 

2010

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After Closing the Rural Broadband Gap:
The case of Korean Information Network Village

presented by
Kyujin Shim

has been accepted towards fulﬁllment
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Master of Arts degree in Telecommunication,
Information Studies & Media

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AFTER CLOSING THE RURAL BROADBAND GAP: THE CASE OF
KOREAN INFORMATION NETWORK VILLAGE

By

Kqu in Shim

A THESIS

Submitted to
Michigan State University
in partial fulﬁllment of the requirements
for the degree of

MASTER OF ARTS
Telecommunication, Information Studies & Media

2010

ABSTRACT

WHAT HAPPENS AFTER THE RURAL BROADBAND GAP IS CLOSED?
THE CASE OF KOREAN INFORMATION NETWORK VILLAGE

By
Kqu in Shim
Having reached 98% coverage in rural areas in Korea, the Information Network

Village (INVIL) project focused on not only constructing broadband infrastructure but
also building online social networks. The current study examined the impact of public
investment in information communication technology on online interaction and social
capital in rural areas after broadband infrastructure was saturated. The ﬁndings indicated
that public investment served a key role for the sustainable development of rural area

through increasing community attachment and reducing migration intention.

To Min

ACKNOWLEDGEMENTS

First and foremost I offer my sincerest gratitude to my committee chair, Dr.
Robert LaRose. His guidance with scholarly rigorousness and expertise has opened up
my world to academic beauty; a world loomed with sensible words and coherent logics.
Were it not for his encouragement and support, this thesis would not have been
completed. I gratefully acknowledge my committee members, Dr. Steve Wildman and
Dr. Cliff Lampe, for their truly constructive advice and valuable feedback.

Words cannot express my appreciation to my husband for his dedication and
persistent conﬁdence in me. His unconditional love and sacriﬁce have brought me to the
US, and to the world-renowned graduate program at Michigan State. My son, Youn has
been and will always be the source of my delight, future, and hope. Also, I truly
appreciate my parents and parents in law who always stand by me. Without their constant
care and support, I would not be able to concentrate on my masters’ work in the US.

Seungcheol Austin Lee is the one who should have the most credit for my thesis.
He contributed to data analysis and his efforts have been integrated into all parts of this
paper. I really appreciate his collaboration and admire his strong commitment to
academics, which has disciplined and matured me.

Last but not least, I would like to extend my special gratitude to my colleagues
and friends, SeungYun, Allison, Angela, Lily and Shawn to name a few, who have
signiﬁcantly contributed to this thesis by ceaselessly reviewing my work and challenging
my academic motivation and execution. Thanks to them, my stay at Michigan State

University could not be happier and more fruitful.

TABLE OF CONTENTS

LIST OF TABLES ................................................................................................. vi
INTRODUCTION .................................................................................................. 1
OVERVIEW OF INVIL ......................................................................................... 4
LITERATURE REVIEW ....................................................................................... 6
Closing the digital divide and INVIL ......................................................... 6
Internet Self-Efﬁcacy and Outcome Expectations ...................................... 7
Social Capital and INVIL ........................................................................... 9
Online interaction and Community attachment .......................................... 9
Community Satisfaction and Intention to stay .......................................... 11
METHOD ............................................................................................................. 14
Participants ................................................................................................ 14
Procedure .................................................................................................. 14
Measurement ............................................................................................. 15
Data Analysis ............................................................................................ 17
RESULTS ............................................................................................................. 18
Demographic Differences ......................................................................... 1.8
Correlation Analysis ................................................................................. 18
DISCUSSION ....................................................................................................... 22
LIMITATIONS AND FUTURE RESEARCH ..................................................... 26
CONCLUSION ..................................................................................................... 28
APPENDIX ........................................................................................................... 29
Research Participant Information and Consent Form ............................... 29
Questionnaire (English) ............................................................................ 31
Questionnaire (Korean) ............................................................................. 41

LIST OF TABLES

Table 1. Correlation Matrix of Variables Controlling for Demographics ............ 20

Table 2. t-Test Analysis ........................................................................................ 21

vi

INTRODUCTION

Public investment in lnforrnation Communication Technology (ICT) and its effect
on rural development is becoming a global issue as niral outmigration and an economic
downturn are threatening the sustainability of rural society. Efforts in telecommunication
infrastructure investment had a signiﬁcant impact on social and economic development in
rural and developing regions (Hudson, 1995). Reducing the rural-urban broadband gap is
also a critical issue even to developed countries like the United States. It was shown that
government investment in rural broadband had signiﬁcant relationships to rural
employment and economic viability (Gillett, Lehr, & Sirbu, 2006; Katz & Suter, 2009).

However, it is unknown whether public investment in ICT is still effective after
broadband adoption reaches high penetration levels nationally (i.e., “saturated”, Katz &
Suter, 2009, p. 2). To address this question, it is worth noting the Korean case of INVIL
(Information Network Village), which is a govemment-driven project that aims to build
broadband infrastructure in rural areas and online communities of local residents. While
many parts of the world are still implementing public investment in infrastructure, Korea
has already achieved 98% broadband coverage even in small cities as well as rural areas
(Kim & Santiago, 2005) and high broadband penetration rate (75%) across the country
(Ministry of Public Administrations and Security [MOPAS], 2009). Still, government
support continues to provide the training and maintenance of online social networks in
rural communities. Thus, the Korean case of INVIL provides a unique opportunity to

examine what happens after the rural broadband gap is addressed systematically.

Since infrastructure penetration in Korea reached maturity, closing the rural-
urban broadband adoption rate is no longer a primary issue (Korea Local Information
Research & Development Institute [KLID], 2008). The new question becomes: how is
public investment in ICT used to enhance the viability of rural areas? This question is
worth noting since Korean rural areas are suffering from economic decline and rural
exodus (Kim, 2003), which is similar to how American rural areas are suffering (Galston
& Baehler, 1995).

Social capital is a signiﬁcant determinant of sustainability of rural development
initiatives, and ICT serves an important role in enhancing social capital of communities
(Simpson, 2005). Yet, the social beneﬁts of the INVIL project are as yet unknown
(KLID, 2008). Thus, the current study explored the impact of government support of
utilization of ICT infrastructure in rural communities. What is the impact of the INVIL
project on social capital of rural areas? Why a public investment is still needed, when
ICT infrastructure is saturated? In what manner, can INVIL help preserve the fabric of
rural communities?

The current study examined the social impacts of the INVIL project from three
perspectives. First, from the perspective of social cognitive theory (Bandura, 1986), the
study examined the inﬂuence of INVIL on Internet self-efﬁcacy and outcome
expectations, which are major indicators in overcoming the digital divide through
sustainable broadband adoption (Hoffman & Novak, 1998; LaRose, Gregg, Strover,
Straubhaar, & Carpenter, 2007). Second, as INVIL has emphasized online social
networks of local residents, its effect on social capital was investigated. Speciﬁcally, its

effects on online interaction and real-life community attachment were examined. Finally,

the impact of IN VIL on community satisfaction and intention to stay which are regarded
as crucial for sustainability of rural areas were investigated. As rural areas are suffering
from the economical decline and rural exodus, this question is closely related with
viability of local community. By examining the three aspects of social impacts, the
current study aims to examine implications for a future public investment in closing the

digital divide.

OVERVIEW OF INVIL

Since its implementation in 2001, the INVIL project has aimed to 1) construct
broadband infrastructure in inforrnationally disadvantaged areas, 2) build content-rich
local websites, 3) encourage community members to use information technology in their
daily lives, and 4) increase the long term viability of local communities through building
an online community and improving the local economy (MOPAS, 2009).

At the early stage of the IN VIL project, the government mainly focused on the
former two objectives to close the infrastructure gap between rural and urban areas. Fiber
optic backbone networks connected each village and 10M bps asymmetric digital
subscriber lines (ADSL) linked each household. As a result, the Internet penetration rate
for participating communities (65%) was signiﬁcantly higher than that of non-
participating communities (40%) (Korea Association of Local Informatization [KALI],
2006). As of January 2008, the INVIL project completed building local websites for a
total of 358 participating villages.

In order for a rural village to beneﬁt from the INVIL project, the village has to
apply to be considered as participant village, clarifying their aims and plans to build the
community’s ties and boom the economy through the network infrastructure and village
websites. The cases of fulﬁlling the criteria index formed by government body in charge
at competing level are likely to be accepted. According to main bodies in charge, the
village selection criterion is the following. Farming and ﬁshing villages has yet to
develop Internet and informatization infrastructure. Villages should be able to generate

income by making use of local specialties and experience tourism. Finally, village

residents must present strong will to conduct self-operation volition to carry on following
construction (MOPAS, 2009).

Currently, the INVIL project focuses on the latter two goals. To increase local
residents’ involvement, the government employed program managers for each village,
who not only manage local websites and teach computer skills to local residents but also
organize online communities. With the effort of local program managers, the number of

memberships on the INVIL website (http://www.invilorg) increased by 64% from 2005

 

to 2007. At the same time, the number of forums and posts increased by 88% and 38%,
respectively (KALI, 2006). Along with this active online participation, the e-commerce
system on the INVIL website contributed to local economies. From 2005 to 2007, the
sales record of specialty goods and tour programs increased by 900% and 90%,
respectively (KALI, 2006). Considering positive collateral effects such as online
promotions of local specialties and tourism, the IN VIL project has signiﬁcantly
contributed to enhanced economic viability of participating villages.

The results of the INVIL project have been promising. According to a survey
conducted by MOPAS, 74.1% of the participants responded that the project was helpful
in resolving the digital divide issue and 62.4% agreed that it had enhanced the viability of
their local community. Two-thirds of participants (65.7%) agreed that the INVIL project
was conducive to local economic growth. Regarding the outlook of e-commerce, 62.8%
thought that revenue would increase in the near future (KALI, 2006). Along with these
positive results, the INVIL project was acknowledged by the 2006 World e-Gov Forum

as a notable case of closing the digital divide.

LITERATURE REVIEW

Closing the digital divide and IN VIL

The digital divide refers to “the gap between those who have access to digital
technologies and those who do not” (Hargittai, 2003, p. 2). In terms of the access and
usage of ICT, the digital divide has diverse dimensions such as “quality of equipment,
autonomy of use, the presence of social support networks, experience and online skill”
among the different segments of the populace (Hargittai, 2003, p. 3). The digital divide
research has focused on the relationship between demographics and the digital divide.
Demographics are reported to have a greater inﬂuence on broadband adoption than the
service availability by public investment (Horrigan, 2009; Government Accounting
Ofﬁce [GAO], 2006).

Seeking answers to the question “is demography destiny?” (LaRose, Gregg,
Strover, Straubhaar, & Inagaki, 2008, p. 5), empirical studies examined mediating factors
such as education and ethnicity. By comparing different ethnic groups in the US,
Hoffman and Novak (1998) found that education had helped to transform Internet access
into usage. Also, Hargittai (2003) suggested that proper policy should be put into effect to
strengthen the users’ beneﬁts not only by improving access to ICT but also by investing
in training. Moreover, broadband adoption was found to be enhanced by external stimuli
such as government’s investment in broadband service and public education efforts
aimed at perceptions of broadband service (LaRose et al., 2010).

The INVIL project was originally aimed to close the digital divide between rural

and urban areas in terms of Internet accessibility. However, with the saturation of

broadband, the IN VIL project is now turning its focus to the creation of user beneﬁts,
such as improving economic viability and strengthening online social networks.
Regarding this, in terms of the digital divide, the current study examined “what happened
after broadband saturation.”
Internet Self-Efﬁcacy and Outcome Expectations

On the premise that demographic characteristics do not necessarily lead to
signiﬁcant differences in user behavior, social cognitive variables have received attention
as indicators in overcoming the digital divide (Eastin & Larose, 2000). Social cognitive
theory (SCT) has explained the possible factors of information technology adoption in
rural areas (LaRose et al., 2008). Social cognitive variables were viewed as factors to
overcome the Internet paradox (Kraut, Patterson, Kiesler, Mukhopadhyay & Scherlis,
1998) which addressed the negative effect of Internet on social involvement and
psychological well-being (LaRose, Eastin & Gregg, 2001). LaRose et a1. (2008) claimed
that Internet self-efﬁcacy enabled individual users with few social ties to seek social
support online.

Social cognitive theory (Bandura, 1986) proposes that self-efﬁcacy and outcome
expectations are associated with human behavior. Self-efﬁcacy refers to “people’s
judgments of their capabilities to organize and execute courses of action required to
achieve designated types of performances” (Bandura, 1986, p. 391). Individuals
cognitively process information concerning their ability and regulate their choice
behavior and exert effort accordingly (Bandura, 1977).

Internet self-efﬁcacy can be constructed as the belief in one's capabilities to

organize and execute courses of Internet actions needed to produce given attainments

(Eastin & LaRose, 2000). Internet self-efﬁcacy has strong ties with other relevant factors
such as prior Internet experience, outcome expectancies, and Internet use (Eastin &
LaRose, 2000). Previous studies found that the level of cognitive outcome expectations is
an antecedent factor to achieve a successful outcome. Expected outcomes of Internet
usage predict Internet use (LaRose et al., 2001). Outcome expectations are deemed as
indicators to close the digital divide between rural and urban areas (Eastin & LaRose,
2000). Expected outcomes of broadband usage were explored as factors to increase
broadband adoption intentions (LaRose et al., 2007), to encourage purchases online
(Vijayasarathy, 2004), try new e-services (Hsu & Chiu, 2004), and to motivate
engagement in web-based instruction (Joo, Bong & Choi, 2006). The ﬁndings indicated
that strong Internet self-efﬁcacy was related to high levels of outcome expectations, thus,
mediating the behavioral intention. Prior experience encouraged by behavioral intentions
in turn would incur higher expected outcomes, recurrently affecting Internet self-efﬁcacy.
Considering that INVIL supports diverse programs to motivate rural residents’
Internet usage the current study aimed to investigate impact of the IN VIL project on rural
residents’ Internet-self efﬁcacy and the expected social outcomes. Training programs and
maintenance of village websites are also provided in order to maximize the utilization of
infrastructure. Further attention is paid to promoting village websites to achieve
community viability through active online interaction. Taken together, from the social
cognitive perspective, it is likely that the IN VIL project has contributed to rural residents’
usage, Internet self-efﬁcacy and expected social outcomes. This leads to the following

questions:

RQla: What is the relationship of the INVIL project with the degree of rural
residents’ Internet self-efﬁcacy?

Rle: What is the relationship of the INVIL project with the degree of rural
residents’ expected social outcome?
Social Capital and IN VIL

To examine the social beneﬁt of the INVIL project, social capital framework is
employed as one of the major theoretical frameworks for this study. Social capital
framework claims that social networks have value (Jacobs, 1960). Social capital can be
formed from various aspects of social engagement and result in enhancing community
ties and bonds. Putnam (2000) claimed that social capital contributes to the entire society
by enabling political and social participation to ﬂourish. Besides the altruistic dimension
of social capital in which Putnam coined the term, social capital can be termed as
pertaining to a “shared interest” within economically engaged circles (Salisbury, 1969)
such as membership in social networks (Portes, 1998). At the individual level, social
capital should be distinguished from an altruistic dimension of community involvement.
For example, people who appear to be friendly neighbors could be business partners or
stake-holders within the same economic community as demonstrated in the INVIL
project. This means social capital can involve a self-serving dimension of community
members’ attachment that is associated with the desire for high quality of one’s living
condition. In this regard, the current study focused on the social networks and shared
interest aimed by the IN VIL project and its relationship with the degree of online
interaction and real-life community attachment of rural residents.

Online interaction and Community attachment

Online interaction refers to social use of the Internet. Recent study about
facebook (Ellison, Lampe & Steinﬁeld, 2007) indicated that online social networking
might be linked both to increases and decreases in social capital. Through online
interaction, rural residents can be connected with their friends or relatives beyond their
local community and link their online and offline relationship together. Furthermore,
online interaction can mediate real-life community attachment through online interaction.
In this sense, online interaction means community-oriented-online engagement as
opposed to the mere accumulated time spent online. That is, the more time given to
online activity does not necessarily bring about online interaction and community ties. In
this respect, it was found that the Internet has no effect on social capital as online
interaction is combined with the real life activities (Wellman, Haase, Witte, & Hampton,
2001)

However, in general, recent attention has turned towards the positive role of
online social networking. In this regard, the current study explored the interplay between
social networking based on online interaction and community attachment. Community
attachment was constructed by employing the concept of bonding and bridging social
capital. According to Putnam (2000), bonding capital means a social connection within
common groups whereas bridging capital means a social linkage across diverse
characters of groups, which have an incremental effect to each other.

The long term effect of online interaction was found to be positive on social
involvement and psychological well-being in contrast to the negative effect previously
found, also known as the “Internet paradox” (Kraut et al., 2002). Also, it was found that

online interaction has a signiﬁcant effect on increased social contact, community

10

attachment and participation (Kavanaugh, Carroll, Rosson, Zin, & Reese, 2005). In a
way, online interaction facilitates community attachment and psychological well-being,
facilitating alternative access to a community (Ellison et al., 2007). This beneﬁt may be
given especially to those with low self-esteem and low life satisfaction (Ellison et al.,
2007), also to those who lack interaction with friends and neighbors (Bargh & McKenna,
2004). Moreover, it is noted that certain aspects of online interaction provide optimal
conditions to motivate self-disclosure more than face-to-face communication (Bargh,
McKenna, & Fitzsimons, 2002). Thus, the degree to which online interaction through
INVIL was related to real-life community attachment came into focus in this study.

RQ2a: What is the relationship of the INVIL project with the degree of rural
residents’ online interaction?

RQ2b: What is the relationship of the IN VIL project with the degree of rural
residents’ community attachment?
Community Satisfaction and Intention to stay

Rural exodus is a critical issue across the globe. American rural areas are

suffering from an economical decline and a rural exodus (Galston & Baehler, 1995). This
is likely the case for Korean society as well. To be speciﬁc, the 10-30 year old age group,
which is considered to be the “effective labor forces of society,” is dramatically
decreasing in rural areas (Kim, 2003) , which deﬁnes the rural exodus. However, there
have been consistent ﬁndings about the promising factors for rural economic viability and
the inﬂux of new residents, among one of which Information Technology counts (Galston

& Baehler, 1995; Parker, 2000).

11

Previous studies have focused on both the intention to stay and psychological
attachment. Putnam (2000) viewed outmigration in an attempt to gain job opportunities
may explain the decreased social capital in the US. Psychological attachment is reﬂected
in the degree of satisfaction that comes with community involvement, helping to reduce
the gap between rural and urban areas in terms of overall life quality.

The relationship between Internet usage and migration intentions remains
arguable. It has been found that the Internet eases the burden of looking for better living
conditions (Wellman et al., 2001 ). Also, heavy use of the Internet decreases community
commitment (Wellman et al., 2001). For example, computers placed in rural libraries
(Egan, 2002) were reported as the possible causes for outmigration, helping library
patrons gain city jobs online. Also, online communication with users outside of the
community would downgrade the quality of the services and goods provided by rural
suppliers and employers, which is detrimental to the sustainability of the rural
communities (Rowley & Porterﬁeld, 1993).

In another light, online interactions result in social integration, one of the
dimensions of social well-being (Smith, Krannich, & Hunter, 2001). As an indicator of
social well-being, community satisfaction may be subject to the availability of
entertainment, education, and public services (Smith et al., 2001); also, rural community
self-development efforts might lead to increased social capital (Flora, Sharp, Newlong &
Flora, 1997). In a longitudinal study conducted in rural American communities, social
uses of the Internet were found to be community satisfaction and attachment, leading to
less intention to relocate from their rural communities (LaRose et al., 2008). Thus, it is

plausible that a government sponsored project, such as INVIL that promoted social

12

networking could be a predictor of enhanced community attachment. Community
attachment, community satisfaction and intention to stay were constructed as major
variables affecting relocation, because enhanced satisfaction and intention to stay may
lead to extended residency. Thus, the research questions are as follows:

RQ3a: What is the relationship of the INVIL project on the degree of rural
residents’ community satisfaction?

RQ3b: What is the relationship of the INVIL project on the degree of rural

residents’ intention to stay?

13

METHOD

Participants

Two hundred and nine participants were recruited from 14 randomly selected
rural towns listed on the INVIL website in Korea. Among participants, 63.2% lived in
villages designated as IN VIL, while 36.8% lived in non-information villages. The sample
consisted of almost identical numbers of male (N = 99) and female (N = 100)
participants. Participant’s average age was 44.71 (SD = 12.50). On average, participants
had been living in their town for 25.38 years (SD = 2.85), working as farmers (24.29%)
or housewives (23.72%). More than half of participants did not have college education
(21.2% some high school, 38.4% high school graduates). Most participants had family
income of US$ 8,500-17,000 (27.6%) or USS l7,000-30,000 (22.9%).
Procedure

The current study used a cluster sampling method for participant recruitment. The
INVIL website (http://www.invil.org/) provided a list of 358 rural villages participating
in the IN VIL project and supported diverse forms of online social clubs of rural residents.
The researchers randomly selected 14 sample villages among 358 villages listed on the
INVIL website. INVIL residents were recruited from the 14 selected villages. Non-
INVIL residents were recruited by drawing IN VIL site members who reside in the same
administrative district with the selected 14 villages. Since INVIL website is a kind of
meta site, aggregating all the INVIL websites as well as providing online social clubs for
ordinary rural Korean residents. Thus, both INVIL and Non-INVIL residents in rural

areas are included as members of each websites in INVIL sites. Even if non-INVIL and

14

IN VIL residents belong to the same administrative district they are separate from each
other according to whether they are the members of INVIL participant villages which call
certain areas in the selected administrative district.

The INVIL site also provided each village/club members’ contact information.
Thus, researchers drew 400 contact information from the selected villages. Emails were
sent to the drawn addresses, describing the purpose of the study to the community
organizers, church members, and social club members listed on the website of sample
villages. If participants’ phone numbers were available on the website, the researchers
encouraged their participation. Once they have agreed to participate in the survey by
replying to the researcher’s email, participants would be notiﬁed of the time and location
at which the survey will be conducted.

The researcher then visited the selected communities and conducted the survey
one-site, at the appointed place. Participants had done so by a self—reported written
survey. Participants signed the consent form prior to taking the survey, and were thanked
upon the completion for their input.

In this way, 14 villages succeed in covering each and every province of Korea and
all the participants are recruited through IN VIL sites. It turned out 209 out of 400 actually
participated in the survey which showed a 52% participation rate
Measurement

Among demographical questionnaire age and whether or not INVIL residents
were coded into nominal scale. Age and income used ratio scale. Degree of education

was responded by 5-point ordinal scales.

15

The questionnaire used S-point scales ranging from strongly agree (scored 5) to
strongly disagree (scored 1) and negatively worded items were reﬂected. The responses
to multi-item indices were averaged across the number of items. Questionnaires were
originally written in English, and were carefully translated into Korean by a bilingual
researcher. Each scale showed evidence of a good ﬁt for a one-factor model and
satisfactory reliability.

Internet Self-Eﬂicacy. Seven items were drawn from Eastin & LaRose (2000).
With a maximum-likelihood estimation procedure, a one factor model showed an
acceptable ﬁt, NF I (normed ﬁt index) = .92; IFI (incremental ﬁt index) = .94; CFI
(comparative ﬁt index) = .94; SRMR (standardized root mean residual) = .05. The
reliability (Cronbach’s alpha) was a = .92.

Social Outcome Expectations of Internet Use. Five items were selected from
LaRose et al. (2007). A one-factor solution yielded a good ﬁt, NFI = .94; IF I = .95; CF I =
.95; SRMR = .04. The reliability was a = .88.

Online Interaction. Five items were drawn from LaRose et al.’s survey
questionnaire on socializing online (2008). A one-factor solution yielded a good ﬁt, NFI
= .98; IFI = .98; CFI = .98; SRMR = .03. The reliability was a = .92.

Community Attachment. Seven items were adopted from LaRose et al. (2008). A
one factor model showed a good ﬁt, NFI = .94; IFI = .95; CFI = .95; SRMR = .04. The
reliability was a = .92.

Intention to Stay. Five items were adopted from LaRose et al. (2008). A one
factor model showed a good ﬁt, NF I = .97; IFI = .98; CFI = .98; SRMR = .04. The

reliability was a = .86.

16

Community Satisfaction. Six items were scale adopted from LaRose et al. (2008).
A one factor model yielded a good ﬁt, NFI = .94; IFI = .95; CFI = .95; SRMR = .04. The
reliability was a = .88.
Data Analysis

Independent sample t-tests, Pearson product-moment correlations, and point~
biserial correlations were analyzed using SPSS, Inc. (2007) version 16.0. A conﬁrmatory
factor analysis was conducted using the AMOS-package (Arbuckle, 2006). Prior to the
analysis, outliers were eliminated and missing data were imputed using maximum

likelihood estimates.

17

RESULTS
Demographic Differences

Prior to test the effect of the INVIL project, the demographic differences between
INVIL residents and non-INVIL residents were examined. The results showed a
signiﬁcant difference in age, I (194) = 4.82, p < .001. INVIL residents (M = 47.72, SD =
11.95) were older than non-INVIL residents (M = 39.19, SD = 11.64). In terms of the
length of residency, INV IL residents (M = 29.16 years, SD = 17.37) had lived in their
villages longer than non-INVIL residents (M = 18.43, SD = 14.24), t (194) = 4.39, p <
.001. The differences were not signiﬁcant for income, t (190) = 1.32, p = .19, or
education, t (196) = 0.67, p = .50.

Correlation Analysis

Table 1 shows the correlations among variables after controlling for demographic
variables (gender, age, family income, education, and the length of residency). Table 2
shows a groups statistics about variables examined among INVIL and non-INVIL
participants and Table 3 demonstrated t-test analysis.

INVIL was not correlated with Internet usage, r = -.03, p = .75. There was no
signiﬁcant difference between the residents in IN VIL (M = 3.31 hours per day, SD =
2.78) and non-INVIL residents (M = 3.41, SD = 2.26).

For social cognitive variables (RQla and Rle), INVIL was not associated with
Internet self-efﬁcacy (r = .06, p = .44). Internet self-efﬁcacy of INVIL residents (M =
2.61 , SD = 0.95) was not different from that of non-INVIL residents (M = 2.66, SD =
0.96); t(l79)=-.495, p = .621. In contrast, INVIL was signiﬁcantly and positively related

with social outcome expectations of Internet use (r = .39, p < .001). INVIL residents (M

18

= 3.05, SD = 0.88) reported higher social outcome expectations than non-INVIL residents
(M= 2.12, SD = 0.77); t (182)=6.532,p < .001.

For social capital variables (RQZa and RQ2b), INVIL was associated both with
online interaction (r = .21, p = .005) and community attachment (r = .28, p < .001).
Online interaction was higher for INVIL residents (M = 3.14, SD = 1.03) than non-INVIL
residents (M = 2.75, SD = 0.99); t (178)=2.31,p < .05. Community attachment was also
higher for INVIL residents (M = 3.60, SD = 0.89) than for non-INVIL residents (M =
2.82, SD = 0.87); t (201)=5.98,p < .001.

For community satisfaction and intention to stay (RQ3a and RQ3b), INVIL was
signiﬁcantly associated with intention to stay, r = .28, p < .001. INVIL residents (M =
3.80, SD = 0.92) reported higher intention to stay than non-INVIL residents (M = 3.05,
SD = 0.77); t(200)=.80, p =.43. INVIL was not signiﬁcantly correlated with community
satisfaction (r = .02, p = .81). There was no signiﬁcant difference in the degree of
community satisfaction between INVIL residents (M = 2.42, SD = 0.83) and non-INVIL

residents (M= 2.33, SD = 0.72); t (l78)=2.3l, p < .05

19

Table 1. Correlation Matrix of Variables Controlling for Demographics

 

Variable 1 2 3 4 5 6 7 8 M SD
1.INVIL 1.00 0.66 0.47
2. Internet .02 1.00 3.36 2.63

usage
3.Internet .06 .32** .92 2.63 0.97

self-efﬁcacy
4'50“” .39** .26** .54** .88 2.75 0.98
outcome

expectations
5.0nline .21** .26** .73** .62** .92 3.04 1.03
interaction
6. Community .28** .13 .21** .57** .37** .92 3.37 0.96

attachment

7. Intention

.29** .07 .10 .38** .30** .60** .86 3.58 0.92
tostay

8. Community

. . .02 .01 .27** .18” .12 .18* .11 .88 2.41 0.80
satisfaction

**. Correlation is signiﬁcant at the 0.01 level (2-tailed).

*. Correlation is signiﬁcant at the 0.05 level (2-tailed).

20

Table 2. t-Test Analysis

Internet use per
day

Internet self-
efﬁcacy

Social outcome
expectations

Online
interaction

Community
attachment

Intention to stay

Community
satisfaction

 

INVIL Non-INVIL Statistics

n M SD n M SD t P
126 3.33 2.84 53 3.51 2.70 0.39 .70
122 2.60 0.98 59 2.68 1.09 0.50 .62
126 3.06 0.90 58 2.14 0.86 -6.53 .00
121 3.15 1.07 59 2.75 1.19 -2.31 .22
130 3.60 0.90 73 2.82 0.89 -5.98 .00
129 3.08 0.93 73 3.04 0.79 -5.89 .00
129 2.42 0.83 73 2.33 0.73 -0.80 .43

21

DISCUSSION

The current study investigated the impact of the INVIL project on 1) social
cognitive variables, 2) social capital, and 3) community attachment. The effect of Internet
usage was tested prior to the main analyses. The results showed that INVIL was not
correlated with Internet usage. This ﬁnding diverged from previous studies conducted in
the United States (e.g., LaRose et al., 2008) which showed a signiﬁcant increase in
Internet usage following public investment. The difference may arise from that
broadband infrastructure construction already completed in rural areas in Korea. Non-
INVIL residents were also well-connected to the Internet, thus, the difference in usage
would not be signiﬁcant.

Rather than closing the infrastructure gap, the INVIL project has had a more
signiﬁcant effect on the phase of rural residents Internet usage, speciﬁcally, in terms of
social networking online given that its function mainly has centered on providing online
community features. Thus, examining social cognitive variables is a critical point of the
current study. The results showed that INVIL was signiﬁcantly associated with social
outcome expectations. It is possible that online community activities of IN VIL over a
long period of time have contributed to higher social outcome expectations of local
residents. This implication also can be supported by a previous study of Eastin & LaRose
(2000) that claimed formation of positive outcome expectations in social cognitive terms
needs enough time after self-efﬁcacy beliefs are established.

However, the correlation between INVIL and Internet self-efﬁcacy was not

signiﬁcant. The reason for the low correlation between INVIL and Internet self—efﬁcacy

22

might be explained in a way that low correlation between INVIL and Internet usage can
be accounted. That is, with diverse phase and purposes of Internet usage of rural
residents, the online social networking supported by the government grants does not
necessarily create Internet self-efﬁcacy that might be established from all sorts of Internet
usage.

Internet self—efﬁcacy and social outcome expectations were correlated to each
other, consistent with the prediction of social cognitive theory. Outcome expectations
were partly determined by self-efﬁcacy beliefs; the outcomes individuals expect depend
on their judgments of how well they will be able to perform in given situations (Bandura,
1986). For example, individuals apprehensive of their computer skills might expect
disappointment as the outcome of their usage, while individuals competent in computer
skills might anticipate convenience. Hence, social outcome expectations depend on the
adequacy of individuals’ performances to some extent. This emphasizes the need to
improve Internet self-efﬁcacy of local residents through more effective computer
training.

In terms of social capital variables, the current results showed that INVIL was
positively associated with online interaction and community attachment. This ﬁnding
indicated the use of INVIL as a social network and was consistent with previous studies
that showed the positive effect of online interaction on community involvement and
social capital (Hampton & Wellman, 2003; Kavanaugh et al., 2005).

At the same time, online interaction and community attachment were positively
associated. This ﬁnding was consistent with Hampton et al.’s (2003) study that suggested

that the Internet did not weaken community by disengaging people away from the

23

neighborhood, or transform community by creating new forms of online relationship.
Instead, INVIL enhanced existing relationships by adding a new means of extending
relationships with neighbors. It might be explained that the online community supported
by a government grant is a geographically-based one. Moreover, direct government
support given to the personnel in charge of the INVIL website management enables
online communities to function as a venue for viable online-ofﬂine communication
among village residents. These features distinguish the INVIL project from other
conventional social networking sites. INVIL may provide more effective online tools to
strengthen “the fabric of real-life community.”

In terms of community attachment, the results indicated that INVIL was
positively related with residents’ intention to stay. The ﬁnding suggested that intention to
stay might be predicted by the intensive online social networking.

Interestingly enough, community satisfaction was neither related with INVIL nor
intention to stay. One of the possible explanations is that the functions offered by INVIL
merely focus on online social networking. Considering that there are diverse purposes of
Internet usage might have effect on life quality of rural residents, online social
networking does not necessarily bring about enhanced satisfaction with community life.
Also, it should be noted that INVIL does not provide any other available online resources
such as entertainment resources and health/education services connected to life in rural
community, which might be indicators to community satisfaction.

It is notable that online interaction was positively associated with both community
satisfaction and the intention to stay. This ﬁnding is inconsistent with LaRose et al.’s

(2008) study that showed a positive relationship between social capital and relocation

24

intention. It appeared that exposure to the outside world on the Internet and creating new
social ties online stimulated outmigration from rural communities (LaRose et al., 2008).
The difference might arise from the characteristic of social networks created by INVIL.
INVIL has unique features in that it combines online market place and online social
networking which is based on same geographic area and real-life community. Through
those features the INVIL project helped in creating “shared interest” among village
members which might increase the intention to stay, instead of stimulating outmigration
intention. In this sense, INV IL has a potential to encourage local residents to act on their
common interests and concerns in a systematic and sustainable manner, and to actively

cope with economical decline and rural exodus.

25

LIMITATIONS AND FUTURE RESEARCH

Internet usage had been explored as a signiﬁcant factor in determining social
cognitive variables such as Internet self-efﬁcacy, social outcome expectations, online
interaction (LaRose et. al, 2001). Also, the current study indicates that Internet usage and
Internet self-efﬁcacy have a causal relationship with online interaction and community
attachment. However, INVIL residents did not show higher degree of Internet usage and
Internet self-efﬁcacy than non-INVIL residents. So, one may not be able to jump to the
conclusion that INVIL might have encouraged more Internet usage, and thus, led to more
social networking among rural residents.

In this regards, the future research should explore which of the attributes that
IN VIL offers the participants village to create social capital such as high degree of online
interaction and community attachment. As long as this question remains, it is arguable
that the beneﬁts of INVIL would come from the online social networking. That is, it
could be something else such as simply strong ties of participant villages irrelevant to the
online community that the INVIL project supports. Other possibility is that INVIL
residents may have strong ties and be encouraged to bond online, which hinge on the
economic beneﬁts of selling their commodities and specialties online.

To address the limitation of this study further study should be conducted to
examine in what way INVIL help increase social capital in rural areas. To be speciﬁc,
further research should explore whether the factor of high degree of social capital shown
in the IN VIL participants comes from e-commerce initiative or social networking

initiative. In that way it could be expected to examine and embody the source and the

26

phase of social capital induced by government driven project in rural areas in a more

speciﬁc manner.

27

CONCLUSION

Current study implicated the online social network services supported by rural
ICT policy is related to social capital. This result might provide an answer to the question
that whether or not ICT investment in rural areas should be continued even when access
does not matter. Since INVIL residents demonstrated high community attachment and
intention to stay it is implicated that community attachment might be predicted by
geographically based online social networking.

In this regards, it is proposed that government investment in ICT should focus on
the utilization of existing infrastructure, pertaining to social capital in rural areas. Even
after the access and the adoption gap is closed continuous public investment is still
needed to be instituted for community development in rural areas.

The current study also provides insight to the global society which suffers from a
rural exodus in a similar phase. As access and adoption became more available in rural
and developing areas, the INVIL case demonstrated a portrait about what should be

sought and done after broadband adoption with regards to ICT policy.

28

APPENDIX

Research Participant Information and Consent Form

STUDY TITLE: Rural Life in the Information age

I am doing a study to verify the correlation among the intensity of intemet use and the
degree of community involvement and life satisfaction in rural areas as an independent study this
semester. The purpose of the survey is to know how your intemet use and government support of
Internet technology and education in your community affects your family and your community.
This study need will beneﬁt your community in that it would help to make appropriate and right
government policy of investing in internet infra to better off rural places. This study would also
be beneﬁcial in ﬁnding out how a business is able to communicate with their clients via the web
and what can the community/city do to help the business owners.

To verify the hypothesis of this study by measuring how rural population use Internet and
feel about their life, research on rural residents should be involved. If you are at least 18 years
old, you are eligible to participate in the survey.

The survey involves answering some general demographics questions and some questions
about your opinions toward your local community. The survey takes about 15 minutes or so to
complete. Your responses will be completely anonymous. The data I collect will be analyzed at
the group level only. You do not have to answer any question you’d rather not answer.

If you agree to complete the survey, please do NOT write your name on it. After you
ﬁnish ﬁlling it out, please put the survey sheets in the box. By ﬁlling out the survey you are
consenting to participate. The risks associated with your participation are minimal and are limited
to the release of private information you supply in completing the survey. Your privacy will be
protected to the maximum extent allowable by law. Your answers are completely conﬁdential and

your name will not be linked to the data in any way. Your participation is completely voluntary,

29

you may choose not to participate at all, or you may refuse to answer certain questions or
discontinue your participation at any time without consequence.

The researcher of this study, Kqu in Shim can answer questions about your rights as a
volunteer participant in this project. She can be reached at 81-10-9998-1565, 1-517-899-8976.
Primary investigator of this study is Dr. Robert Larose, who is a professor in Michigan State
University, you can reach him through email larose@msu.edu.

If you have any questions or concerns about your role and rights as a research participant,
would like to obtain information or offer input, or would like to register a complaint about this
research study, you may contact, anonymously if you wish, Michigan State University Human
Research Protection Program at 1-517-355-2180, FAX l-517-432—4503, or e-mail irb@msu.edu,

or regular mail at: 202 Olds Hall, MSU, East Lansing, MI 48824, United States of America.

If you agree to participate in this study please reply me by email at
shimkyuj@msu.edu, m cell phone number is 81-10-9998-1565. The results of my project
will be available after August 22, 2009. If you would like a copy of the results of my
project or have any questions, please contact me. (82-10-9998-1565, 1-517-899-8976)

Please keep this for your records. Thank you for your participation.

I HAVE READ THE INFORMATION PROVIDED ABOVE (OR HAVE HAD
IT READ TO ME) AND HAD MY QUESTIONS ANSWERED TO MY
SATISFACTION. I VOLUNTARILY AGREE TO PARTICIPATE IN THIS STUDY.

SIGN HERE

 

DATE

 

3O

Questionnaire (English)

1. Is your community receiving beneﬁts from government policy of investment in
computer use in rural communities?

Yes

No
Don’t know

2. Is your business or job connected to the Internet?

Yes

No

Don’t know

3. Does your business or company or producers’ cooperative have a web site?

Yes

No
Don’t know

4. Is your company’s or business’ web site equipped to process purchases of your
products and service?

Yes

No

5. Do you have a computer at home?

Yes

No
6. Does your village have an Information Center in which anyone can receive
computer skills training program?

Yes

No
Don’t know

7. Have you ever participated in computer skills training program provided by
information center?

Yes => IF YES How many times? times
No

 

31

8. Do you have basic skills to use computer?

_ Yes (which ones? Please list the programs and applications you can
use via computer, e.g., e-mail, messenger, intemet, Word, PowerPoint,
Excel etc.) )

_ No

 

9. Do you currently use the Internet?

Yes (Continue to Question 10)
No (Skip to Question 20)

10. About how much time do you spend at home on the intemet in the typical
weekday? (ENTER 0 IF NONE)
HOURS MINUTES

11.About how much time do you spend at home on the intemet in the typical
weekend day?
HOURS MINUTES

12.The following are things people have told us they do on the Internet. How
frequently do you use the Internet to...

 

 

 

 

 

 

 

 

No. Item 5:52)] or Neutral ﬁezjgttly
1 Bank online 1 2 3 4 5
2 Purchase products 1 2 3 4 5
3 Read news 1 2 3 4 5
4 Work on my own blog or site 1 2 3 4 5
5 Sgglsépefsonnation on government 1 2 3 4 5
6 Seek information about health 1 2 3 4 5

 

 

 

13. Please tell us how much you agree or disagree with the following statements
about the Internet in your life.

32

 

 

Strongly Neutral Strongly

No. Item .
disagree agree

 

1 I feel conﬁdent using the Internet to gather

data. 1 2 3 4 5

 

2 I feel conﬁdent explaining why a task will
not run on the lntemet.*

 

I feel conﬁdent I know how to learn
advanced skills related to the Intemet.*

 

I feel conﬁdent understanding terms/words
relating to lntemet software.*

 

I know how to make new friends on the
Internet.*

 

I use the lntemet so much it interferes with
other activities.*

 

7 I get strong urges to be on the lntemet. 1 2 3 4 5

 

8 I know how to get help with my personal
problems through the Intemet.*

 

I have to struggle with myself to limit my
time online.

 

 

I am conﬁdent I can ﬁnd social support on

10 the Intemet.*

 

 

 

* Items used in the analysis for the lntemet self-efﬁcacy dimension

14.1ncluding email, instant messaging and social networking sites like Café or
C yworld, how often do you contact people from inside your local community
online?
_Never contact them
____Less than once a month
__At least once a month but less than weekly
___At least once a week but less than daily
__One or more times a day

15.Including email, instant messaging and social networking sites like C afé or
C yworld, how often do you contact people from outside your local community
online?
_Never contact them

33

 

__Less than once a month

_At least once a month but less than weekly
_At least once a week but less than daily
______One or more times a day

16.Including family and friends, how many people from your local community have
you been in contact with online in the past month? [ENTER 0 IF NONE]

TOTAL ONLINE CONTACTS WITH

 

 

LOCAL PEOPLE
17.How many of those are local people who run their own businesses [ENTER 0 IF
NONE]
CONTACTS WITH LOCAL BUSINESS
OWNERS

18. How much do you agree or disagree with the following statement about the
people online?

 

 

 

No. Item Strongly Neutral Strongly
disagree agree
Interacting with people online makes me
1 interested in things that happen outside of 1 2 3 4 5

my town.*

 

Interacting with people online makes me
want to try new things.*

 

Interacting with people online makes me feel
connected to the bigger picture.*

 

There is someone online I can turn to for
4 advice about making very important 1 2 3 4 5
decisions.*

 

The people I interact with online would put
their reputation on the line for me.*

 

If I needed an emergency loan of 500,000
Won, I know someone online I can turn to.

 

 

 

 

* Items used in the analysis for the social outcome expectations dimension

34

19.Thinking of your use of e-mail, instant messaging, village website or social
networking site (such as Café and C yworld) to what extent

 

 

 

 

No. Item Not at all Neutral A great
deal
1 Does your participation make you feel a part 1 2 3 4 5
of a commumty?*
2 Do you communicate with friends from your 1 2 3 4 5
local communrty?*
3 Do you communicate with friends in other 1 2 3 4 5

communities?*

 

Do you communicate with family from your
local community?“

 

 

Do you communicate with family in other
communities?*

 

 

 

* Items used in the analysis for the online interaction dimension

20.Please answer these questions even if you don’t use the lntemet so we can learn
why some people use it while others don’t. If you can’t answer one, just skip to

the next one. Using the lntemet I will...

 

No.

Item

Strongly Neutral Strongly
disagree agree

 

Improve my future prospects in life

1 2 3 4 5

 

 

 

 

 

 

 

 

 

 

2 Have my credit card number stolen 1 2 3 4 5
3 Find people like myself 1 2 3 4 5
4 Find cool new Web pages 1 2 3 4 5
5 Have fun 1 2 3 4 5
6 Find a way to pass the time 1 2 3 4 5
7 Spend money on things I don’t need 1 2 3 4 5
8 Save time shopping 1 2 3 4 5
9 Provide help to others 1 2 3 4 5
10 Get support from others 1 2 3 4 5

 

 

 

3S

 

 

 

 

 

 

 

 

 

 

 

11 Get up to date with new technology 1 3 5
12 Maintain a relationship I value 1 3 5
13 Find information about my local community 1 3 5
14 Find products I can’t get locally 1 3 5
15 Find a job in another area 1 3 5
16 Start a home business 1 3 5
17 Make a new friend in the local community 1 3 5
18 Make a new friend in another community 1 3 5

 

 

 

21.How many voluntary associations, such as clubs, churches, youth programs, and

any other community associations are you a member of?

ENTER NUMBER OF ORGANIZATIONS,

 

(ENTER 0 IF NONE)

22. Now think about issues in your community. How active are you in resolving

community problems? Over the past month, have you

 

No

Item

Yes

No

 

Spoken with a local politician

 

Talked to a person or group causing a problem in the

 

 

 

 

2 neighborhood

3 Attended a meeting of a neighborhood group about a
problem

4 Talked with a local religious leader

5 Gotten together with neighbors to do something about a

 

problem in the neighborhood

 

 

 

36

 

 

[Community attachment and intention to stay]

23.How much do you agree or disagree with each statement about your community?

 

 

No. Item Strongly Neutral Strongly
disagree agree
1 Ifeel I ampart ofit.* 1 2 3 4 5

 

I spend a lot of time participating in
activities there.*

 

I come into contact with new people all the
time.*

 

I am willing to spend time to support
4 . . . *
actrvrtles there.

 

I can count on my neighbors to run errands
for me."‘

 

6 The longer I live in this town, the more I
feel that I belong.*

 

It makes no difference to me whether my
7 job or business is here or in another 1 2 3 4 5
community.

 

If I was in trouble, most people in this
8 community would go out of their way to 1 2 3 4 5
help me.*

 

9 I would never consider leaving here.** 1 2 3 4 5

 

If I had to move away from this community
10 for some reason, I would be very sorry to 1 2 3 4 5
leave.”

 

I would really like to leave this community

11 if I had the opportunity.

 

12 Our community has seen better days.M 1 2 3 4 S

 

 

Our community has a lot of future

13 potential.* *

 

 

 

37

 

 

 

Our community’s future depends on the

14 . .
efforts of Its resrdents.“

 

The solutions to our community’s problems

15 will have to come from outside.

 

 

 

 

* Items used in the analysis for the community attachment dimension
“Items used in the analysis for the intention to stay dimension

[Community satisfaction]

24. Please keep your community in mind and circle a number between 1 (Very
dissatisﬁed) and 5 (Very satisﬁed) in each row. How satisﬁed or dissatisﬁed are

 

 

 

 

 

 

 

 

 

 

 

you with. ..
Very Very

No. Item dissatisﬁed Neutral satisﬁed
1 Living in my community. 1 2 3 4 5
2 My opportunities for further education. I 2 3 4 5
3 The recreatronal servrces and opportunrtres 1 2 3 4 5

avarlable.*
4 The quality of streets and roads.* 1 2 3 4 5
5 The availability of lntemet services.* 1 2 3 4 5
6 The medical services. 1 2 3 4 5
7 The shopping facilities in my community.* 1 2 3 4 5
8 My employment opportunities.* 1 2 3 4 5
9 My opportunities to partlcrpate 1n the local 1 2 3 4 5

government.
10 The programs for youth in my community.* 1 2 3 4 5

 

 

 

 

 

38

 

11

My cultural opportunities.

 

12

 

Educational opportunities for young
people.*

 

 

 

*ltems used in the analysis

25.The following are possibilities you may be considering. How likely is each one

next year? If you are doing it or planning it already, consider how likely or
unlikely you are to carry through on it in the next year. In the next year I will. . ..

 

 

 

 

 

 

 

 

 

 

 

No. Item :53;er Neutral Very likely
1 Move out of village 1 3 5
2 Move to another home in urban area 1 3 5
3 Start a small business 1 3 5
4 Work from home using the lntemet 1 3 5
5 Run a business from my home 1 3 5
6 Look for employment in another area 1 3 S
7 Complete a degree or training program 1 3 5
8 Have a member of my family move away 1 3 5
9 Install a wireless computer network at home 1 3 5

 

 

 

39

 

 

[Personal income and other information]

26.What is your sex?

Male
Female

27. What year were you born? 19
28. What is your family’s total annual household income before taxes?

_Under 10,000,000 Won
__10,000,000 to 19,999,000 Won
_20,000,000 to 34,999,000 Won
__35,000,000 to 49,999,000 Won
_50,000,000 to 74,999,000 Won
____75,000,000 to 99,999,000 Won
_100,000,000 Won or more

29. What is the highest level of education you have completed?
__ Less than high school degree
_ High school degree
__ Some college
_ College graduate
__ Advanced graduate degree

30. How long have you lived in this area? YEARS MONTHS

31.What is your job and job title?

 

32.Do you have any children enrolled in local high schools?

Yes
No

33. Did you attend high school in the local community yourself?

Yes
No

Thank you.

40

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