in this research include the former Soviet

Union republics, Eastern Europe, and Mongolia. Specifically, they include the following

28 nations: Albania, Armenia, Azerbaijan, Belarus, Bosnia and Herzegovina, Bulgaria,

Croatia, Czech Republic, Estonia, Georgia, Hungary, Kazakhstan, Kyrgyzstan, Latvia,

Lithuania, Macedonia (FYROM), Moldova, Mongolia, Poland, Romania, Russia, Slovak

Republic, Slovenia, Tajikistan, Turkmenistan, Ukraine, Uzbekistan, and Yugoslavia

(Serbia and Montenegro). These countries represent a unique region of the world. Since

the end of the Cold War they have been undergoing a transition from totalitarian regimes

to democratic societies. A Freedom House report titled Nations in Transit examines the

transition in the region, which is characterized by trends toward building civil society and

market economy (Karatnycky et al., 1997). The report shows that the post-communist

countries can be divided into three distinct groups, based on progress in these two areas

(Karatnycky et al., 1997). The members of the three groups are listed below.

Transition Progress

The first group includes the leaders in the transition process: Poland, the Czech

Republic, Hungary, Slovenia, Estonia, Latvia and Lithuania. These countries are

classified by the Freedom House based on their 1996 survey as "liberal democracies, or

polities that are well on their way to democracy, with vibrant civil societies, well-

established rule of law, and market economies" (Karatnycky et al., 1997, 17). These six

nations, no doubt, have made considerable progress and are leaders in the transition

process in the region.








The next group of post-communist countries was classified as the intermediary

group. It consists of countries that have made some progress towards the goal of building

strong democratic societies, but the transition has not been as quick or smooth as in the

leading countries noted above. Albania, Armenia, Bulgaria, Croatia, Georgia,

Kyrgyzstan, Macedonia (FYROM), Moldova, Romania, Russia, the Slovak Republic, and

Ukraine are members of the intermediary group. Bosnia and Herzegovina and Yugoslavia

(Serbia and Montenegro) are also members of this group. There is considerable variation

across these countries, both in terms of political development and economic progress.

The third group among the post-communist countries consists of those that have

been slow to change, relative to the rest of the transition societies--Azerbaijan, Belarus,

Kazakhstan, Tajikistan, Turkmenistan, and Uzbekistan. The Freedom House report posits

that the first and the third group are more stable while the middle group is less stable as

countries belonging to that group are more fluid and can transition to the next levels

rather quickly (Karatnycky et al., 1997). However, the three groups are distinctly

different from each other and are likely to remain different over time. In other words, the

distinctive features of the three groups of transitional societies are stable. An interesting

observation is that the countries in the three groups are clustered together geographically.

Also, "the intermediate countries deserve particular attention, as their variable legacies

and half-hearted reforms do not imply any clear-cut outcomes" (Karatnycky et al., 1997,

20).

Another grouping of the countries in the region is given by the United Nations

Development Programme (UNDP, 1999), which uses six regional groupings in its Human








Development Report for Central and Eastern Europe and the Commonwealth of

Independent States (CIS), based primarily on geographic location.

Geographic Regions

The post-communist countries can be divided into 6 regions based on their

geographic location: Central Europe, Eastern Europe, Caucasus, Baltic states, Western

Former Soviet Union, and Central Asia.

Probably the most advanced group of countries is located in Central Europe. This

group includes the following states: the Czech Republic, Hungary, Poland, the Slovak

Republic, and Slovenia. The second geographic group is Eastern Europe. The Eastern

European countries are Bulgaria, Croatia, Macedonia (FYROM), Slovenia, Romania, and

Yugoslavia (Serbia and Montenegro). The Caucasus region includes Armenia,

Azerbaijan, and Georgia. All of these counties are former Soviet republics. The Baltic

states have also made considerable strides in the post-Cold War transition. These states

include Estonia, Latvia, and Lithuania. The Western FSU (Former Soviet Union)

incorporates the following states: Belarus, Moldova, Russia, and Ukraine. Finally,

Central Asia includes the republics of Kazakhstan, Kyrgyzstan, Tajikistan, Turkmenistan

and Uzbekistan.

Economic Inequalities

Using national income as a criterion, the post-communist countries can be divided

into four groups, according to the 2000 World Development Report of the World Bank,

which is based on 1998 data. The four groups are low income (less than $760 GNP per

capital lower middle income ($761-$3,030), upper middle income ($3,031-$9,360), and

high income ($9,361 or more).








The low income countries in the region are Albania, Armenia, Azerbaijan, Bosnia

and Herzegovina, Kyrgyzstan, Moldova, Mongolia, Tajikistan and Turkmenistan. The

next category--lower middle income--includes the majority of the countries: Belarus,

Bulgaria, Georgia, Kazakhstan, Latvia, Lithuania, Macedonia (FYROM), Romania,

Russia, Ukraine, Uzbekistan, and Yugoslavia (Serbia and Montenegro). Upper middle

income states are Croatia, the Czech Republic, Estonia, Hungary, Poland, and the Slovak

Republic. The only high income country in the region is Slovenia (World Bank, 2000).

In conclusion, the post-communist countries have made different progress in the

post-Cold War transitional period (de Melo & Gelb, 1996). Variations both in political

and economic development exist (EBRD, 1997).

Need for Research of Internet Diffusion

Understanding the process of Internet adoption at the county level is, first and

foremost, critical for formulating public policy. National policies can contribute to

accelerated Internet adoption, which can be beneficial to the country. As noted earlier, the

Internet can contribute to national development in several ways. Internet adoption has a

positive economic impact overall. The utility of the Internet as a political tool, which

allows people to stay better informed and participate more fully in the political processes,

has also been discussed. Country-specific research on Internet diffusion can also be used

to enhance the technological development of the country, as outlined above. Finally, the

Internet has important social functions, as it allows individuals to create online

communities and interact with people around the globe, regardless of geographic

boundaries. The Internet deeply impacts societies. Therefore, it is critical to better

understand the process of its adoption. This will enable policy makers to exploit the

Internet's full capabilities (Maherzi, 1997; Sadowsky, 1993; World Bank, 2001).








The dissertation focuses on the aggregate level of Internet adoption. Various

studies in multiple disciplines have examined the topic of Internet diffusion at the

individual level. Most research has been conducted in the industrialized nations. Research

on Internet adoption and diffusion in the United States in particular has been quite

extensive (Atkin et al., 1998; GVU, 1998; Lin, 1999; Lindstrom, 1997; NTIA, 1995,

1998, 1999; Pew, 1995; USIC, 2000) and the number of studies looking at Internet

adoption and usage keeps growing.

The focus of Internet studies in general has been primarily on the United States

(Daly & Miller, 1998). Literature exists also on Internet adoption by other industrialized

nations, such as The Group of Eight (G-8) nations (Canada, France, Germany, Italy,

Japan, Russia, United Kingdom, and United States) and OECD member countries

(Australia, Austria, Belgium, Canada, Czech Republic, Denmark, Finland, France,

Germany, Greece, Hungary, Iceland, Ireland, Italy, Japan, Korea, Luxembourg, Mcx i,.

Netherlands, New Zealand, Norway, Poland, Portugal, Spain, Sweden, Switzerland,

Turkey, United Kingdom, and United States) (Hargittai, 1999; McElhinney, 2001). Yet

few studies have examined the process of Internet adoption in other countries.

As the birthplace of the global information superhighway, the United States

remains one of the countries with the highest Internet penetration (ITU, 1999; Pitkow,

1996; USCD, 1998; USIC, 2000). Other developed countries (notably Scandinavian

nations) are also leaders in Internet adoption. Gunarante (2001) identified three "global

centers" where information technology is concentrated: NAFTA center, EU center, and

Asian-Pacific center. Countries that do not belong to any of those centers are considered

on the periphery of the Information Society (Gunarante, 2001).






12



The global distribution of Internet hosts shows that more than 88 percent of the


hosts in 1999 were located in North America and Europe (ITU, 1999). The members of


the European Union clearly have higher Internet penetration than the rest of the world. As


Figure 1 illustrates, South Asia, North Africa, the Middle East, and sub-Saharan Africa


exhibit lower levels of Internet adoption (ITU, 1999; World Bank, 2000). The countries

where extensive Internet research exists tend to have higher Internet penetration. Figure


1-1 shows the unequal distribution of Internet hosts in different regions of the world.


Internet Hosts by Region



.60

i 20



.00


so


40

20
!:0






South Asia MOte East & North SLb-Sahrwan Africa East Asia & Pacific Latlin Amnica & Eurqw A Crnt" Asia Euopaw Urnon
Africa Carfbbean

Figure 1-1. Internet hosts across world regions. Source: World Bank, 2000.

The obvious discrepancy between the industrialized countries and the rest of the


world makes it not only interesting but also critical to study the determinants of Internet

diffusion. It is very important to examine whether and how the "global information

highway" is adopted by other countries, especially considering the possibility that the

Internet not only bridges, but also widens the gap between rich and poor countries (Tele-








haves, 1996; WIPO, 2001). Furthermore, cross-cultural studies allow for identifying

regional differences in the adoption of information technologies.

Studies of Internet adoption at the country level will not only provide insights about

the process of Internet diffusion across countries but also show whether this process

varies by certain country-level characteristics. Our understanding of Internet diffusion in

non-Western countries is still very limited. As shown above, differences in levels of

Internet penetration between industrialized countries and the rest of the world are quite

significant. These differences cannot be fully explained by the existing literature. This

dissertation extends current literature by offering insights on Internet trends in the post-

communist countries.

Better understanding of how new technologies are adopted by post-communist

countries can help development in those countries. Even though the direct causal

relationship between Internet usage and development/economic growth has been debated,

studies have shown consistently a strong positive correlation between telecommunication

services and country-level economic indicators such as per capital income (Arnum &

Conti, 1998; Elie, 1998; Hargittai, 1999; Singh, 1999). The process of Internet adoption

remains not fully understood. It has become clear that per capital income plays an

important role, but few studies have examined what other factors affect Internet adoption

at the macro/societal level. This study adds to current literature as it proposes a more

comprehensive model of Internet diffusion.

This dissertation focuses on Internet adoption in the former Soviet bloc. The post-

communist countries are of particular interest for several reasons. First, they present a

unique case study: countries that were subjected to communist rule for 40 to 70 years








give researchers a chance to follow the transition of telecommunications in post-

communist societies (Katchanovski, 2000). As Rose (2002, 33) notes, "Internet access is

especially important in the transition countries, because the transition process is about

opening up a country to the world."

The post-communist countries share at least 40 years of Soviet influence, which

makes them a different cluster for research. They share certain objective characteristics,

such as high literacy rates and high educational levels (UNDP, 1999). At the same time,

they differ in some cultural aspects, such as religious beliefs and historical experience

(Katchanovski, 2000). The focus on one particular region of the world allows researchers

to detect more intricate relationships among variables and gain insights about the

magnitude of importance of country-level characteristics.

The post-communist countries present the opportunity for a case study of the

Internet adoption process among a group of relatively similar countries. It is interesting to

examine whether and how countries that had relatively similar technological, political,

and economic levels have reached significant differences in the area of new information

and communications technologies, such as the Internet. The post-communist countries

can either follow the models of Internet adoption of other countries--the industrialized

countries, for instance--or exhibit a different path of Internet adoption due to their unique

socio-economic development. The results of the study advance knowledge of different

patterns of global Internet diffusion.

Further research on Internet adoption in the region is needed because it has been

identified as the next area where an Internet boom will be seen (Arnum & Conti, 1998;








ITU, 1999; USIC, 2000). This upward trend makes research on Internet adoption in the

post-communist countries even more timely and important.

Table 1-1. Internet Hosts per 10,000 population in 1995 and 1999.


Source: World Bank, 2000.

Internet use in the post-communist countries has increased exponentially over the

past decade (1TU, 1999; Magyar & Karvalics, 2001). Table 1-1 illustrates the growth of

Internet usage in the post-communist countries by showing the increase in the number of

Internet hosts. From 1995 to 1999, that number has doubled at the least. In the case of


COUNTRY NAME Hosts in 1995 Hosts in 1999 Increase (%)
Albania 0.11 0.24 118
Armenia 0.46 1.85 302
Azerbaijan 0.02 0.23 1,050
Belarus 0.02 0.79 3,850
Bosnia and Herzegovina 0 1.38 N/A
Bulgaria 1.26 11.9 844
Croatia 5.27 25.94 392
Czech Republic 21.16 85.59 304
Estonia 24.11 174.66 624
Georgia 0.11 1.59 1,345
Hungary 15.44 93.13 503
Kazakhstan 0.12 1.47 1,350
Kyrgyz Republic 0 4.03 N/A
Latvia 5.25 50.83 868
Lithuania 1.23 30.45 2,376
Macedonia (FYR) 0.46 4.4 857
Moldova 0.01 2.42 241
Mongolia 0 0.05 N/A
Poland 5.98 40.9 584
Romania 0.77 9.01 1,070
Russian Federation 1.48 13.09 784
Slovak Republic 5.61 38.79 591
Slovenia 28.22 99.12 251
Tajikistan 0 0.24 N/A
Turkmenistan 0 0.56 N/A
Ukraine 0.47 4.56 870
Uzbekistan 0.02 0.05 150
Yugoslavia (Serbia & Montenegro) N/A 7.65 N/A








Belarus, for example, Internet hosts increased by 3,850 percent. Lithuania, for example,

had only 1.23 hosts per 10,000 in 1995, but the number increased 2,376 percent to 30.45

hosts per 10,000 in 1999. Bulgaria had a similar number of hosts in 1995--1.26 per

10,000--but the increase in 1999 was relatively small compared with Lithuania--to 11.9

hosts only. These examples illustrate that the number of Internet hosts per capital in post-

communist countries remains uneven and the growth rate across countries varies widely.

Among the Central and Eastern European nations, Slovenia, the Czech Republic,

Slovakia, Hungary, and Poland have higher Internet penetration than the rest of Eastern

Europe. Among all post-communist countries, Slovenia and Estonia seem to exhibit

higher rates of Internet adoption (CDT, 2000; ITU, 1999; World Bank, 2000). These

variations in Internet penetration among countries with relatively similar socio-economic

developments in the post-Cold War years suggest that there are multiple factors that

affect Internet adoption on a country-level basis. The main contribution of this

dissertation is to identify a group of variables that constitute the most important

predictors of Internet diffusion in this particular region of the world.

Research Method

The dissertation employs aggregate data to determine the multivariate relationships

between Internet adoption and a number of explanatory variables.2 These variables fall

into five categories: economic, political, technological, cultural, and audience factors.

The study design reflects the theoretical framework discussed in the literature review

chapter. The dissertation employs t-test, multiple regression, and Tobit analysis to


2 The study is limited by data availability. It relies on the latest data published by various international
organizations. Data paucity accounts, in part, for why Internet adoption in the post-communist countries
has not been well researched so far.








determine the statistical significance of a set of explanatory variables. A more detailed

explanation of the methods is provided in Chapter 4 of the dissertation.

Dissertation Outline

After discussing the need for research in Chapter 1, the dissertation continues to a

more detailed explanation of the significance of the Internet for the political and

economic growth of society in Chapter 2. Chapter 2 also offers a brief historical overview

of the major events that led to today's Internet. Next, Chapter 3 reviews relevant

literature and explains how it is related to the present study. Chapter 3 also describes the

comprehensive five-dimensional theoretical model proposed and tested in the

dissertation. Chapter 4 explains the methods used and describes the study design, data

collection, operational definitions, and scales of measurement. The statistical results are

analyzed next in Chapter 5. The discussion of the results follows in Chapter 6. Chapter 7

summarizes the entire dissertation. It also addresses broader implications and limitations

of the study. Suggestions for future research and theoretical and practical consequences

also are offered.













CHAPTER 2
INTERNET AND SOCIETY

The Internet's contributions to society are manifold. The Internet is especially

important for the political and economic development of nations. The first section of this

chapter presents an overview of Internet development and growth from the 1960s until

today. A timeline including Internet milestones is provided. After outlining briefly the

history of the Internet, the chapter describes the importance of the Internet for society as

it relates to two major issues: the political process and economic development.

Development of the Internet

Even though the concepts underlying today's Internet were created in the late

1960s, the Internet diffusion on a global level occurred only in the 1990s. Several key

developments that led to the current state of the Internet are presented below.

The Invention of the Internet

The Internet was created in the 1960s as a result of close collaboration within the

American research community (Hafner & Lyon, 1996). Tracing the history of today's

Internet, it is important to note that four significant aspects of the network were

considered from the start: technological, management, social, and commercial (Leiner et

al., 1997).

The first documented idea of an Internet was discussed in internal memos by J. C.

R. Licklider at the Massachusetts Institute of Technology (MIT). Licklider described his

idea of a "galactic network" in these memos in 1962 (Leiner et al., 1997). Other

developments such as the first work on packet switching theory took place during the








early 1960s as well (Hafner & Lyon, 1996). The Advanced Research Projects Agency

(ARPA), a research and development organization funded by the U.S. Department of

Defense, began operating in 1967.

ARPA was instrumental in the development of the early Internet. ARPA tested data

transfer across telephone circuits using packet-switching and thus became the first agency

to implement a network based on that technology (Leiner et al., 1997). This network was

named Advanced Research Projects Agency Network--or ARPANET--and became the

forerunner of the Internet (Hafner & Lyon, 1996).

Robert Taylor at ARPA found funding to test this so-called "network experiment"

beginning with a few nodes (Hafner & Lyon, 1996). The first two computers linked on

the ARPANET were at the Network Measurement Center at the University of California

at Loss Angeles (UCLA) and the Stanford Research Institute (SRI) at Stanford

University. The exchange of the first host-to-host message took place on that network in

1969. Soon after that, two more nodes were added: the University of California at Santa

Barbara (UCSB) and the University of Utah. Thus, four host computers were connected

by the end of 1969 into the initial ARPANET (Leiner et al., 1997). These four nodes

were the first realization of the idea of the "galactic network." Today it is common to

refer to the 1969 ARPANET as the earliest existing Internet (Hafner & Lyon, 1996).

From the beginning, the Internet was conceived as a general infrastructure that

would connect multiple independent networks and support numerous and new

applications. It is considered an open-architecture network--a network of interconnected,

independent computers. The structure of the Internet was "foretold" by Paul Baran, an

engineer at the RAND corporation (Hafner & Lyon, 1996). He created the idea of a








distributed network, a digital switching technology to connect computers at various

locations. Baran also came up with the idea to break down the message into small pieces

(packets) that will travel independently over a network and then reconnect before arriving

at their final destination. This is still how messages are sent on the Internet.

A major step toward developing today's Internet was the creation of TCP/IP

(Transmission Control Protocol/Internet Protocol). This protocol meets the needs of an

open-architecture network environment. It was compiled in 1972 by Robert Kahn at

DARPA and Vinton Cerf at Stanford University (Leiner et al., 1997). Basically, the

TCP/IP protocol allows information bits to travel to destinations independently. The

Internet Protocol (IP) is responsible for addressing and forwarding of individual packets

while the Transmission Control Protocol (TCP) is responsible for service features such as

flow control and recovery from lost packets.

It is important to note that the researchers at ARPA, its contractors, and several

universities collaborated closely to create, test, and improve the Internet invention

(Hafner & Lyon, 1996; Leiner et al., 1997). In the post-Sputnik era, money for research

from the U.S. government became abundant. As Hafner and Lyon (1996,23) note,

science was "the New Frontier." The initial collaboration between the academic research

community and ARPA, an agency within the Defense Department, led to the successful

implementation of the ARPANET (Hafner & Lyon, 1996). Therefore, the Internet

represents a good example of "the benefits of sustained investment and commitment to

research" (Leiner et al., 1997). A number of people contributed to the development and

improvement of the initial Internet, but the original research and implementation

happened mostly under ARPA's funding umbrella in the 1960s (Hafner & Lyon, 1996).








Below, some milestones in Internet development are shown.

1962--Primary idea of galactic network

1967--ARPANET development begins

1969--First four host computers connected over the ARPANET

1972--TCP/IP implemented

1972--First public demonstration of ARPANET

1972--First email application created at BBN

1973--First international connections to ARPANET created in England and Norway

1974--First use of the term "Internet" in a conference paper by Cerf and Kahn

1978--Trials for a private system, Telset, begin in Finland

1983--Domain Name System developed at the University of Wisconsin

1986--NSFNET replaces the ARPANET

1989--World Wide Web invented

1993--Mosaic, the first Web browser for personal computers is created

Figure 2-1. Internet timeline.

Internet Growth and Global Expansion

The previous section shows that initially the Internet was nothing more than a

network to used internally within a particular agency. Access to that network was limited

to a handful of people and information about it was sparse. The first public demonstration

of the network happened only in 1972. Even at that time, however, people envisioned its

expansion to a worldwide, borderless network (Rogerson & Thomas, 1998). This was not

yet technically possible though. The Web browser--the graphical interface of the World

Wide Web--was created in 1993. The first graphical browser Mosaic was the precursor of

Netscape and later Internet Explorer. It encouraged faster diffusion of the Internet around









the world (Winston, 1998). Figure 2-2 shows the growth of Internet hosts over the years

on a global scale.


InerMet hosts wide
100.000.000 :: ." !. ..... .. :".:,: :!." : "; :":;,i "'..


90.000.00























Figure 2-2. Total number of Internet hosts. Source: Internet Software Consortium, 2000.

Clearly, the use of the Internet increased dramatically after the free distribution of

the Web browser. The World Wide Web was developed by Tim Berners-Lee at CERN in

Switzerland. The World Wide Web (WWW) uses HTML (hypertext markup language),

which incorporates text and graphical elements as well as hyperlinks. The introduction of

the World Wide Web made it easy for non-technical persons to use the computer

network. As the inventor of the World Wide Web acknowledged, "transferring

information was too much of a hassle for a non-computer expert" before that (Berners-

Lee, 1999, 18). Berners-Lee' s goal was not only to make it easier to use the Internet, but
70.000.000


50.000.000

60.000.000

30.000.000



20.000.000

10000.000

0




Figure 2-2. Total number of Internet hosts. Source: Internet Software Consortium, 2000.

Clearly, the use of the Internet increased dramatically after the free distribution of

the Web browser. The World Wide Web was developed by Tim Berners-Lee at CERN in

Switzerland. The World Wide Web (WWW) uses HTML (hypertext markup language),

which incorporates text and graphical elements as well as hyperlinks. The introduction of

the World Wide Web made it easy for non-technical persons to use the computer

network. As the inventor of the World Wide Web acknowledged, "transferring

information was too much of a hassle for a non-computer expert" before that (Berners-

Lee, 1999, 18). Berners-Lee's goal was not only to make it easier to use the Internet, but








also to create a system in which different computers with different software could

connect and "talk" to each other and thus enable researchers to share their work quickly

and easily. Berners-Lee's first formal proposal for funding was submitted in March 1989

at CERN, but received no feedback. Another proposal followed with the same result. As

Berners-Lee wrote (1999, 27), "explaining the vision of the Web to people was

exceedingly difficult."

Finally, the World Wide Web was released in 1993. Like the Internet on which it

runs, the Web has no central location as the online information is distributed: i.e.,

documents are stored on many computers all over the world. The Internet has no main

node, so it has an infinite storage capacity as a result.

The global growth of the Internet has been impressive and often labeled

"revolutionary" and "phenomenal." In fact, it has been argued that the Internet is the

fastest growing communications technology ever (WIPO, 2001). In 1990, only 22

countries were connected to the Internet, compared to 226 countries in 1999. The number

of countries connected to the global network increased tenfold in less than 10 years. As of

September 2002, there are 605.60 million online users worldwide (Nua, 2002).

Even though the global expansion of the Internet has been accelerating, disparities

between regions and countries do exist. The United States and North Western Europe

have the lion's share of the Internet (ITU, 2000). The Internet is expected to become less

U.S.-centric though. Forecasts show that Internet growth in the United States will level

off by 2002, and most continuing growth will be observed in Western Europe and

developed Asia (Bieler & Stevenson, 1998).








In the Asia-Pacific region, Australia, Japan, and New Zealand are clearly the

leaders in Internet adoption. Hong Kong, Singapore, South Korea, Taiwan, and China

also exemplify fast Internet growth rates (USIC, 2000). The rest of the region and South

Asian countries in particular lag behind in Internet usage. Japan is expected to continue

dominating the Asian Internet market (Bieler & Stevenson, 1998).

In Europe, there are disparities in Internet penetration across East-West and North-

South lines. Internet penetration rates in Sweden, Norway, Denmark, and Finland

surpassed 35 percent in 1999 (USIC, 2000). Italy, France, and Spain had relatively lower

Internet use compared with the Northern European and Scandinavian nations. With the

exception of Slovenia, the countries of Eastern Europe are further behind. Analysts

forecast, however, that Eastern Europe and the former Soviet Union are likely to exhibit

high Internet growth rates (Bieler & Stevenson, 1998; ITU, 1999).

Projections show that together with Eastern Europe, Latin America will be one of

the regions to experience substantial increase in Internet usage (USIC, 2000). Internet

adoption in Latin America and the Caribbean is growing steadily. Brazil, for instance, has

one of the fastest growing ICT markets in the world (World Bank, 2001). Mexico and

Argentina, in addition to Brazil, are leaders in Internet usage in the Latin American

region.

In Africa, Internet growth rates have been relatively low. According to 2000 data,

there were 1.5 million Internet users in Africa (USIC, 2000). About 1 million of those--or

two-thirds of all Internet users, however, were located in South Africa (USIC, 2000). In

the summer of 2000, more than 300 million people worldwide were using the Internet

regularly (USIC, 2000). Yet only 0.6 percent of the people living in developing countries








had access to the Internet (USIC, 2000). As a recent report from the Center for

Technology and Democracy (2000) notes, Internet disparities bring a danger of dividing

the countries in the world into "information rich" and "information poor."

The Internet is constantly evolving and expanding. It is hard to control the Web,

both in terms of access and content, unlike other media (Perrit, 1999). Regulation has

been formulated within different countries, including China, Singapore, and Turkey, to

try to limit freedom of expression and censor the Internet (Cortez, 2000). Legislation to

restrict Internet in some way (by censoring online information, licensing Internet

providers, etc.) has been proposed in Australia, Chile, Great Britain, and South Africa

(Cortez, 2000). In China, for example, cyber caf6s must obtain a license from the state

and ISPs are required to "register their customers with the authorities" (Cortez, 2000). In

addition, Web sites containing subversive information are blocked. However, it is

generally hard to implement Internet regulation due to the global and changing nature of

the network (Perrit, 1999).

The World Wide Web and the Internet as a whole offer unique opportunities for

nations, both in terms of political and economic development. These opportunities are

discussed next.

Internet and Political Development

A number of studies have discussed the potential of the Internet to enhance

democratic governance. Ahmann (1998), for instance, looked at how the Internet can

increase political participation in South Africa. She found that political information

online is abundant and that the Internet can easily be used for political education within a

country (Ahmann, 1998).








The Internet, then, can strengthen the democratic process by serving as a vehicle

for political education of citizens. This is achieved not only by keeping the citizens better

informed (with access to various sources and media online), but also by providing a

public forum for communication and exchange of information with other like-minded

people. Thus the Internet can serve as a channel for mediated interpersonal

communication and community formation.

Interestingly, in the early 1960s J.C.R. Licklider, one of the key figures in the

invention of the Internet, conceived it as a network that would, indeed, allow citizens to

participate in the political process more actively. He envisioned people on the global

network attending a "giant teleconference" (Hafner & Lyon, 1996, 34).

Perrit (1999) discusses the role the Internet can play in strengthening both national

and global governance. He sees the potential of the Internet in four specific areas, all of

which lead to strengthening international cooperation. Perrit (1999) argues that the

Internet can strengthen international law and can also empower and improve local non-

governmental organizations (NGOs). The Internet has the potential to support the

international security system. Finally, the Internet can strengthen the economic

interdependence between countries (Perrit, 1999).

Democracy and the Internet

Many scholars at different times in history have tried to define what democracy

means. There is no single clear-cut definition that encompasses all characteristics of

democracy. The meaning of democracy varies with time and place. The 2000 political

crisis in Yugoslavia shows the significance of one aspect of a democratic society--free

and fair elections. When the Serbian people realized that Slobodan Milosevic was trying








to manipulate election results, they took to the streets because the mandate of their vote

was not acknowledged.

In addition to free elections, people in a democracy require freedom of expression.

This is also supported by a Serbian example, which speaks to the fact that the nature of

the Internet makes it hard to control. Slobodan Milosevic tried to censor print and

broadcast media during the 1999 Kosovo crisis. Milosevic's government also tried to

suppress media freedom by shutting down those media that supported government

opposition. After being closed down, a popular opposition radio station--Radio B92--used

the Internet to "broadcast" to the outside world. Thus, the Serbian opposition was able to

distribute news and information that was censored by other media. This clearly speaks to

the democratic potential of the Internet. During the Serbian crisis, this new medium

provided one of the few channels for pro-democratic groups in the country to speak to the

outside world while other domestic media were strictly censored by the Serbian

government. As Perrit (1999) notes, "the decentralized nature of the Internet itself...

makes it very difficult for.., governments to control and censure political thought,

speech, and action."

An attempted legislation in the United States also clearly shows the value of a free

Internet. The proposed Communication Decency Act, which was not accepted by the U.S.

Congress, shows that freedom of expression is highly valued (Cortez, 2000). The Reno

vs. ACLU lawsuit exemplifies the value of freedom of expression embedded in the

American constitution. As Cortez (2000) notes, the following international treaties also

recognize freedom of expression as a basic human right: the Universal Declaration of

Human Rights of 1948, the Pact of Civil and Political Rights of 1966, and the Pact of








Economic, Social, and Cultural Rights of 1966. By extension, all countries that are

signatories of these international treaties have to harmonize their national legislation with

the provisions of the treaties (Cortez, 2000).

The Internet has served as a vehicle for communication for anti-government groups

worldwide. In China, Lin Hai was given a two-year sentence for sending email addresses

to an anti-government publication (Cortez, 2000). The Internet provides an outlet both for

reaching other anti-government activists directly and for publishing relevant information.

In the case of Malaysia, the Internet allowed the political opposition that was living on a

remote island to use email to organize anti-government action.

Diversity of opinions is critical for a well-functioning democracy. The more voices

are expressed in a public forum, the better. The value of having more information

available from more sources than before, expressed in a public forum, can hardly be

disputed--it makes democracy stronger (Held, 1995).

The Internet certainly makes it easier to get more information from more sources

than ever before and provides a unique opportunity to communicate online, despite

geographic distances. Perrit (1999) says: "The ease with which people can participate in

cyberspace activities enabled the Internet to grow exponentially with virtually no

governmental oversight. This growth has created a cyber-culture that celebrates freedom

and distrusts traditional political institutions trying to come to grips with the implications

of this profound electronic revolution in information technology."

Poster (2001) discussed Habermas's idea of the public sphere--a "space" where

citizens deliberate and interact to form public opinion--as it relates to the Internet.

Jakubowicz says that the "public sphere is a forum of public debate where citizens can








debate issues of common concern, voice and act on their views and seek to arrive at a

consensus on matters of general interest" (Jakubowicz, 1998, 12). Gaynor (1996) argues

that it is difficult to see if the Internet enhances or fragments the public sphere in a

democracy. Because it offers citizens a venue for expressing public concerns, it does,

indeed, serve as a part of the public sphere. Thus, the Internet enables individuals to

influence public policy through the pressure of public opinion.

Sen (1999a, 10) argues that a democracy requires "the guaranteeing of free

discussion and uncensored distribution of news and fair comment." The importance of a

free press and informed citizenry is discussed next.

Free Press and the Internet

The Internet affects media organizations around the world. The structure of the

Internet makes national boundaries irrelevant to the distribution of media messages. The

Internet also allows people to speak publicly and publish information, just like the

traditional press in the past. Online media, however, reach wider, global audiences

(Perrit, 1999). Thus, citizens can access various sources and free media over the Internet.

Today we seem to take for granted that a free press is a vital part of any democratic

society (Jakubowicz, 1998). But what specific functions do the media perform in a true

democracy? According to McChesney (1999), the press has a responsibility to perform a

public service. A free press, he adds, should encourage diversity of opinions. A

democratic society presupposes pluralism, i.e. the expression of different opinions. Under

Communism, people living in the so-called Soviet-bloc countries not only couldn't

express their opinions freely, but they even felt the pressure to say "the right thing," even

if it wasn't what they believed (Yakovlev, 1989). The state prevented the existence of a

free press by enforcing strict censorship and also having financial control of all media.








The Communist Party also jammed foreign media that broadcast within the Soviet bloc to

prevent diverse viewpoints from reaching the average citizen. The official press was

simply a mouthpiece of the communist government.

In a democratic society, however, the press should not be a mouthpiece of the

ruling party. On the contrary--it should hold the government accountable for its actions.

The press is said to have a watchdog function--to hold the government accountable for its

actions. The media in a democracy should serve the public by ensuring that the

government is not abusing its powers. A free press in a democratic society is a place

where deliberation should happen, according to Nader (Nader, 1998). The press, he

argues, should enliven public debate and engage people into it. Such lively press

functions as part of the so-called public sphere. The public sphere, as mentioned above,

enables individuals to give their input through public debate, which is necessary for a

healthy democracy. If the Internet acts as a space for public debate, then it can empower

citizens globally.

Another important basic function of a free press is to keep citizens informed. It has

been argued that citizens on a global level can stay better informed through the Internet.

Thus, citizens can participate better in the democratic process in any country (Sen,

1999b). Sen says that "guaranteeing of open discussion, debate, criticism, and dissent, are

central to the process of generating informed and considered choices" (Sen, 1999a, 9).

This is even more important to people in the post-communist countries who, as

mentioned above, were not allowed to openly state their opinions and engage in free

discussion prior to 1989.








Traditionally, the media have served as gatekeepers in society. They filtered the

information and chose which facts were newsworthy. The media thus used to serve an

important agenda-setting function: they told the public what issues were important. It has

been argued that the gatekeeper role and the agenda-setting role of the traditional press

can be manipulated by governments. The Internet may remove the possibility for such

direct controls. Internet news are not easy to control, as the gatekeeping and the agenda-

setting role can be assumed by the average person.

The Internet transcends national boundaries and withstands governmental controls.

The Internet also allows people to speak publicly and publish information, just like the

traditional press in the past by reaching wider, global audiences (Perrit, 1999). Thus, both

functions are enhanced: (1) citizens can stay better informed (with access to various

sources and free media over the Internet) and (2) citizens can use the Internet as an

avenue for communication and debate in a public forum. This suggests the potential of

the Internet to affect the political process both nationally and internationally, and to shift

the practice of democracy to more active citizenry.

In addition to political development, the Internet also affects economic

development worldwide. The rest of the chapter outlines the most important economic

impacts at the national level.

Internet and Economic Development

There are at least four aspects of the Internet that directly affect developing

countries. First, the Internet has enabled cheaper production and distribution of goods.

Second, the emerging Internet economy has played an important role in reforming

traditional economic structures within countries. Third, the Internet has expanded and

strengthened global markets by enabling more exports and imports between countries.








Finally, it has been argued that the Internet has "leapfrogging" potential for less

developed countries.

Lower Production and Distribution Costs

The 20th century has witnessed a tremendous growth of technology. One of the

important effects that technology innovations have brought about is the reduced cost of

production (Christensen, 1997; Sadowsky, 1993; The new economy, 2000). Not

everybody agrees that reduced production costs or optimized efficiency is generally good

for society, but still the cost of information exchange today is much lower compared to

the time when computers first started (The new economy, 2000). This is true for other

services as well.

Sadowsky (1993) discusses several ways in which communication technology

affects economic development in society. He contends that the transportation industry as

well as the finance sector would be very different without the use of high-speed

communication and computing technology. Decrease in the price of microelectronics,

satellite technology, fiber optics, and packet-switching, Sadowsky (1993) argues, have in

turn accelerated the adoption of modem computing.

Information technology (IT) has been a major factor in the increased production of

goods and services by U.S. workers (Barua et al., 1999). IT has also made these workers

more efficient. Of the 2.6 percent increase in U.S. labor productivity between 1996 and

1999, more than half was directly related to the information technology sector (USIC,

2000).

The Internet intensifies price competition among producers and their suppliers, and

thus leads to lower prices for consumers as well (DePrince & Ford, 1999; Guthrie &

Austin, 1996). Guthrie and Austin (1996) contend that product quality is improved as a








result. DePrince & Ford (1999) argue that labor productivity is increased by Internet

marketing while searching and transaction costs tend to drop. They predict that "as the I-

ECON's share of the total economy rises, the magnitude of the Internet's macroeconomic

impact will also rise" (DePrince & Ford, 1999).

The Internet Economy

The economic impact of the emerging Internet economy is also impressive.

DePrince & Ford (1999) note that the Internet economy has been affecting the following

areas: hardware, software, intermediaries (such as travel and auction companies), and e-

commerce. All these sectors have been transformed, directly or indirectly, by the advent

of the Internet (McKnight & Bailey, 1997).

DePrince & Ford (1999) note that there is a shift from traditional distribution

methods to Internet distribution of specific products and services. They distinguish

between two types of Internet distribution: "Amazonic" and "Dellphic." The former

refers to ordering products online from a company, such as Amazon.com, that maintains

a warehouse of its products. Such transactions can be either public or private, individual

or wholesale. The second distribution method, named after Dell computers, is the

ordering of a product before it has been manufactured. Users make an order; then the

producer creates the product or service and ships it to the consumer/buyer. In this case,

the customer usually responds to promotional efforts by the producer. Both of these

distribution channels have become popular and are affecting the overall economic

structure within and between countries.

The Internet has been seen as a driver of economic boom. The Internet economy

workforce in the United States grew 36 percent from 1998 to 1999 (Barua et al., 1999).

According to the U.S. Commerce Department, out of a 5 percent improvement in U.S.








production of goods and services in 1999, 1.6 percent has been attributed to information

technology (IT) use (Barua et al., 1999). Labor productivity in the United States

increased by roughly 3 percent a year from 1995 to 2001; faster growth was observed in

IT-using industries (Baily, 2001). In other words, studies have shown that IT improves or

at least contributes to economic productivity.

The Internet facilitates electronic transactions. Even though electronic commerce is

not a new phenomenon in itself, the speed of growth has been accelerated by the Internet

(Atkinson & Court, 1998; Dryden, 1998; WIPO, 2001). Online commerce (e-commerce)

is expected to comprise 4.4 percent of the U.S. Gross Domestic Product (GDP) by 2002

(WIPO, 2001). Its growth globally has also been impressive (World Bank, 2001; WIPO,

2001).

As Baily (2001) notes, "new technologies are altering the way traditional industries

operate." The Internet has also strongly affected the following areas: financial services,

travel agents, stock trading, computer sales, music CDs, software, and book sales. Some

other types of businesses are likely to be affected by the growing Internet economy as

well. E-bay is one example where the role of the intermediary is eliminated. Other

intermediaries such as stock brokers may disappear as well.

Of course, as DePrince and Ford (1999) point out, not all products and services will

be affected by the Internet economy. They also note that the Internet has a tremendous

impact not only on the micro, but also on the macroeconomic level, as it promotes

improved macroeconomic performance (DePrince & Ford, 1999).

Global Markets

The Dellphic and Amazonic distribution channels described above also work in a

global setting. Business-to-business transactions and international trade are facilitated by








the Internet. DePrince and Ford (1999) conclude that "the emergence of the Internet

economy... may well rival the introduction of printing, steam power, the telephone, and

the assembly line as a growth-enhancing innovation."

Electronic communications facilitate international commerce (Bauer, 1994). The

Internet introduces new mechanisms for imports, exports, and trade in general (World

Bank, 2000, 2001). As a global channel, it makes the actual transactions easier and faster.

One type of product that illustrates well the ease of online transactions is information. It

is very easy to buy, sell, or transfer data over the Internet. Information transactions

exhibit economies of scale. The more copies of a data set, for instance, are sold, the

higher the profit margins. Producing an additional copy of the same data set is virtually at

no cost.

Leapfrogging

The argument exists that developing countries can "leapfrog" as they adopt new

technologies and thus surpass developed countries. Basically, leapfrogging is the ability

of countries that are technologically behind suddenly to skip generations of intermediate

technology and adopt the latest one. This is seen as economically beneficial to countries

(Singh, 1999). For example, a nation with very low telephone penetration may adopt the

latest technology for mobile phones and thus jump ahead of other states. Such technology

is likely to be cheaper, more efficient, and easier to build. Government policy in

developing countries has been identified as the main barrier to leapfrogging (The new

economy, 2000).

The term leapfrogging has been used in the literature in two other ways, in addition

to skipping an intermediate technological stage. Singh (1999) argues that the term

"leapfrogging development" has been used to imply that developing countries can skip








stages of development as a results of telecommunications and thus become members of

the postindustrial society. The third way in which leapfrogging has been used is to mean

that telecommunications can itself lead to accelerated development in such countries

(Singh, 1999). Even though this doesn't happen automatically, the possibility exists at

least that adopting latest information and communications technologies (ICTs) and

sophisticated Internet infrastructure will lead to positive economic impact within

countries.

Finally, the tremendous impact of the Internet needs to be put into perspective. All

the possible positive changes will not happen automatically (IMF, 2000b; World Bank,

2001). Sale (1999) discusses the negative effects of large displacement of human labor by

the introduction of more sophisticated industrial technologies, such as the Internet.

Solomon (1998) warns us about the possibility of the Internet becoming an electronic

mall. Winner (1997) raises questions about the concentration of wealth and power

"around" new technologies such as the Internet. Another potential drawback of Internet

use is that the Internet allows dominant ideology transfer and consumer life-styles to

other countries. The Internet can also widen the gap between developing and developed

countries. That is one reason for concerns about the uneven Internet diffusion on a global

level. Despite these potential setbacks, it was argued above that the Internet opens doors

to improving democratic governance and economic development of nations worldwide.













CHAPTER 3
LITERATURE REVIEW

This chapter first discusses the diffusion of innovations theory. It provides an

overview of its generalizations and establishes how these generalizations apply to the

Internet. Several different issues that help in understanding Internet adoption from a

diffusion of innovations perspective are identified. Next, the chapter reviews the body of

literature on new media technologies adoption and use. The chapter concludes by

identifying what major factors affect Internet adoption at the country level. A

comprehensive five-dimensional analytical framework is proposed. Finally, potential

interactions between diffusion of innovations and new media technologies research are

discussed.

Diffusion of Innovations

One way to study the Internet is by using traditional diffusion studies. This is not

an easy task, however. Classification of the Internet as an innovation is difficult because

of its very complex nature. In addition, the diffusion process at the societal level is not

fully understood. Rogers (1995, 5) defined the diffusion of an innovation as "the process

by which an innovation is communicated through certain channels over time among the

members of a social system." An innovation can be an idea, product, value or a new

technology. Diffusion of innovations typology is applied below to one of the fastest

growing new technologies--the Internet.








Basic Generalizations

Diffusion of innovations is one of the most popular social science theories and it

has been used in variety of academic disciplines (e.g., anthropology, sociology,

communications, marketing, geography, education and health). It started in the early

1900s with the writings of Gabriel Tarde, a French philosopher, who described many of

the components of adoption and diffusion in his work The Laws of Imitation (Tarde,

1903). The first systematic diffusion study, however, was conducted at the University of

Iowa in 1943. In their seminal work, Ryan and Gross (1943) examined the adoption of

hybrid seed corn by Iowa farmers. Diffusion research has grown considerably since then.

Diffusion of innovations offers a linear model for the diffusion process, mostly

focusing on the individual level of adoption (Rogers, 1995). It posits that innovations are

typically diffused after going through the following stages: (1) knowledge, (2)

persuasion, (3) decision, (4) implementation (the actual adoption of the innovation), and

(5) confirmation stage. The first two stages in this process resemble a communication

model in which a sender has to get a message across to a receiver. The mass media are

very important at the knowledge stage (but not as important at the persuasion stage) to

get the information out that a new product or technology exists to fulfill a particular need

(Rogers, 1995).'

Diffusion of innovations posits that innovations in general follow an S-curve of

adoption over time. In other words, the first stages of adoption are slower, then we have a

faster increase in the number of adopters (resulting in a steeper slope of the adoption



'At the knowledge level of adoption, we can distinguish three different levels of knowledge: awareness
knowledge, how-to knowledge, and principles knowledge.








curve), and finally the curve levels off at the later stages. Empirical data for various

technology adoptions support the S-curve typology (Severin & Tankard, 1997).

Technology Innovation Attributes

Everett Rogers, one of the most influential diffusion scholars (Severin & Tankard,

1997), identified five attributes that play a role in whether a particular innovation is

adopted or rejected (Rogers, 1995). They are: (1) relative advantage; (2) compatibility;

(3) complexity; (4) trialability; and (5) observability of the new idea, product or

technology. Rogers later added reinvention as the sixth additional attribute. Reinvention

refers to cases where an existing technology is used for a different purpose than originally

conceived. For example, if we first thought that the computer was supposed to be used

for word-processing, we reinvented its use when we started sending e-cards. Rogers

(1995) contends that 48 to 87 percent of the variability of adoption is explained by the

perceived attributes of an innovation.

The first attribute--relative advantage--refers to the question whether the

innovation is better than what one used before. The perceived relative advantage of the

Internet, at least at first, will be largely dependent on the marketing and promotion efforts

put into mass media campaigns. Compatibility is whether the innovation is compatible

with previous technologies. The next attribute, complexity, refers to the question how

difficult it is to use the innovation. If it is more complex, people will be less likely to use

the innovation. Trialability is whether a person can try out the innovation. Finally,

observability is whether the results of the innovation are readily observable. Clearly there

are extraneous factors "outside" of the individual that will affect these attributes.








Interactive Innovations

Interactive innovations are innovations that depend on the number of people who

have already adopted a particular innovation (Mahler & Rogers, 1999). In other words,

the value of the innovation--its relative advantage in the mind of the potential adopter--

increases if there is a large number of people who are already using that innovation. In

the case of the Internet, people may be more likely to adopt it if they have the ability to

be connected to more people who are using the Internet already. A good example to

clarify this point is email--if your friends have email already, then you can communicate

with them over the Internet. The perceived value of the technology increases as a result.

Several technological innovations have been labeled interactive in nature.

Previous research, however, has not clearly distinguished between interactive and non-

interactive innovations (Mahler & Rogers, 1999). The classic example of the fax machine

shows that if only very few people are using the innovation, its value is relatively low.

Once there is a large number of others that use the fax machine, its diffusion increases

very fast.

Mahler and Rogers (1999) examine the diffusion of interactive communication

innovations (several telecommunications services) and their adoption by German banks.

They argue that the rate of adoption of such interactive innovations follows a modified S-

curve (Mahler & Rogers, 1999). The adoption process of interactive innovations such as

the Internet begins with a slower rate of adoption, but then has a more "pronounced"

critical mass effect; once the critical mass is reached, the innovation takes off more

rapidly than projected by the traditional S-curve (Rogers, 1995; Mahler & Rogers, 1999;








Garrison, 2000). In other words, the adoption of interactive innovations follows a

modified S-curve.

The importance of the (perceived) number of other adopters of the interactive

technology decreases over time. Today fax machines and telephones are so widespread

(at least in the United States) that potential adopters don't have to consider the interactive

nature of these communication technologies. As Mahler and Rogers (1999, 720) point out

about telephone adoption today, "the utility of adopting depends almost entirely on

factors internal to the individual, rather than on such externalities as the perceived

proportion of others with whom the individual wishes to communicate by telephone."

The Internet in the United States has probably reached that point. If we study Internet

adoption in a developing country, however, network externalities are likely to affect the

Internet diffusion process (Maherzi, 1997).

Network externalities are often cited as attributes of information goods and

services. Basically, network externalities add value to a certain product or service with

the increase in the number of its users. Shapiro and Varian (1999) discuss in economic

terms how information goods have higher network externalities and thus are more

valuable to both the user and the provider. In the case of the Internet-the so-called global

network of networks, externalities stemming from the number of others who have already

adopted it should be highly visible. As the Internet becomes more and more prevalent,

and especially after a critical mass is reached, the significance of the total number of

users will fade away.

Network externalities can be direct or indirect. As Mahler and Rogers (1999) note,

there were indirect network externalities in the case of the VCR diffusion. Two different








standards were developed--Beta and VHS; tapes dubbed in one of these standards

couldn't be played on the other. Yet the VCR standard that was adopted was VHS, even

though it was the technologically-inferior one (this was largely due to better marketing

efforts on the part of VHS). In the VCR case, critical mass had to be reached for each of

the two standards (Mahler & Rogers, 1999). This example is applicable to Internet

adoption, and especially to the adoption of specific Internet software. The diffusion of

online chat programs such as ICQ will depend largely on the ICQ company's efforts to

make their program the standard in online chatting.

Cluster Innovations

One way to study the Internet using traditional diffusion studies is by positioning

it as an interactive innovation. Another approach is to examine it as a cluster innovation.

Prescott and Slyke (1997) argue that the Internet can be best understood as a cluster

innovation because of its many components. Clearly, classification of the Internet as an

innovation is hard because of its very complex nature. As Prescott and Slyke (1997)

suggested, a good way to understand the Internet may be by positioning it as a technology

cluster innovation--i.e., not as one single technology, but as several technologies working

with one another. The Internet has many components, many of which are related to or

dependent on each other. If people adopt email technology, they are more likely to adopt

Instant Messenger, for example. They will not be able to do this, however, unless they

have the Internet Explorer browser installed already.

If we see the Internet as a cluster innovation (several technologies working

together), we see that it has many relative advantages, depending on which purpose you

use it for. The Internet is not compatible with anything that existed prior to it, its

networked structure and way of condensing space and time have been unprecedented.








The only other technological innovation in history that had such dramatic effect was

probably the telegraph--"shrinking the world faster and further than ever before"

(Standage, 1999, vii).

Both cluster innovations and interactive innovations will have different degrees of

complexity, trialability and observability. The Internet today may be easier to try out

compared to five years ago. Any American can go to the public library or to a friend's

house, for example, and try using the Internet or any of its components and/or services.

Its results are also readily observable. In general, that should contribute to a faster rate of

Internet adoption.

When we talk about the diffusion of an innovation, we basically examine behavior

change over time. In this case, we are interested in how many people have adopted the

new technology within a country. Thus we are interested in measuring the number of

adopters who have reached the implementation stage in the adoption process. It will be

useful to review next what type of adopter categories exist in diffusion literature.

Types of Adopters

There are five basic adopter categories described in diffusion of innovations

studies on the basis of how fast a member of the social system adopts a new idea, product

or technology. They are: (1) innovators, (2) early adopters, (3) early majority, (4) late

majority, and (5) laggards (Rogers, 1995). Diffusion of innovations posits that innovators

are venturesome, cosmopolite, with higher income and technical knowledge (Rogers,

1986; Rogers, 1995). The innovators account for 2.5 percent of the total population that

in the end adopts the innovation. Typically, the early adopters are about 13.5 percent, the

early majority and the late majority groups are 34 percent of the population each, and the








laggards account for 16 percent (Rogers, 1995). This reflects the S-curve adoption

process and follows from the normal distribution of the total number of new technology

adopters.

Using Rogers' normal distribution curve of innovators, early adopters, early

majority, late majority, and laggards, it is easy to predict in which category future

Internet adopters will fall. This is a useful technique when examining adoption at the

national level.

Internet User Profile

An increasing number of research studies have been conducted in the United

States to discover the "profile" of Internet users. A number of user studies conducted by

the Georgia Tech GVU lab in the past years show that most Internet users in the United

States are male, well educated, and upper income (GVU, 1999). in a study of American

students Stewart et al. (1998) conclude that, in general, men are more willing to adopt a

new technology than women. Interestingly, they also suggest that whites are more willing

to adopt than other cultural groups in the United States.

Lindstrom (1997) finds similar characteristics for North American Internet users:

they are mostly male, upper class and well educated. Lindstrom's survey looks at users in

the United States and in Canada during two time periods. The second survey shows that

the typical user has changed and that the user base has broadened (Lindstrom, 1997). The

typical Internet user in the United States has changed. More women and older people

have joined the online community. In fact, more recent statistics show that the majority of

American Internet users are women (Nielsen NetRatings, 2000). This remained true in

2002 (Nielsen NetRatings, 2002).








What is the Internet user profile in other countries? Research on Internet use in

Chile, for example, shows some similarities: Internet users in the city of Santiago

resemble closely early American users (Mendoza & Alvarez de Toledo, 1997). The

typical Chilean Internet user can be characterized as young, male, and highly educated.

The study also reveals that Chilean users tend to have higher income level and to connect

to the Internet from work or from educational institutions (Mendoza & Alvarez de

Toledo, 1997).

One of the few studies on Internet users in Eastern Europe shows a similar

typology (Dimitrova, 2002). Dimitrova's survey of Bulgarian Internet users finds that the

majority are highly educated and male (Dimitrova, 2002). Her questionnaire does not

include income level questions. Similarities in user characteristics are also found in Asian

countries. The typical Internet user in China, for instance, is also more educated, young,

and mostly male (Jisi et al., 2001). In addition to the United States, Canada is the only

other country where the number of female Internet users has surpassed that of male users

(Nielsen NetRatings, 2002).

Many studies have tried to explain why some people have adopted the Internet

while others have not (Goode & Stevens, 2000). Atkin, Jeffres, and Neuendorf (1998)

examine what differences exist between Internet adopters and non-adopters, and whether

those individual characteristics can be used to predict the potential users of Internet

technology. Atkin, Jeffres, and Neuendorf (1998) draw from several theoretical

frameworks. They see the computer as one of the most discontinuous innovations ever.

They include media usage variables when looking at what characteristics differentiate

early Internet adopters from late adopters.








Atkin, Jeffres, and Neuendorf (1998) examine the demographic characteristics of

the Internet adopters and non-adopters to test the diffusion of innovations paradigm. As

suggested in the diffusion typology, they find that Internet users tend to be better-off and

better educated than the population at large. Atkin, Jeffres, and Neuendorf (1998) also

find that prior use of and interest in technology is a good predictor of Internet adoption,

which also fits with Rogers's technologically-knowledgeable innovator profile. Internet

adopters are also found to be more cosmopolite than non-adopters (Atkin et. al, 1998).

Many studies support Rogers' generalization that early Internet adopters are better

educated and upscale (Atkin et. al, 1998; Lin, 1998). Interestingly, several studies suggest

that individual demographic factors are statistically more significant in predicting Internet

adoption than attitudinal or communication needs factors (Atkin et. al, 1998). Media

usage is not an important predictor of computer and Internet adoption (Atkin et. al, 1998;

GVU, 1998; ITU, 1999; Lin, 1998). Demographic segmentation then can be used by

diffusion agencies to target specific adopter groups in the diffusion of new technologies,

especially in the early stages of adoption. Demographic characteristics also should be

used as predictors when studying Internet adoption by countries with lower Internet

penetration levels.

Other Communication Technologies

Garrison (2000) looks at the diffusion of online research tools in American

newsrooms. These tools represent a particular aspect of the Internet and its diffusion to a

particular group of users--American journalists. Garrison (2000) concludes that

computers are already largely adopted as a newsgathering method and that the "value of

interactive Internet information-gathering tools" has increased over time.








The rate of adoption (the number of people who adopt an innovation over a

specified period of time) varies greatly between different technological innovations. The

adoption of Nintendo games in the United States, for example, and the VCR was very

fast (Rogers, 1986). Computers, however, have exhibited a slower rate of adoption. Weir

(1999) examines the adoption of electronic newspapers and finds that it is different from

that of other consumer products. Weir (1999) agues that this may be due to the fact that

electronic newspapers are more like media than like software applications.

We cannot observe Internet diffusion unless there are personal computers adopted

in the first place. As Lin (1998) indicates, PC's adoption rate in the United States has

been relatively slow. She also finds that communication technology ownership is the

strongest predictor of computer adoption rate (Lin, 1998). Lin argues that demographic

predictors are still important to forecast computer adoption rates, but that is no longer the

case for the VCR and cable television. This suggests that communication technologies'

adoption and diffusion changes over time, both in terms of speed and type of adopter.

This, in fact, supports Rogers's model, in which it is expected that innovators and early

adopters may be demographically different than the later adopter groups. Among the

laggards, early majority, and late majority there are no major demographic distinctions.

Therefore, the strength of demographic predictors decreases over time.

Prescott and Slyke (1997) argue that (1) the Internet is a complex technology

cluster and (2) its adoption is context-specific. The researchers ask the following

questions regarding Internet adoption at the organizational level: Is the Internet radical

versus incremental innovation, product versus process innovation, voluntary versus

involuntary adoption, and pull versus push technology. Internet adoption will have








different dimensions in different contexts. For example, when a company adopts new

software that does not change significantly the way business is conducted (just changes

the application from text-based to windows-based software, for instance), this is an

example of an incremental change (Prescott & Slyke, 1997). On the other hand, if the

company introduces a Web-based software that allows customers for the first time to

place orders online, we have a radical shift from previous organizational practices

(Prescott & Slyke, 1997). The type of Internet adoption is contextual then--on a case by

case basis, Internet adoption can fall into one or the other category.

Levels of Internet Adoption

Not only is Internet adoption contextual, but it can also be divided into three

different levels: individual, organizational, and societal. Most research to date has

focused on either individual or organizational adoption. As Rogers (1995) says, however,

we can also study adoption at the societal level.

One of the few studies that applies diffusion of innovations to the societal level

conducted by Bazar and Boalch (1997) supports the traditional diffusion of innovations

typology. They argue that Internet diffusion in developing countries is achieved when a

critical mass is reached and the adoption becomes self-sustaining (Bazar & Boalch,

1997). The main institutions that play a role in the Internet adoption process within a

country, according to Bazar and Boalch (1997), are the government, the carriers, funding

institutions, and the information technology (IT) professional associations. Others have

also found that national governments affect significantly the Internet diffusion process

(Lin, 1993).

There are three different ways of approaching Internet adoption in terms of which

level of adoption we are looking at. These levels, again, are the individual,








organizational, and societal level. With a global innovation such as the Internet, however,

we need more insights about the societal level of adoption. At this level, different factors

affect the rate of adoption, and diffusion of innovations, while useful, is not sufficient to

explain country-level technology diffusion. A major limitation of the diffusion of

innovations typology is the fact that it has been applied mainly to the individual and

organizational levels. This dissertation contributes to knowledge on diffusion of

innovations at the societal level.

Other Considerations for Internet Adoption

Few studies on Internet adoption make a clear distinction between the software and

hardware parts of the Internet, a distinction that Rogers (1995) considers important for

any technology. Such distinction may reveal different patterns of adoption. In addition,

we need to consider which aspect of the Internet is being examined (e.g., email) when we

look at the adoption of the Internet from a diffusion of innovations perspective. Such

delimitations are important yet difficult to make.

Internet adoption is also subject to whether it is voluntary or not for the individual

adopter. As Rogers (1995) points out, there are authority or contingent decisions that

apply to certain adoption situations. The diffusion process is different in cases of optional

or collective adoption decisions. In this study, we assume that Internet users in the post-

communist world have made a voluntary decision to use the Internet.

Wolcott et al. (2001) incorporate national systems of innovation (NSI) literature in

their discussion of Internet diffusion theory. This body of research underscores the

importance of national institutions for the diffusion of innovations within countries. NSI

studies often include Research and Development (R&D) expenditure as a factor affecting

the successful adoption of the innovation as well as other measures of training and








education (Nelson, 1993). Typically, countries with higher income levels have higher

R&D expenditure so including both variables as determinants of Internet usage rates

could be redundant.

A better conceptualization of the Internet itself is needed before we can fully

understand its adoption at either the individual, organizational, or societal level. Some see

the Internet as a technological innovation. Others describe it as a cluster of technologies.

Some see the Internet as a culture (Wilson et al., 1996). Yet others talk about the Internet

as a place (Poster, 1995). Many portray the Internet as a strategic national infrastructure

(Madon, 2000). Others have discussed its potential to enhance democratic governance

and improve socio-economic development of developing countries in particular

(Maherzi, 1997).

The Internet is very complex in nature and is still evolving. Therefore, further

research on Internet diffusion and adoption is needed. The diffusion of innovations

typology is useful overall, but cannot fully explain the adoption at the country level. This

dissertation also draws on new media technologies literature, which is summarized in the

next section.

New Media Technologies Research

Diffusion of innovations basically postulates that the diffusion process occurs in

stages over time. A main assumption of that theoretical paradigm is that (1) the diffusion

process is linear and (2) different groups adopt innovations at different points in time.

The width of adoption that can describe how widespread a technology is within a country

is largely based on individual factors. Thus, audience variables are critical for explaining

levels of Internet adoption. In particular, demographic factors such as personal income,








and educational level, and attitudinal factors such as cosmopoliteness and innovativeness

have been identified as important in the diffusion of innovations model.

According to diffusion of innovations, external factors are also important for

Internet adoption in developing countries. These include government policies and the

existence of prior technologies. Multiple technology components are critical in the case

of the Internet, as the above discussion of interactive and cluster innovations shows.

Therefore, government policies and political environment as well as technological

infrastructure can be used as predictors for Internet adoption.

The nature of interactive communication technologies and the Internet in particular

requires us to draw from a multidisciplinary theoretical framework to explain variations

in adoption (Lin, 1998). Several basic sets of factors have emerged in the growing body

of new media technologies literature as predictors of country level Internet adoption.

These are economic factors, political climate and policy factors, technology and

infrastructure, audience characteristics, and cultural factors. This study proposes a

conceptual framework including the afore mentioned five areas to explain Internet

adoption at the societal level.

While certain prerequisites exist that affect adoption of new technologies, it is a

difficult task to pinpoint exactly what drives Internet diffusion into different countries.

Most studies to date have shown that the country's economic development plays an

important role. The next section reviews literature on Internet adoption and economic

development.

Economic Factors

The argument exists that innovations are borne as a result of scientific discoveries.

Some scholars have argued against this proposition, however, saying that the rate of









technological progress does not stem directly from basic scientific discovering (Romer,

1999). Rather, "it is the incentives created by the market that profoundly affect the pace

and direction of economic progress" (Romer, 1999). Logically, then, technology growth

is faster when these incentives are stronger. Many scholars have argued that business

incentives and potential markets determine whether a new technology is introduced or not

in the first place (Romer, 1999; Sale, 1999). Malecki (2001), for example, contends that

commercialization has been the main catalyst for the development and growth of Internet

technology.

The most evident predictor of Internet penetration in a country is probably the level

of economic development (Arnum & Conti, 1998; Bazar & Boalch, 1997; Elie, 1998;

Hargittai, 1999; Wolcott et al., 2001). The country's economic situation has a direct

effect on Internet adoption. Studies have consistently detected a strong positive

correlation between the level of economic development and Internet use in a country

(Arnum & Conti, 1998; Clarke, 2001; Elie, 1998; Gunarante, 2001; Hargittai, 1999;

Kiiski and Pohjola, 2001). Using World Bank data and classification, Figure 3 shows the

uneven distribution of Internet hosts across countries with different income levels.

In addition to empirical data, previous research also shows that countries that are

better off economically tend to have higher Internet penetration. Bazar and Boalch (1997)

contend that capital (economic resources) are crucial for adoption of the Internet in

developing countries. Richer countries in general have more resources to put into the

service sector of their economies, which includes the information technologies (IT) sector

(Elie, 1998). Previous research has also supported the assumption that richer countries






53


have more telecommunications networks and higher media penetration overall (Maherzi,

1997).


Internet Hosts by Income Regions





6Rim
6'00 '-- ------"---"'"-----"-------"----------"---""----"---"-----





49W~~~,. .. --., . :,a ..: ....








Low ieome Lower -rdfte icome Upper middle income H.igh iome: r nOECD Hi. "come: OECD


Figure 3-1. Internet hosts across income regions. Source: World Bank, 2000.

Bazar and Boalch (1997) examine Internet diffusion within developing countries'

context. They define five categories that can be seen as prerequisites for Internet adoption

in developing countries: national/organizational needs and opportunities in place (this

concept is related to the nation's vision of the future and relative advantage of the

country); technology (including infrastructure and Internet technology itself); necessary

skills and people to introduce the innovation; capital (economic resources); and finally

good management of the technology adoption and diffusion process. Again, they contend

that economic resources are critical for Internet adoption at the societal level (Bazar &

Boalch, 1997).

One of the few studies on Internet growth in the post-communist countries focuses

on Internet use in enterprises within the countries (Clarke, 2001). Thus, the unit of








analysis is the individual enterprise and the dependent variable in the econometric model

is whether or not an enterprise has access to the Internet. The main question that the study

addresses is how enterprise ownership and foreign competition affect Internet access in

the region. The sample includes 2,999 enterprises from Eastern Europe and Central Asia

and uses the WBES database of the World Bank (Clarke, 2001). The main conclusion of

the study is that foreign ownership of enterprises positively affects Internet growth. In

addition, the results suggest that enterprises in smaller countries with higher income

levels and larger urban populations are more likely to be connected to the Internet

(Clarke, 2001).

Most studies of cross-country Internet adoption to date show that national income

level is an important determinant. Elie (1998) and Hargittai (1999) find a strong

correlation between Internet penetration in a country and per capital income. Hargittai

(1999) examines how four country-level indicators affect Internet connectivity among

OECD members. She includes the economic situation of the country (measured by GDP

per capital) as well as education level, legal environment (regarding communication

technologies) as well as infrastructure to explain differences in Internet connectivity. The

GDP per capital is the strongest predictor in her model: it explains 38 percent of the

variation. Rodriguez and Wilson (2000) also use GDP per capital as a predictor of ICTs

use, as measured by and Index of Technological Progress (ITP). They find a strong

positive correlation between ITP and GNP PPP, also arguing that richer countries make

more technological progress over time than poorer countries.

Clearly, GDP or other macroeconomic indicators can be used as predictors of

Internet adoption in a country. This is also a logical variable since it translates individual








income, which has been identified as important in the diffusion of innovations paradigm,

to the country level.

Kiiski and Pohjola (2001) look at cross-country diffusion of the Internet using the

Gompertz model of technology diffusion. Thus, their model is longitudinal and their

dependent variable is the rate of change in the number of Internet hosts from 1995 to

2000. Their sample includes 23 OECD countries, similarly to Hargittai (1999). Their

study concludes that the best predictors for adoption are GDP per capital and Internet

access cost.

Some researchers, however, find no relationship between national income and

Internet penetration. Surprisingly, the parameter for income per capital is statistically

insignificant in a recent study at the World Bank (Dasgupta et al., 2001). Thus, the

researchers conclude that economic development does not have a strong influence on

Internet intensity. They extend this conclusion by noting that the disparity in Internet use

is just a reflection of the "long-standing disparity in telecommunications access" between

developed and developing countries (Dasgupta et al., 2001, 6). One possible explanation

for this finding is that income and teledensity (telephone penetration per capital) are

highly correlated and when one of them is included, the other does not appear to have an

effect. However, there is no information on the bivariate correlations among the

predictors given in the study.

Another economic variable that is clearly related to Internet use is price of Internet

access. Petrazzini and Guerrero (2000) argue that there is an inverse relationship between

price of Internet connection and Internet use. They find that once the price of leased lines

and of tariffs for local calls in Argentina has been reduced, Internet growth increases








dramatically. Higher Internet prices are generally indicative of more restrictive

telecommunications policies. They also present a barrier to Internet use of lower income

demographic groups. However, the price of Internet access in the post-communist

countries is not available; neither is any other synchronized country-level data on

governmental policies regarding Internet access.

In addition to price of Internet connection and basic macroeconomic indicators, the

size of the service sector of the economy has also been found an important factor for IT

diffusion (Elie, 1998). The size of the service sector of the economy, however, is

typically related to national income. Countries with higher per capital income tend to have

bigger service sectors (World Bank, 2000).

When comparing some Western European and some Eastern European countries,

Elie (1998) finds that Internet penetration differs from what would be expected only on

the basis of macroeconomic indicators, however. Economically highly developed

countries of Southern and Central Europe (such as France, Germany, Italy, and Spain)

have lower Internet usage levels than predicted on the basis of their GDP levels (Forrester

Research, 2000). On the contrary, the Internet seems more "developed" in the

economically less advanced Eastern European countries of Slovenia, Czech Republic,

Hungary, Slovakia, and Poland.

Arnum and Conti (1998) note a similar discrepancy. When calculating Internet

ratio2 per country, they show that France and Estonia are very close to each other in their

Internet penetration. Similarly, Estonia and Slovenia were ranked higher than Hong


2 Instead of using the conventional measures of Internet hosts or Internet users per 10,000 people, Arnum
and Conti measured Internet penetration per country as what they called an Internet ratio. The Internet ratio
formula used in their study is: (Internet Hosts + Domains + Web Pages)/ Population.








Kong, Portugal, and Greece, in terms of their Internet ratio (Arnum & Conti, 1998). The

study also concludes that several countries with relatively high levels of economic

activity--for example, Saudi Arabia, Oman, Venezuela, and the U.A.E.--have surprisingly

low levels of Internet activity (Amum & Conti, 1998). These results suggest that

although economic factors are important, there is more at stake in the case of Internet

adoption at the societal level.

Political Climate and Policy

Economic indicators by themselves cannot fully explain the diffusion of interactive

communication technologies, such as the Internet. Even among rich countries, there is a

large amount of variation in Internet penetration (ITU, 2000). A study focusing on the

Organisation for Economic Cooperation and Development (OECD) members concludes

that GDP by itself explains less than 40 percent of the variation in Internet connectivity

(Hargittai, 1999). Other studies have indicated the importance of the political stability of

a country on its overall development and adoption of new technologies (Berg-Schlosser

& Siegler, 1990). Clearly, political instability will present an obstacle to fast Internet

diffusion. A good example to support this claim is Rwanda, a country with serious

political conflict in recent years. The most recent data from the World Development

Report of the World Bank show that Rwanda has practically zero Internet usage (World

Bank, 2000).

The democratization level of the country has been suggested to be an important

predictor of Internet usage. Studies show some evidence that political freedoms are

positively related to Internet use (Daly, 2000; Norris, 2001; Rodriguez & Wilson, 2000).

Rodriguez and Wilson (2000), for instance, argue that a national democratic system is

critical in the adoption of information technologies such as the Internet. They underscore








the significance of democratic rights and civil liberties for the creation of a climate where

information and communication technologies (ICTs) can be easily adopted (Rodriguez &

Wilson, 2000). Most accounts show a reverse relationship: countries with restricted

political and civil liberties tend to have lower Internet usage levels, while democratic

societies tend to encourage Internet growth.

Rodriguez and Wilson (2000) measure technological progress as a combination of

TV sets, mobile phones, personal computers, Internet hosts, and fax machines. Their

study shows the following four factors are critical for national technological progress: a

climate of democratic freedoms that facilitates the adoption of ICTs; rule of law and security

of property rights; investment in human capital; and finally low levels of government

distortions. Interestingly, they found that a transition from the least free stage to a higher

stage of civil liberties led to an increase in growth rate of technology of 18 percentage

points (Rodriguez & Wilson, 2000). They also claim that "developing countries that

successfully innovate and diffuse ICTs are able to open their political systems as well as

their investment and commercial institutions" (Rodriguez & Wilson, 2000, 28). It seems

that the relationship between Internet use and political freedoms may be circular.

Another study testing the relationship between democracy and Internet use shows

that Internet penetration was highly correlated with higher political freedoms and

democratization levels (Norris, 2001). Norris (2001) also argues that Internet adoption

within a national context is generally affected by two broad factors: (1) socioeconomic

development and (2) democratization. Empirical testing showed that national level of

democratization is highly correlated with a New Media Index (Norris, 2001). When








controlling for income levels, however, democratization becomes insignificant (Norris,

2001).

One way of measuring democratization is by looking at the level of civil liberties

(Pritchett & Kaufmann, 1998; Rodriguez & Wilson, 2000). Definitions of civil liberties

vary. One organization that has consistently studied the level of civil liberties around the

globe is the Freedom House. Their civil liberties ranking focuses on several areas,

including freedom of expression and belief, independent media, freedom of assembly and

demonstration, rule of law and human rights, and personal autonomy and economic rights

in the country. The Freedom House civil liberties ranking emerges as the best proxy for

democratization and will be used as a predictor in this study.

In addition to democratization, government effectiveness can also directly impact

the rate of adoption of new technologies such as the Internet. Previous studies have

shown that the role of government is crucial in the early stages of Internet adoption

within a country (Bazar & Boalch, 1997; Lin, 1993). Lin (1993) argues that the American

government, for example, has played a critical role in the development and growth of the

Internet in the United States. National government policy has been critical for Internet

growth in Latin America and Western Europe as well (Petrazzini & Guerrero, 2000;

Tanner, 1999).

Policies are directly related to the political climate in a country (Godwin, 1998). A

study of cross-country Internet diffusion includes policy and urbanization variables in

addition to income to explain diffusion levels (Dasgupta, et al., 2001). Hargittai (1999)

finds a strong explanatory power in policies regarding the telecommunication sector in

her study of Internet connectivity among the OECD countries. Those countries that have








allowed free competition or even some degree of competition have a higher level of

Internet penetration than countries with telecom monopolies, other things being equal

(Hargittai, 1999).

Kiiski and Pohjola (2001) also include competition in telecommunications

(measured as existence of some form of competition in telecom markets) as a predictor of

Internet use. However, competition in their model is not found to be significant, in

contrast to Hargittai (1999). One possible explanation is that they use both competition

and access prices in one regression model. That combination can be redundant as the two

variables are likely to be correlated. Typically there will be an inverse relationship: more

competition will bring lower prices and vice versa.

Other researchers have also claimed that it is critical to take into account

government policies when trying to examine levels of Internet adoption (Petrazzini &

Guerrero, 2000; Sallai, 2000; Wolcott et al., 2001). This is especially important in the

post-communist countries, which have been undergoing major political transformation

have been trying to open up their telecommunications markets only since the early 1990s.

There is no doubt that government policies impact the pace of new technology

adoption. Changes in the telecommunications industry in the 1970s and in the 1980s in

particular have resulted in the introduction of privatization and liberalization policies in

many countries around the world (Bauer, 1994; Gruber, 2001). Western European nations

undertook a major shift toward telecom liberalization in the 1980s. Bauer argues that

three main factors contributed to this shift: innovative equipment resulting from rapid

technological changes; demand for customized and specialized telecommunications

services; and desire by the large telecom equipment providers to enter foreign markets.








It is important to understand the significance of national policy for the creation of

supportive Internet environment. Specifically, government support is needed to make the

Internet affordable for the population at large (The Internet's new borders, 2001). A

competitive telecommunications market becomes critical not only for the development of

e-business, but for making the Internet more accessible to people. A World Bank report

(1999) finds that telephone networks expand much faster in those countries that have

privatized their telecommunications market. Even if the telecom operator is a privatized

monopoly, it is claimed to be better than a state monopoly operator. Clearly national

policies in the telecommunications sector are important and need to be considered in the

study of country-level Internet adoption.

Government policy is found significant in a study of national computer imports.

Caselli and Coleman (2001) examine cross-country technology diffusion by looking at

the determinants of computer imports. Their study suggests that computer adoption is

related to policy: higher levels of trade openness towards the OECD positively affect the

number of computers in this case. The results also show that income per worker,

investment per worker, and secondary education are significant predictors. All of these

factors are positively related to computer adoption. The study also finds that computer

adoption is negatively affected when having a large government share in GDP as well as

large share of agriculture in GDP (Caselli & Coleman, 2001).

Privatization and liberalization policies directly affect the price of

telecommunications devices and services. Prices have been claimed to be higher in

countries with monopolistic telecommunications markets (Horvath, 2002; Jamison, 1995;

Ryan, 1997). Fish (1998) underscores the importance of privatization and liberalization in








the post-communist world in explaining, at least in part, the relative differences across

these countries (Fish, 1998).

Previous research shows that in general there are several stages in

telecommunications reform. At the first stage typically we observe privatization of the

incumbent state-owned telecom operator. At the second stage, competition in the telecom

market is introduced. General, it has been found that competition is more beneficial to the

consumer of telecommunications services.

Fish (1998) examines the power of privatization and liberalization combined as

determinants of the long-term economic reform in the post-communist countries. These

two sets of policies are important not only for the success of the economic reform in the

region, but also for the facilitation of telecommunications development and restructuring

from a centralized model to an open-market model. Paltridge (2000) argues that

liberalization in telecommunications facilitates Internet development. Internet access

prices are important factors as suggested by the vast variability in Internet usage across

the OECD group (Paltridge, 2000).

Sometimes privatization needs to be preceded by the adoption of a clear-cut

regulatory framework in the country (Wheatley, 1999). Wallsten (2002) argues that

institutional reform and regulations need to be in place before the telecommunications

firm is privatized in order to have a positive effect. In other words, he recommends

having regulation first and then subsequent privatization in the telecommunications sector

in any country.

It is critical to include the level of privatization when studying Internet penetration

in the post-communist countries (Estache et al., 2002, Kuentzel et al., 2000; Maddock,









1997). Privatization has been a difficult process in the transition from centralized state

economies to market-based economies in those countries (Ellis, 1999; Fish, 1998;

Gospic, et al., 2000; Gulyas, 1998; Hoelschner, 2000; Jasinski, 1997; Papir & Oleszak,

2000; UNDP, 1999). As Bauer argues (1994), the post-communist countries "often have

to create very favorable conditions for infrastructure service providers ... to succeed in

the attraction of foreign investment capital and technology." Lari (2000) underscores the

importance of both financial and non-financial aid that international institutions need to

provide for Eastern European countries. This need is especially acute in the area of

telecommunications (Lari, 2000). In addition to attracting foreign capital, privatization in

the telecommunications sector is also very important for competition and Internet growth

in general (Gulyas, 1998; Sallai, 2000; Sokolov & Goldenstein, 2000).

As Maddock (1997, 166) points out, "Eastern Europe has followed the Latin

American model by relying on liberalization to achieve reform but social and political

disruption has meant that the potential gains have not yet been achieved." In all post-

communist countries, the main telecommunications operator used to have a strong

monopoly in the domestic market. In the past, the incumbent telecommunications

operator often served as a tax collector and regulator (Canning, 1997; Maddock, 1997;

Michalis & Takla, 1997; Xavier, 2000). The pricing structure was distorted by cross

subsidies where domestic calls were artificially kept at a lower price, which was

compensated for most often by high international tariffs.

Campbell (1995), in his overview of the telecommunications industry in the former

Soviet Union, makes several observations, which are generally true for the rest of the

Soviet bloc. He notes that the control of the Post, Telephone, & Telegraph (PTT) is








completely in the hands of the government. The monopoly, he notes, will be rather

difficult to break as this sector is considered strategically important (Campbell, 1995).

The Communist leaders did not view information and communications networks as its

top priority. Campbell (1995, 25) concludes: "The telecoms sector illustrates the general

problem that it is not that easy to just start over. The old system left a technological and

organizational legacy that cannot be overcome quickly." The old structures--both

institutional and physical--will take time to improve and open up even though the Cold

War is over.

The telecommunications sector has being undergoing major reforms since then, but

it has proven to be quite difficult to modernize. Looking at the former Soviet republics,

Campbell notes that telecomss policy is a result of what is happening under the general

processes of privatization, antimonopoly policy, price regulation, and tax policy as much

as by specific legislation on telecommunications" (Campbell, 1995, 207). Among the

former Soviet republics, the Baltic states have been most liberal in giving autonomy to

the telecom operator. Ukraine and Belarus, on the other hand, show less desire to change

quickly. The reforms in these countries have been slower (Campbell, 1995). Central and

Eastern European countries are trying to get closer to the regulatory framework of the

European Union with their telecom legislation. The process of liberalization of national

telecom markets is going faster in these five countries: the Czech Republic, Estonia,

Hungary, Poland, and Slovenia (Bruce, 1999). However, there are different degrees of

progress not only across the region, but also across these countries.

Dasgupta et al. (2001) show the importance of policy, measured as the degree of

private sector competition in a study of cross-country Internet diffusion. However, this








measure does not directly capture the level of openness in the telecommunications sector

in particular. Thus, the policy variable in this study can be questionable, even though it

shows the expected direction of impact on Internet use. In addition, the policy index used

in the study is based on data from 1995 while the rest of the variables are from 1990. This

is another shortcoming of the policy predictor. This is a case in point that it is very

challenging to find a good measure of national policies, especially as they relate to

Internet development.

Indeed, it is difficult to measure the recent liberalization and privatization policies

in the post-communist countries. It can be argued that the overall level of market

openness within a country is reflected by the level of economic freedom, so the

Economic Freedom index of the Heritage Foundation could have been used. However, as

noted about the Dasgupta et al. study (2001), this can be misleading because if a country

has adopted liberal economic policies overall, its policies in the telecommunications

sector could still be very restrictive. Thus the level of privatization in telecommunications

specifically needs to be used, when data permit, to explain Internet adoption levels.

Privatization by itself, however, may lead to negative results in some cases.

Wallsten (1999) examined the effects of competition, privatization, and regulation in the

telecom markets in a number of African and Latin American countries. He found that

when regulation is introduced with the privatization reform, the effects tend to be

positive. Again, regulation is also an important aspect of telecommunications reform.

This study, however, measures only one aspect of telecommunications reform--telecom

privatization, which is only the first stage in the liberalization process. Future studies








should try to incorporate not only privatization, but also completion and regulation

variables, whenever possible.

Technology/Infrastructure

Hargittai (1999, 705) notes that "existing telecommunication facilities may be

crucial for understanding variation in the spread of the Internet." Bazar and Boalch

(1997) identify technology as one of five determinants Internet adoption in developing

countries, in addition to economic resources, needs and opportunities, necessary skills

and people to introduce the innovation, and finally good management of the diffusion

process. They position technology to include not only Internet technology itself, but the

general infrastructure within the country (Bazar & Boalch, 1997).

Amum and Conti (1998) argue that whatht TV was to the second half of this

century, what the telephone and the paved road were to the early 20 century, and what

the railroad was to the 19th century, so too is the Internet to the current generation."

Amum and Conti (1998) relate the speed of adoption of new technologies to the prior

existence of other infrastructure. They conclude that the Internet is more popular in

countries that have long-established infrastructures for communications and

transportation. Western European countries then will be more likely to have higher

Internet adoption rates, as they have historically had widespread networks of

transportation, communications, and other technological infrastructure.

Daly (1999) emphasizes that infrastructure in general varies widely across regions

of the world. Since existing infrastructure significantly affects Internet adoption in a

country (Amum & Conti, 1998; Bazar & Boalch, 1997; Elie, 1998; Gulyas, 1998;

Hargittai, 1999; Lin, 1998; Sadowsky, 1993), variations in Internet use are to be

expected. Gulyas (1998) argues that a modem telecommunications network is a basic








requirement for a society to become an information society. Elie (1998) contends that the

existence of a telecommunications network is critical for Internet adoption. Sadowsky

(1993) discusses the substantial physical and capital investment required to build Internet

infrastructure before a country can benefit from the Internet. He adds that the

infrastructure in many developing countries is inadequate for more advanced network

activities (Sadowsky, 1993).

In the former Soviet bloc, telephone infrastructure is generally inferior than the one

in place in Western European countries. Looking at the ex-Soviet republics, Cambell

(1995) notes that the telephone infrastructure in those countries is outdated and, therefore,

the quality of service is low. He says: "Old-fashioned and worn-out switching equipment

meant bad connections" (Cambell, 1995, 25).

Kiiski and Pohjola's study (2001) shows that infrastructure variables are critical for

the increase in the number of Internet hosts per capital. Specifically, per capital telephone

lines and number of PC's are included in their estimation (Kiiski & Pohjola, 2001). The

researchers note that both telephone lines and PC's are strongly related to GDP so they

may have a somewhat indirect effect on cross-country Internet diffusion. However, no

partial correlations are provided.

One way to measure the existing telecommunications infrastructure in a country is

telephone penetration (teledensity). Telephone infrastructure has been traditionally used

in studies on Internet penetration (Clarke, 2001; Elie, 1998; Guillen & Suarez, 2001;

Hargittai, 1999; Kiiski & Pohjola, 2001). The analytical framework proposed here will

use telephone density as an infrastructure indicator, but will also include mobile phones

in addition to residential phones.








Jupiter Research (2001b) projects a significant global increase in the number of

mobile Internet users. In the developing world in general, mobile phones seem to play an

important role. In some African countries, the number of mobile phone subscribers

surpasses those that use residential phones. Interestingly, Uganda has more mobile phone

customers than fixed telephone customers as of July 1999 (Minges, 2001). The popularity

of wireless is evident in the Latin American region as well. Research shows that there is

an emerging audience in Latin America which will access the Internet only or primarily

from a mobile phone (Jupiter Research, 2001). The growth of the mobile telephone

market in Eastern European countries has served as a major incentive for

demonopolization of telecommunications service overall (Oaca, 2000).

It is true that Internet usage is dependent on phone line availability and also on

computer availability. Clearly, to connect to the World Wide Web one needs to have a

personal computer in the first place. Yet lack of data prevent us from using number of

computers per capital as an independent variable in this study. Also, even though the

association between Internet users and number of computers is relatively clear, the

direction of causality between the two variables is not so obvious.

Another question that may arise is why not include cable infrastructure to account

for broadband Internet users. Broadband use in the post-communist countries is very

limited. Even in Western Europe, broadband Internet has not become very popular

(Pastore, 2002). Pastore notes that Western European countries are not yet ready to go

broadband. Specifically, the number of broadband users of all Internet households is

about eight percent in France, nine in Germany and a very low two percent in Britain








(Pastore, 2002). In the post-communist countries, it will be quite a while before

broadband technology becomes available nationwide.

Audience Characteristics

Research to date has focused more on the supply side rather than the demand side

when examining Internet diffusion within countries (Lamberton, 1997). Researchers have

attempted to answer the question what demographic and attitudinal characteristics affect

Internet adoption. Diffusion of innovations (reviewed above) shows that innovators and

early adopters typically have higher socio-economic status, are better educated, more

cosmopolite, and technologically savvy (Atkin et al., 1998; Rogers, 1995).

Audience characteristics affect Internet adoption in several ways then. First of all,

education has emerged as a major determinant of Internet adoption both at the individual

and country level. The higher the education level of the general population, the more

likely people are to adopt new media technologies such as the Internet (Caselli &

Coleman, 2000; Hargittai, 1999; World Bank, 1999). Lack of adequate education, on the

other hand, can impede Internet diffusion. El-Nawawy (2000), for example, sees

education as the primary deterrent to Internet growth in the case of Internet adoption in

Egypt.

Caselli and Coleman (2000) contend that the choice of technology is driven by the

human capital in a country. They conclude that countries that have more skilled labor

adopt technologies that efficiently use that labor, which in turn leads to more capital. In

contrast, countries with more unskilled labor adopt "less sophisticated" technologies and

accumulate less capital as a result (Caselli and Coleman, 2000). Press et al. (1998) note

that there are several determinants of Internet adoption, including the existing

telecommunication infrastructure, financial resources as well as human capital. The








characteristics of the human capital then can be seen as drivers of or barriers to Internet

adoption.

Kiiski and Pohjola (2001) examine cross-country diffusion of the Internet using the

Gompertz model of technology diffusion. They include educational level as one of the

predictors in their study (Kiiski & Pohjola, 2001). Surprisingly, education does not show

statistical significance. This could be due to lack of variation across the countries, as they

examine only OECD members. Another possibility is that years of schooling is not the

best education variable to be used as a predictor of Internet adoption. Both of these

explanations could be true because when the regression analysis is replicated on a world

sample of countries and education is measured by university attendance, it becomes

significant.

College education is critical in the new communications era. According to the

World Bank, basic education is important overall, but "new, information-based

technologies are more demanding in skills for diffusing, interpreting, and applying

knowledge" (World Bank, 1999,42). The report additionally notes that "countries at or

near the technological frontier need strong tertiary education and research institutions to

compete in the creation of new knowledge" (World Bank, 1999,42).

English language proficiency is another important factor for Internet adoption since

the World Wide Web is still dominated by English-language Web sites (Global Reach,

2000),3 even though projections indicate that Chinese will become the dominant Web

language by 2007. If more users speak English within a country, they are more likely to

search for the predominantly English-language Web content. Sadowsky (1993), for

3 Even though the domination of the English language is expected to wane, it was still by far the
predominant online language at the time this study was conducted.








example, argues that the ability to find online content is critical for Internet popularity in

developing countries. Interestingly, the rapid growth of Internet use in Bolivia has been

connected to the increased Spanish-language online content (Minges, 2001). English

language fluency facilitates not only content retrieval, but also computer and software

4
usage.

Wallraff (2000, 61) contends that "most people like new technology better when it

speaks their own language." Even though the English language has achieved a global

status, the proportion of English-speaking people is expected to shrink to less than five

percent in 2050. (Wallraff, 2000).

Caselli and Coleman (2001) include the fraction of the population who speak

English as a predictor of computer adoption. They test for the effects of English or

European language skills of the population. The language variable in this study is defined

as the proportion of those who speak English as a first language (Caselli & Coleman,

2001). The results of their study, however, show that fluency in English is not statistically

significant.

Hargittai (1999) defines "human capital" as related to Internet usage to include

educational level and English language proficiency. The addition of human capital

significantly improves the fit of the regression model. Hargittai (1999) finds that

education is positively correlated with level of Internet adoption (i.e., the higher the

educational level in the country, the higher its Internet connectivity). On the other hand,

lower education levels may prevent mass adoption of the Internet.


4 Most computer commands, instructions, and help files are in English.








Similarly to Hargittai (1999), Kiiski and Pohjola (2001) include English language

proficiency in their model. Hargittai's study shows no significance for the English-

language variable. Even more unexpectedly, the English language variable in the Kiiski

and Pohjola (2001) analysis has a negative sign. It could be inferred that at this stage of

adoption among the OECD group of countries, English language is not a significant

factor.

The framework proposed here defines audience factors as including both

educational level and level of English language proficiency. If data permit, both will be

used as predictors for the level of Internet penetration in the post-communist countries.

These are the two most important audience characteristics identified in current literature

on new communication technologies adoption.

Cultural Factors

Finally, it has been argued that culture affects Internet adoption in a country (Elie,

1998; Maitland, 1998). Elie gives the example of European and Asian former Soviet

republics, claiming that GDP and telecommunications infrastructure cannot explain the

differences in their Internet positions. Maitland (1998) argues that culture should be

included as an explanatory variable of the adoption of interactive technological

innovations, such as the Internet. She argues that adding cultural differences makes the

understanding of Internet diffusion across countries more robust (Maitland, 1998).

Researchers acknowledge that the construct of culture is very complex (Jones,

1997; DiMaggio, 1997; Sondergaard, 1994; Tayeb, 1994). Writing in Britain in the late

1950s, Raymond Williams conceptualized one of the first definitions of culture. He

wrote: "Culture is ordinary: that is the first fact. Every human society has its own shape,

its own purposes, its own meanings. Every human society expresses these, in institutions,








and in arts and learning" (Gray & McGuigan, 1997, 6). Broadly defined, culture refers to

the values, religious beliefs, ethics, institutions, customs, and traditions shared by a group

of people. Thus, cultural traits are innate to all individuals living in a social system. They

are embedded and transparent within the culture.

DiMaggio (1997) among others points out that culture is a very complex concept.

Sociology and psychology researchers have looked at various dimensions of culture and

cognition. DiMaggio (1997) suggests that culture is fragmented across groups. The move

from understanding culture as a unified to fragmented phenomenon "makes studying

culture much more complicated" (DiMaggio, 1997, 265).

Hofstede (1980), however, sees culture as cohesive and manifested in national

societies where people within the country share certain beliefs and attitudes. This

conceptualization supports Williams' definition of culture (Gray & McGuigan, 1997).

Culture then exists at the societal level as an aggregate of individuals' shared beliefs and

attitudes.

Hofstede (1980) developed four dimensions to measure differences across

cultures: power distance, uncertainty avoidance, individualism and collectivism, and

masculinity and femininity. The cultural dimension which relates to the adoption of new

media and the Internet is uncertainty avoidance (Hofstede, 2001). Broadly defined,

uncertainty avoidance is "the extent to which the members of a culture feel threatened by

uncertain or unknown situations" (Hofstede, 2001, 161). It follows that countries with

higher uncertainty avoidance would be more resistant to the adoption of the Internet

compared with low uncertainty avoidance countries.








Katchanovski (2000) examines the influence of culture on economic growth in the

post-communist societies. He concludes that cultural differences do affect growth both

directly and indirectly. Katchanovski (2000) derives a cultural index on the basis of five

aspects of culture. His factor analysis identifies one factor consisting of civil society

index, religion, historical experience, and business index, which is labeled Western

Culture Index. The addition of cultural variables improves the fit of the regression model,

with the Western Culture variable showing the highest standardized regression

coefficient.

Domanski (2000) looks at religion and its effects on modernization in Eastern

Europe. The results of the study show a correlation between religiosity and social

stratification. It is clear that different religions are dominant in the different countries.

Based on 1993 data from six Eastern European societies, Domanski (2000) argues that

Poland is the most religious and the Czech republic the least religious of those. The level

of religiosity across all post-communist nations is expected to vary even more.

Cultural traits have been given as an explanation for differences in Internet

adoption among Western European countries (Forrester Research, 2000). Several studies

support the argument that culture influences the diffusion of technology in a country

(Maitland, 1998; Rey, 1998). Some studies divide Western European countries depending

on their geographic location (Beilock & Dimitrova, 2003; Kiiski & Pohjola, 2001). Kiiski

and Pohjola (2001) include a dummy variable for OECD countries depending on whether

they are located in southern or northern Europe (N=23). Beilock and Dimitrova (2003)

regress Internet usage rates against the percent of Roman or Orthodox Catholics in each

Western European country. Interestingly, these cultural variables show statistical








significance in both studies. In fact, the model fit improves once the regional dummies

are added in the Kiiski and Pohjola study (2001). Therefore, they conclude that there are

certain cultural factors that play an important role in the process of Internet diffusion.

Drawing from diffusion of innovations, Maitland offers five propositions how

culture can influence the adoption of interactive technologies at the country level.

Maitland positions gender equality as a social norm. Interestingly, she argues that the

diffusion of interactive networks, such as the Internet, will be higher in countries with

higher gender equality. Maitand (1998) extends the notion of "cosmopoliteness" from

diffusion of innovations to the country level. Basically, she suggests that openness of

society can be measured by the country's ethnocentrism, and that cultures low in

ethnocentrism will begin the diffusion of interactive networks earlier. This argument has

been supported by others as well (Rey, 1998). The way of measuring countries'

ethnocentrism can be problematic, however.

Religion is an important part of culture. In a study of economic reform in the post-

communist world, Fish (1998) includes religion as a determinant. First he uses three

categories for religious affiliation, but his ANOVA comparison of means indicates that

there is, in effect, no statistical difference between the Muslim/Buddhist and Eastern

Orthodox group. The analysis shows that the number of religion categories can be

reduced to two, namely the Catholic/Protestant countries as group 1 and the

Muslim/Buddhist and Eastern Orthodox countries as group 2 (Fish, 1998). Western

Christianity arguably shows similarity with Western culture/societies. The results in the

Fish (1998) study, however, show no effect of religion on economic growth.








The fifth dimension of our Internet diffusion model will be cultural factors. These

will be represented by dominant religious composition of the population. Incorporating

this variable with a focus on the three dominant religions also allows for measuring a

particular aspect of culture--Westernization-though the Western Christianity variable.

Conceptual Framework

The diffusion of innovations literature reviewed above posits that diffusion is a

linear process. It identifies several individual characteristics that are critical for Internet

diffusion, namely income, educational level, cosmopoliteness and innovativeness traits.

The income and education levels of the audience are critical in the adoption process.

Diffusion of innovations research also shows that externalities are important for Internet

adoption in developing countries. Government policy and preexisting technology are

among the determinants identified in diffusion of innovations literature.

New media technologies research, too, supports the notion that the political climate

and technological infrastructure are critical for Internet use. Past research suggests that

economic factors remain one of the most significant determinants of Internet adoption at

the country level. New media technologies studies also show that audience characteristics

(human capital) as well as cultural factors play an important role in the diffusion process.

Thus, a multitude of factors emerge as significant for the Internet diffusion process

at the societal level. The five sets of factors identified in diffusion of innovations and new

media technologies literature constitute the conceptual framework used in this study.

They are:

1. Economic factors
2. Political climate and policy factors
3. Technology/Infrastructure factors
4. Audience factors
5. Cultural factors









This five-dimensional analytical framework for the study of Internet adoption at the

country level is proposed and tested in this dissertation. Specific variables pertaining to

each set of factors are described in the following chapter.

Further Thought

Rogers posits that innovations have the following five attributes: relative advantage

(whether the innovation is better than previous ones), compatibility (whether it is

compatible with previous technologies), observability (how hard it is to use the

innovation), trialability (whether a person can try out the innovation), complexity (how

difficult it is to use it) and observability (whether the results of the innovation are readily

observable). He adds reinvention as the sixth additional attribute. Reinvention refers to

cases when an innovation is used in a new way/for completely new purposes.

These six innovation attributes and the five dimensions identified here interplay

with each other. The framework proposed above includes economic, political climate and

policy, technology/infrastructure, audience characteristics, and cultural factors. These are

conceptualized as country-level determinants of Internet adoption. Below, some possible

influences on Internet adoption patterns as a result of the interactions between the two

models are described.

The Internet is a very complex innovation. It can be used for a number of different

purposes, ranging from email to data searches to online marketing. The relative

advantage of the Internet will be higher for people who can see its value as a marketing

tool or even as a way to market their products abroad. In fact, countries in the lower

middle income range (such as many of the former socialist republics) may gain more by

using the Internet for import and export of various goods or services. In other words, the








relative advantage of the Internet will be higher for countries with lower national

incomes, which also tend to be less involved with international trade.

The Internet is not compatible with almost anything that existed prior to it. That

means countries with very low Internet may need to have special training programs for

potential users to show them how the Internet works. Countries with lower GNP levels

are less likely to spend money on training courses. The combination of lower income and

lower compatibility will make the adoption process in those countries for the Internet

slower, compared with innovations with higher compatibility in a country with the same

income level.

The benefits of Internet use are readily observable. Messages travel instantly and

information (usually) is downloaded very fast. Countries with lower income levels,

however, do not take advantage of higher speed Internet as much as they lack broadband

technology (ITU, 1999). Thus, the results of Internet browsing, mailing, downloading

and so on can be a little slower. If the user does not have a basis for comparison though,

this interaction is unlikely to have an effect on the rate of Internet adoption. The more

observable the results are to the users, the more likely they would be to go online again in

the future.

The trialability of the Internet as an innovation is also likely to affect its adoption.

If a person cannot try/does not have access to an Internet terminal, they are unlikely to

adopt it. Again, poorer nations have lower Internet penetration. Especially in rural/

remote areas, people have no access to the Internet. Countries with lower national income

will have less Internet connections/terminals available for public use, which means that

the potential adopter will have fewer chances to try out the Internet. This means they will








be less likely to adopt compared to persons in countries where the Internet is widely

spread.

People in more affluent societies tend to have access to more technologies and

other communication innovations (e.g., personal digital assistants or PDAs). In a way,

they are more likely to reinvent the Internet from say, just a typewriter or email box, to

use for online banking. (Online banking, of course, is related to a whole network of

technologies, software products, bank accounts security and other issues).

Some governments may adopt policies facilitating Internet penetration, especially if

they perceive the ability to receive public feedback online as valuable. Thus, the

relationship here is reversed: those political leaders who see the Internet as a tool for

encouraging public participation may be more likely to pass legislation that promotes

Internet adoption. Alternatively, those governments which see the Internet as a threat are

likely to adopt measures to limit its use.

As my dissertation proposes, privatization and liberalization policies can facilitate

Internet development and thus make it more available for people to try. This interaction

shows that for countries with more favorable market policies, the trialability of the

Internet will be higher. This interaction is likely to lead to faster adoption rates. Also, if

the beneficial results of Internet use are obvious for the policy makers, then adoption will

be promoted by favorable policies.

People who live in a country with limited communication technologies will see

more relative advantages of the Internet, as it is likely to be one of the few ways to

connect with people or get information. People who live in country with extensive

technological infrastructure will find the Internet more compatible, will have an easier








time using the Internet and trying it out in general, will find it less complex and may even

be more likely to reinvent its use because of their previous experience with various

technologies.

Those who can read English will be able to find much more information online and

thus will perceive the Internet as more valuable. A person who can only read Macedonian

is limited in the amount of online content he/she can locate compared to another person

fluent in English. If the person uses the Internet for email only, that will not be a major

issue, however.

Arguably, people with higher education levels will see more value in Internet

information, particularly highly specialized information in their professional areas. In

addition, more educated people will be more likely to want to have professional contacts

with others around the world. Thus the Internet with its email and bulletin board

capabilities can be considered even more valuable.

A person with higher education is more likely to have used a personal computer

(PC). Therefore, such people will find the Internet more compatible with their previous

experiences as opposed to those who have never used a PC.

Some religions may view the Internet as more valuable than others. More closed

societies definitely are not as likely to embrace the Internet compared with more open

societies. Also, societies which have been isolated in terms of information from the

outside world may see the Internet as fulfilling an acute need--they will then perceive the

Internet as more valuable.

Some societies are more open to new ideas and find it easier to adopt new

technologies. Thus members of more open cultures may find it less complex to use the





81


Internet and also more compatible with their cultural predispositions. Certain cultural

traits can affect the way people use and come up with reinvention ideas for various

technologies.













CHAPTER 4
METHODS

This chapter outlines the methods for testing the five-dimensional analytical

framework proposed in the previous chapter. The main research question addressed in

this study is what factors affect Internet adoption in the post-communist countries. Six

testable propositions are made. The study aims to identify the most significant predictors

of Internet adoption and explain a significant portion of the variation in Internet use.

Operational definitions, data collection methods, and hypotheses are proposed below.

The method chosen is governed by the primary research question and the nature of

the data. The research design is described next.

Research Design

The literature review identified five sets of factors that affect Internet diffusion at

the country level. These are economic factors, political climate and policy,

technology/infrastructure, audience characteristics, and cultural factors. To use these

factors in a systematic, multivariate analysis, they need to be further defined as specific

variables pertaining to each set of factors. The operationalization of variables is shown in

Table 4-1. The study uses secondary data from a number of different sources. Data

sources and collection methods are provided below. The study employs t-test, multiple

regression, and Tobit analysis to test hypotheses and examine the significance of the set

of explanatory variables. Theoretical propositions and statistical procedures for testing

them follow.









Table 4-1. Definition of variables in the proposed model of Internet diffusion.
T VARIABLE DEFINITION OPERATIONAL NAME DATA YEAR
Y DEFINITION SOURCE
P
E
Internet Individuals Estimated Internet IUR ITU 1999,
users using the users per 10,000 July
SInternet in a people
z particular
country, per
capitala
Gross GNP per The total domestic GNP World 2000
national capital, and foreign value Developme (1998)
product Purchasing added claimed by nt
Power Parity residents within or Indicators
outside the
country's borders,
converted to the
U.S. dollar value of
U the goods and
Services which can
0 be purchased within
Z
C the country in the
S local currency. _______
Level of Length of Number of years PRIV Privatizatio 1999
privatization privatization of since the incumbent nLink,
u in incumbent has been privatized, MIGA
Stelecommun telecom either fully or (part of the
ications operator partially World
o0 Bank)___
Democratic Level of civil Composite ranking DEM Freedom 1999
ation liberties based on 14 criteria House



Teledensity Number of Number of TEL ITU 2000
residential telephone lines per (1998)
phones per 1,000
capital people plus the
number of mobile
U phones per 1,000
.__.______________ people______________


Even though the World Development Indicators Report was issued in March 2000, most of the data are
from 1999 and 1998.








Table 4-1. Continued.
T VARIABLE DEFINITION OPERATIONAL NAME DATA YEAR
Y DEFINITION SOURCE
P
E_________
SEducation Enrollment of Tertiary percent of EDU World 2000
u level college relevant age group, Developme (1997)
Z students gross enrollment nt
ratio Indicators


Religion Predominant Two dummy MSL, Fish; CIA 1998;
religion variables, using WST World 2000
Eastern Orthodox Factbook;
as a base: 1 if U.S. State
Western Christian Department
_(Catholic or
Protestant) and 0
Otherwise; 1 if
Muslim/Buddhist
and 0 otherwise.


Data Collection

The study uses secondary country-level data from a number of sources. It is

important to underscore that comparative data for the post-communist countries are

difficult to find. Fish notes that there "exists no reliable cross-national survey" that

encompasses all post-communist countries (1998, 37). Aggregate data from international

organizations--notably the International Telecommunication Union (ITU) and the World

Bank (WB)--are used in this study. Thus, definitions of indicators are drawn directly

from the original data source. Alternative data sources are also used to cross-check the

telecommunications data in particular.

The main data sources as shown in Table 4-1 are: Freedom in the World published

by the Freedom House; PrivatizationLink of the World Bank; World Development

Indicators published by the World Bank; and the World Telecommunication Indicators








Database published by the ITU. National government sources are also used in cases when

secondary data are not available from the international organizations noted above. For the

religion variable, the work of Fish (1998) is used as the main data source and cross

checked against the CIA World Factbook and country data from the U.S. State

Department Web site. Additional sources are noted in the statistical analysis.

Operational Definitions

It is critical to determine which potential variables best reflect the broad set of

factors identified in the literature review.

Economic variable

The main economic indicator to be used is per capital income. Gross national

product (GNP) per capital is the variable chosen in this model. This standardized variable

is a key indicator of national economic development and allows easy comparisons across

countries (Kennedy, 1998). The GNP measure includes the total domestic and foreign

value added claimed by residents as well as net receipts of primary income (both

compensation of employees and property income) from nonresidents (World Bank,

2000). GNP is calculated in U.S. dollars, using the Atlas method for conversion.

However, GNP in terms of purchasing power parity (PPP GNP) is more appropriate for

this study as it reflects the citizen's ability to buy goods and services (Arquette, 2002;

Beilock & Dimitrova, 2003), such as Internet connection or dial-up services. PPP GNP is

the U.S. dollar value of the goods and services, which can be purchased within the

country using personal income in the local currency. Thus, an "international dollar has

the same purchasing power over GNP as a U.S. dollar has in the United States" (World

Bank, 2000, 13). The income variable will be log-transformed, based on Rodriguez and

Wilson (2000).








A few methodological notes are in order. First, the GNP data for Bosnia and

Herzegovina and for Ukraine come from the next edition of World Development

Indicators, using 1999 data--not 1998. Yugoslavia's GNP data is based on data for

Macedonia, because of the inherent similarity between the two transition economies.

Political climate and policy variables

The political climate is measured by the level of democratization in the post-

communist country, which is demonstrated by the level of civil liberties. Thus, a good

proxy variable for the level of democratization in the country is the Freedom House

ranking of the level of civil liberties. This ranking is based on 14 different criteria, which

include freedom of expression and belief, free and independent media and freedom of

cultural expression. The Freedom House has collected data on civil liberties within

countries since 1972. It publishes an annual assessment of the state of freedom within a

country by assigning a score to each state worldwide. The civil liberties ratings range

from 1 to 7. A rating of I refers to a country considered "Most Free" while a rating of 7

denotes "Least Free" countries. The scores will be inverted for analysis so that higher

rankings indicate higher levels of civil liberties in society. The inverted ratings also make

interpretation of the regression coefficients easier.

The civil liberties variable is a proxy for the level of democratization in the

country. In other words, the higher the level of civil liberties, the more democratic the

country is. Similarly to the Rodriguez and Wilson (2000) study, the civil liberties variable

is treated as interval even though it is an ordinal variable, similarly to the Rodriguez and

Wilson (2000) study. The difference between a country with a score of 5 and a country

with a score of 1 is not exactly 5 times, but this is assumed to be a good approximation

established by the Freedom House foundation.








The policy variable used is the length of telecommunications privatization. At first

glance, privatization can be seen as an economic variable. However, it belongs in the

political climate and policy category as it is a direct result of the decisions of the political

leaders in the country. The specific sector of interest in this study is telecommunications.

There is no consistent cross-country data on overall telecommunications policy in the

region. Thus, the study uses privatization of the incumbent telecommunications operator

as the best proxy for telecommunications policy in the country.

In this study, we assume that earlier privatization of the main telecom operator is an

indication of successful national policy in the area of telecommunications. In Bulgaria,

for example, the privatization of the main telecom operator, BTC (Bulgarian

Telecommunications Company), has been seen as one of the major privatization

transactions on a national level, comparable with that of the national electricity operator

and major tobacco companies. The fact that BTC's privatization has been extremely

difficult and slow is an indication of poor policy making on the part of the Bulgarian

government.2 This policy has allowed BTC to continue its monopoly. The reverse is true

in the case of Hungary: The major telecom operator MATAV was privatized in 1993 and

is considered a major sign of the success of Hungarian telecommunications

policymaking.

The definition of the telecommunications privatization variable is number of years

since the incumbent telecom operator has been privatized, either fully or partially, at the

end of 1999. This operationalization provides a method for determining the length of the

telecommunications privatization in the respective countries. The length of privatization


2 BTC's still pending privatization has not been completed as of end of 2002.









is clearly related to telecom deregulation in these countries, which makes it a good proxy

variable3 to be used in this research.

Technology/Infrastructure variable

A number of variables that measure Information and Communication Technologies

(ICT) infrastructure exist. For the purposes of this study, only telephone infrastructure is

included, even though cable, TV, and other technologies can also play an important role

in Internet development. Broadband technology is not yet a viable option for Internet

connection in the post-communist countries. The telephone provides the main mode of

network connectivity in the region and has been used as a determinant of Internet

adoption in a number of studies (Beilock and Dimitrova, In press; CDT, 2000; Hargittai,

1999).

A logical possibility for an infrastructure variable in this model would have been

the number of computers per capital. As mentioned in Chapter 3, we cannot account for

Internet users if we do not have computers in the first place. However, lack of data for the

majority of the countries of interest prevents us from using that variable.

The most significant infrastructure variable regarding Internet usage is the number

of telephones in the country. Thus, the main infrastructure variable used here is the

number of residential phones per capital. This is measured by the International

Telecommunication Union (ITU) as telephone mainlines per 1,000 people. This measure

includes all telephone lines connecting a customer's equipment to the public switched

telephone network (PSTN).

3 Another potential measure of political climate and policy would have been the level of economic freedom.
Economic freedom is commonly measured by the Economic Freedom Index, which is based on 10 areas,
including government intervention, property rights, and foreign investment. However, economic freedom
does not directly reflect openness in the telecommunications sector, which is of particular interest in this
study.








However, mobile phones play an important role in the technological advancement

of the post-communist societies. The growth of the mobile market in the post-communist

countries has been seen as a basic representation of the overall market demonopolization,

as noted in Chapter 3. Also, technology today allows users to connect to the Internet via a

mobile phone. The number of mobile phones per 1,000 population is then combined with

the number of residential phones per 1,000 population into one independent variable

called teledensity. The only disadvantage of using this composite variable is that we

cannot compare the separate effects of mainline telephones and wireless.

Audience variables

Two critical characteristics of the audience as Internet users were discussed in the

literature review. The most important variable in this category is educational level. Past

research shows that early adopters of the Internet tend to be more educated and usually

hold a college degree (Atkin et al., 1998; Howard et al., 2001; ITU, 1999). Thus, the

study uses educational level as measured by the gross enrollment ratio in tertiary

education of relevant age group. This variable shows how many people in the relevant

age bracket are attending college in a particular country.

As the literature review showed, people who speak English are more likely to go

online and have an easier time browsing the Web. The best proxy variable for English

language proficiency is looking at the number of students who take English as a foreign

language in school. One way to measure it is as the percentage of pupils in secondary

education learning English. However, such data are limited only to current or future

members (the so-called candidate countries) of the European Union. Thus, English as a

second language is not included in the final regression model, but is recommended for

future studies.









Cultural variable

Arguably, the best cultural measure is the dominant religion in the country. As Fish

observed about the post-communist region, "in the overwhelming majority of countries, a

single religious tradition clearly predominates" (1998, 41). National religion is a stable

variable, not quick to change (Fish, 1998). Using data from Fish (1998) and the CIA

Factbook (2000), the study incorporates religious affiliation as a cultural variable.

Orthodox Christianity is the most common religious group in the sample. The other

two major groups are Western Christians and Muslims. It is argued that these three

groups are substantially different from each other (Fish, 1998). The following nine post-

communist countries are predominantly Western Christian (Catholic or Protestant):

Croatia, Czech Republic, Estonia, Hungary, Latvia, Lithuania, Poland, Slovakia, and

Slovenia. The majority of the countries are predominantly Eastern Orthodox (Armenia,

Belarus, Bulgaria, Georgia, Macedonia (FYROM), Moldova, Romania, Russia, Ukraine,

and Yugoslavia (Serbia and Montenegro). Therefore, Eastern Orthodox religion will be

used as a base group for the dummy variables (coded as 0). The remaining nine countries

are predominantly Muslim, with the exception of Mongolia.4 Thus, two dummy variables

will be employed to represent the three major religions in the region.

Dependent variable

The dependent variable of interest in this analysis is Internet users per capital. This

indicator is measured by the International Telecommunication Union (ITU) as the

estimated number of Internet users based on the number of Internet hosts in the country.

The dependent variable in this study will be transformed as a natural logarithm of the

4 Mongolia is a predominantly Buddhist country, but is included in the Muslim group in this analysis, based
on Fish (1998).








number of Internet users because the distribution of that raw variable is skewed.

Logarithmic transformations are especially useful in cases when the normality of the

distribution is violated, usually resulting from the magnitude of the changes in the

observed variable. Therefore, the interpretation of the beta coefficients is in terms of

ratios, not in additive terms. When the data have been log-transformed, the slope

indicates a ratio of change (increase or decrease) in the dependent variable.

The number of Internet hosts is collected by Network Wizards on a biannual basis.5

These data are used to estimate the number of Internet users per country. Internet hosts

and Internet users are the most commonly used measures for country-level Internet

penetration (Press et al., 1998). For complete explanation on data processing of the raw

Internet host data, check the World Telecommunication Indicators 2000/2001 edition or

visit the ITU Web site (http://www.itu.int/ITU-D/ict/publications/wti2000-01/). A brief

explanation follows.

The number of Internet hosts per capital refers to individual computers connected to

the Internet--i.e., computers with an actual IP address. Network Wizards collects data on

active Internet hosts worldwide. This measure of Internet usage has been criticized in the

past (OECD, 1998a; Minges, 2000; Press, 1997; Zook, 2000). One reason is that Internet

hosts are misleading if more people use the Internet at Internet cafes rather than at a home

computer. In addition, Internet host figures are derived on the basis of country code top

level domains (TLDs) rather than actual physical location of the host. As Minges (2000)

explains, a host under the .RU country code domain can be located anywhere in the

world, not necessarily in Russia. By the same token, the so-called generic TLDs (.com,

5 A detailed description of Network Wizards' data collection methods can be found at
http://www.isc.org/dsview.cgi?domainsurvey/new-survey.html.