3D Communities as Platforms for Developing Social Capital
Claudia Loebbecke
1
, Paolo Depaoli
2
and Marco De Marco
3
1
Dept. of Media and Technology Management, University of Cologne, Pohligstr. 1, Cologne, Germany
2
Department of Earth Science, Life and Environment, University of Urbino, Urbino, Italy
3
Department of Political Sciences, University Guglielmo Marconi, Rome, Italy
Keywords: Social Community, Social Capital, 3D, Empirical Analysis.
Abstract: 3D virtual communities, a particular form of platforms, have gained remarkable attention in theory and
practice. Similarly, the well established concept of social capital, which describes resources becoming
accessible and available through the connection and interaction between individuals on a platform, has
regained prominence with the boom of social media. In this study, we investigate the development of social
capital in 3D virtual communities. Adapting the model of Adler and Kwon (2002), we analyze the role of
motivation, ability, opportunity, and integration fir constituting social capital in 3D virtual communities.
Our empirical investigation conducted in 2008 and 2009 among users of two 3D virtual communities, one
networking platform and one online gaming platform, suggests that only motivation and ability are
generally important. We conclude that the sources of social capital depend on the specific type and user
audience of a 3D virtual community as well as on the sophistication of the available tools in the particular
3D environment and the cultural openness of the network.
1 INTRODUCTION
Facebook, YouTube, MySpace, Flickr are only some
of the communities present on the Internet these
days. The number of virtual communities in general,
and of 3D virtual communities in particular, which is
available to the regular Internet user is exploding.
Whereas some people in virtual spaces only come
together to have fun and do small talk, many join
virtual communities looking for different kinds of
help in their daily life. Purposefully or not, they
create social capital by interacting with others
online; the social capital in turn, just as other types
of capital, then may increase a person's productivity
(Becks et al., 2004).
In this paper, we investigate what drives the
development of social capital in 3D virtual
communities. To that end, the remainder of the
paper is structured as follows: In the next section,
we briefly outline the concept of 3D virtual
communities and describe two examples, Cyworld
(CW), which resembles more a networking platform,
and SecondLife (SL) appearing to be closer to an
online gaming platform. We then introduce the
concept of social capital. Subsequently, we develop
our research model adapted from Adler and Kwon
(2002). We present the approach and the results or
our empirical study. We discuss our results focusing
on their implications for theory and practice. At the
end, we summarize and provide some suggestions
for future research.
2 TERMS AND CONCEPTS
2.1 Virtual Community
The term 'virtual community' as a community of the
Internet is rather broad. According to Preece (2000)
an online community consists of socially interacting
people who come together in the com-munity for a
shared purpose. Policies determine daily life in the
community and all this is supported by computer
systems. Hagel and Armstrong (1997) argue that
people register for virtual com-munities and use
them because they are looking for a space that they
feel comfortable in and which gives them the chance
to meet other people. To them, interaction in a
virtual community is based on four basic needs:
interest, relationship, fantasy, and transaction. Lee et
al. (2003, p. 51) define a virtual community as "a
cyberspace supported by computer-based
information technology, centered upon
communication and interaction of participants to
227
Loebbecke C., Depaoli P. and De Marco M..
3D Communities as Platforms for Developing Social Capital.
DOI: 10.5220/0004050102270236
In Proceedings of the International Conference on Data Communication Networking, e-Business and Optical Communication Systems (ICE-B-2012),
pages 227-236
ISBN: 978-989-8565-23-5
Copyright
c
2012 SCITEPRESS (Science and Technology Publications, Lda.)
generate member-driven contents, resulting in a
relationship being built up". They see four basic
elements of virtual communities: (1) Existence in
cyberspace, (2) use of computer-based information
technology, (3) concentration on communication and
interaction with the focus on content-driven by
participants and (4) relation-ships. Different from
Hagel and Armstrong (1997), they do not include the
'fantasy' aspect.
We distinguish a variety of communities which
depend on different technological structures. Smith
and Kollock (1999) distinguish six types: (1) eMail
and discussion groups, (2) Usenet and BBS's
(Bulletin Board Systems), (3) text chat, (4) multi-
user domains or dungeons, (5) www sites, and (6)
graphical worlds. Graphical worlds are similar to the
3D worlds, which are at the focus of this study.
Other virtual community types include online games
(Hsu and Lu, 2004; Wu et al., 2008). They fulfill the
fantasy aspect and typically resemble the multi-user
dungeons with more graphical and multimedia
features. Porter and Donthu (2008) distinguish
virtual communities serving market research or
customer communication needs of a particular
company and those encouraging customers to share
personal information with the firm, cooperate in new
product developments, or become loyal customers.
The most prominent form of virtual communities are
social networking sites (Dwyer et al., 2008) such as
Facebook, MySpace, and Flickr. Offering a
combination of digital communication and
publishing, they emerged from the Web 2.0 trend.
Specific to 3D virtual communities is the use of
avatars, that are "three-dimensional and typically,
but not exclusively, anthropomorphic representa-
tions of people, including related in-world behavior
and paraphernalia, for the purposes of interaction
within virtual worlds" (Barnes and Mattson, 2008, p.
197). Tools are available to the user; images, sound
and models of spaces, the latter are three-
dimensional real-time video and audio tools are
often integrated as well as text chat.
Cyworld (CW) such a 3D virtual community
similar to sites like Facebook, perhaps with a more
realistic design (The McGraw-Hill Companies,
2005). Homepages are three-dimensional with the
ability to decorate a rather bare mini-room on the
personal page with furniture, art or music by paying
for virtual items. Inside the room 'lives' the personal
avatar of each individual user, the so-called 'mini-
me' (Dong-Hee and Won-Young, 2008). The
homepage includes a photo gallery, message board,
guestbook, and personal bulletin board. Members
can join a variety of groups or 'clubs' and discuss
topics and ideas via 'talk threads'. The currency is
called 'acorn' and is the equivalent of 0.10 US
Dollars. The 3D community was launched 1999 in
Korea (Kanellos, 2006). It really took off Korea's
largest wireless service provider SK Telecom took
over in 2003. CW Europe opened in 2006 and closed
in 2008.
Second Life (SL) is a 3D virtual world with
mountains, oceans, cities with houses and streets and
with a virtual sky. It is operated by Linden Lab,
founded in 1999. Users are represented by avatars
and guided by the members via their computers. The
currency, Linden Dollar, is pegged to the US Dollar.
With Linden Dollars, residents can make all kinds of
transactions on the platform. SL has also been used
as an educational channel. It offers like-minded
people the chance to find each other and to attend
virtual events or play games in SL. Users create
everything in the virtual world themselves, from the
cars they drive virtually to the streets they drive on
(Ondreijka, 2004/2005). They create landscapes and
items in real-time and share the creation itself as
well as the act of creation with each other. This
fosters interpersonal bonds between them.
SL is more complex than CW offering vaster
graphical tools and allowing users to be more
creative. However, those opportunities make it also
harder to use for new users.
2.2 Social Capital
Social capital stands for a variety of approaches and
definitions. There are several differences as to what
the sources of social capital are, what types of social
capital exist, and what it can be used for (Bourdieu,
1986; Coleman, 1990; Putnam, 2000; Lin, 2001). In
any case, social connections between individuals
have to exist for social capital to develop. These
connections enable resources for the individuals and
the group. Individuals make investments in social
relations. The maintenance of these relations is
necessary to ensure social capital. Norms, trust, and
reciprocity are important preconditions for the social
relations, thus social capital, to render benefits.
In this paper, we build on Lin's (2001, p. 19)
definition of social capital as "a social asset by
virtue of actors' connections and access to resources
in the network or group of which they are members".
Social capital is used in the same context as social
networks (Lin et al., 1981a; Lin and Dumin, 1986),
explicitly using the term 'tie', which refers to the
structure of a network.
Social capital is a collective of personal
resources and social resources that lie in the
ICE-B 2012 - International Conference on e-Business
228
connections and can be accessed through them (Lin
and Dumin 1986). Personal resources, such as one's
wealth, status, and power, belong to the individual
who decides how to use them (Lin et al., 1981a).
Social resources are accessible through the ties in a
network; they are temporary and borrowed.
Examples are wealth, status, and power of the
people with whom one is linked (Lin et al., 1981b).
For social capital to exist and grow, requires
investments in social relations (Lin, 2001).
Lin (2001) puts forward several benefits derived
from social capital: The flow of information is
facilitated. Social ties may lead to influence on
agents who are important decision makers, e.g.,
recruiters for jobs. Social ties can serve as 'social
credentials' by a third party building reputation.
Social ties strengthen identity and recognition, and
thus act as reinforcements. They provide emotional
support to individuals by helping them to find like-
minded people in society. They also help others
understand that an individual is entitled to certain
resources.
Social network theory has existed as a separate
field of research for many decades (Travers and
Milgram, 1969; Granovetter, 1973; Burt, 1997). It
focuses on the role that network structure plays in
generating benefits from social relationships. In
social network theory, there is a distinction between
nodes (actors) and ties, i.e., relationships between
the actors (Burt, 1997).
However, in spite of the network aspect of social
capital theory, studies that focus on social capital
and virtual, especially 3D virtual communities are
rare. Oh et al. (2004) look at social capital and
socializing ties in communities and particular parts
of society. They use social capital in groups to
analyze how social relations of members of a group,
both inside and outside of the group are linked to
group effectiveness. Bieber et al. (2002), defining a
virtual community as a group formed around a
particular interest and requiring electronic support,
focus on educational communities and professional
societies. They develop a plan for a community
knowledge evolution system aiming at a type of
digital library with particular functions and tools for
contributing knowledge and discussion of the
contributions. They investigate the knowledge
contribution in electronic communities without
directly mentioning social capital.
McLure, Wasko and Faraj (2005) put the
knowledge sharing in electronic networks of practice
as core of their studies. They analyze reasons, ways
to foster, and the results of knowledge contributions.
Their study focuses on how individual motivations
of people as well as social capital foster knowledge
sharing. They adapt the approach by Nahapiet and
Ghoshal (1998), which is different from the one
applied in this work. McLure Wasko and Faraj
(2005) suggest that reputation is a strong motivator
for participation and see social capital as a source,
rather than a result.
Investigating specific aspects that influence
knowledge contribution in virtual communities, Ma
and Agarwal (2007) investigate technology
infrastructure, Bock et al. (2005) look into extrinsic
rewards, reciprocal relationships, and sociological
factors, and Dholakia et al. (2004) study group
norms and social identity. However, none of these
studies use directly the term social capital. Finally,
Huysman and Wulf (2006) offer a framework
similar to the one in this study without empirical
analysis.
3 RESEARCH FRAMEWORK
AND HYPOTHESES
In our study, we use social capital mainly as a
synonym for information provision and proposed
that if information was accessible and passed on
from one person to another, social capital was
created. This is different from Miller et al. (2009)
posit a socializing, rather than a solely informational
role for interpersonal online exchanges. Similarly,
Wellmann and Gulia (1999) focus on social capital
providing support in case of social and mental
problems; Lin (2001) stresses social capital mainly
influencing agents.
We consider social relations, equal to an
exchange of favors and gifts, as the relevant basis of
social capital. Building on the model of social
capital proposed by Adler and Kwon (2002), we
employ their three constituting factors opportunity,
motivation, and ability and then add the factor
integration.
Opportunity is equal to the ties in a network or
the network structure (Adler and Kwon, 2002).
Assuming that a certain type of social tie is usually
helpful in connection with a specific task, we
examine three dimensions of opportunity:
opportunity through infrastructure, network
closure/strong ties, and weak ties/non-redundancy.
The usefulness of a tie depends on the specific
context (Adler and Kwon, 2002), which cannot be
generally described when studying 3D virtual
communities. Therefore we only analyze if any kind
of network structure exists, i.e., if any kind of tie
3D Communities as Platforms for Developing Social Capital
229
exists, which members of the communities use for
the creation of social capital. We assume that
network structure is important if the individual has
either strong or weak ties connecting him or her to
others. If both types of ties exist, we conclude that
this is a more valuable situation than having only
one type of tie available. The reason for this is that
the kind of information an individual looks for can
vary while he or she is a member of the community.
Regarding opportunity, we propose:
H1a: In CW, opportunity acts as a source of
social capital.
H1b: In SL, opportunity acts as a source of
social capital.
Motivation encompasses the background to
actions of donors and why they help others without
being certain of a form of repayment for their favors
(Adler and Kwon, 2002). The existence of a
relationship between two people alone is no
guarantee for social capital to emerge; therefore
individual motivations are be considered. Trust,
norms (reciprocity), associability, instrumental
motivation, and perceived identity verification
contribute to contribute to motivation. Trust is a key
source of motivation (Putnam, 2000). The same goes
for norms, in particular those of generalized
reciprocity (Putnam, 2000; Blau, 1986).
Associability refers to the "willingness and ability of
participants in an organization to subordinate
individual goals and actions" (Leana and van Buren,
1999, p. 541) allowing individual actors help others
in order to achieve a common goal. Instrumental
motivation means that actors are motivated by the
expectation of getting another use out of social
capital, for example information on career
advancement (Adler and Kwon, 2002; Lin, 1981a).
Further, based on the literature, we consider
perceived identity verification, which fosters
knowledge contribution. The idea is that precise
communication and verification of identity, e.g.,
through tools in online communities can yield
benefits for the participants (Ma and Agarwal,
2007). Regarding motivation, we propose:
H2a: In CW, motivation acts as a source of
social capital.
H2b: In SL, motivation acts as a source of social
capital.
Ability driving the development of social capital
refers to the resources and competencies of
individual actors. Following Adler and Kwon
(2002), no social capital can develop when the
people in the network do not possess any knowledge
or expertise which they can then share with others.
This is different from Burt (1997) who says that
ability touches only the dimension of human capital,
but not social capital. We distinguish five categories
of ability: personal resources, resources of contacts
(social resources), cognitive ability, Internet
experience, and associability. One can use personal
resources, resources of contacts, and the others'
resources that are accessible through social ties (Lin,
1999). Cognitive ability refers to the ability to share
context (Nahapiet and Ghoshal, 1998). i.e.; a person
is able to make others understand what she tries to
tell him. Internet experience takes into account the
Internet context, as Internet experience has an effect
on the perception of the usefulness of a website
(Nysveen and Pedersen, 2004). Associability affects
both the motivation and the ability dimension of
social capital (Leana and van Buren, 1999).
Regarding ability, we propose:
H3a: In CW, 'ability' acts as a source of social
capital.
H3b: In SL, 'ability' acts as a source of social
capital.
Integration has been added as potential
constituting factor. Alesina and La Ferrera (2000)
found a connection between a fragmentation of any
kind and a negative impact on social participation
and so consequently on social capital. As the
Internet makes it easy to find people with the same
opinions, interests and ideologies, there is a risk that
'fringe communities' develop, which are distant
geographically (van Alstyne and Brynjolfsson,
2005). Such heterogeneity in an online environment
can destroy social capital or circumvent its creation
(van Alstyne and Brynjolfsson, 2005).We assume
that that there is a positive connection between a
level of high integration and social capital in the 3D
virtual community. Regarding the factor integration,
we propose:
H4a: In CW, 'integration' acts as a source of
social capital.
H4b: In SL, 'integration' acts as a source of
social capital.
Table 1 summarizes our hypotheses.
ICE-B 2012 - International Conference on e-Business
230
Table 1: Research Hypotheses.
H
Hypothesis
H1a
In CW, the factor 'opportunity' acts as a
source of social capital.
H1b
In SL, the factor 'opportunity' acts as a source
of social capital.
H2a
In CW, the factor 'motivation' acts as a
source of social capital.
H2b
In SL, the factor 'motivation' acts as a source
of social capital.
H3a
In CW, the factor 'ability' acts as a source of
social capital.
H3b
In SL, the factor 'ability' acts as a source of
social capital.
H4a
In CW, the factor 'integration' acts as a
source of social capital.
H4b
In SL, the factor 'integration' acts as a source
of social capital.
Compared to Adler and Kwon (2002), we exclude
possible risks and benefits of social capital. We
assume that social capital yields benefits only
although for instance Portes (1998) warns about the
risks of social capital, such as free-riding on
information. We measure the benefits of social
capital because social capital itself is difficult to
operationalize. Nevertheless, we focus on the
existence and the 'quantity' of social capital.
Determining its value would be beyond the scope of
this study. Therefore, we do not consider
contingencies and capabilities affecting social
capital value either.
4 RESEARCH APPROACH
We use an online survey to collect the data from an
online environment. We employ a seven-item Likert
scale, ranging from the highest ('applies fully') to the
lowest ('does not apply at all'). In the analysis, the
highest rated answer was represented by the value '6'
and the lowest by the value '0'. At the end of the
questionnaire, we asked about the participant's,
gender, age, and education.
We pre-tested the questionnaire by six executives
of two 3D virtual communities. Based on their
comments, we provided more detail on the purpose
of the research in the introduction and modified
some of the warm-up questions since they were
perceived as too polarizing. After the refinements,
the survey link was distributed through various
channels related to the two platforms (details upon
request).
After six weeks of online presence between
December 2008 and January 2009, 223
questionnaires were completed. Of those, we
eliminated four questionnaires because of answers
the respondents filled in the same answer for every
single question. Further, in preparation for the
analysis, we aggregated the individual factor items
by calculating their mean, so that we obtained one
value for each factor.
Of the 219 remaining questionnaires, 63% were
filled in by SL users and 37 % by CW users (of
those: 44% CW U.S., 54% CW Korea, 1% CW
China, and 1% CW Japan). Overall, 61% of
respondents were female and 39% male. Their age
ranged from 18 to over 45 years in SL and from
under 18 to 36-45 years in CW. The largest
respondent group in SL was over 45 (42%) and in
CW 18-25 years (51%). In CW, 52% had a college
degree or higher level of education, in SL even 88%
(74% overall).
5 RESULTS
5.1 Descriptive Statistics and
Regression Analysis
First, we tested the sample size, i.e. whether the
sample contains enough subjects to actually conduct
a multiple regression analysis. We used the formula
proposed by Green (1991) for models with less than
7 independent variables. We apply the
formula
mN 850
. For CW, the required
minimum number of subjects is 50 + 8*2 = 66
compared to 79 subjects in the sample. For SL, the
140 subjects meet the required 50 + 8*4 = 82 ones.
The standard deviation is low for the overall
sample, CW, and SL. The higher standard deviation
value for social capital (0.937, 1.433, and 951 for the
three samples) could mean that the level of social
capital that is created for the individual differs from
respondent to respondent.
Tests on Cronbach's alpha suggest sufficient
reliability of all constructs. Almost all values for
Cronbach's alpha exceed a level of 0.70. Only for
SL, the value for the integration is 0.692; which is
still acceptable (Ma and Agarwal, 2007).
We then estimated the regression functions for
CW and SL. Of the models with significant t-values,
we chose the one with the best overall predictive fit.
The regression functions are:
Social Capital (CW) = -1.143 + 0.759 Motivation
+ 0.431 Ability
Social Capital (SL)= -0.889 + 0.213 Motivation
+ 0.511 Ability + 0.282 Opportunity + 0.190
Integration
3D Communities as Platforms for Developing Social Capital
231
Concerning the goodness of fit (see Table 2), the
R
2
adj
for CW is 0.502 and the value for SL is 0.503.
This means that 50.2% (50.3%) of the variation in
social capital is explained by the independent
variables in the particular model. We then checked
the validity of the regression functions, i.e., whether
the proposed models are valid for the population, by
looking at the F-values (see Table 2). They are
40.357 for the CW sample and 36.184 for SL. At the
required level of significance of 0.05 and 2 degrees
of freedom (CW) as well as for 4 degrees of freedom
(SL) the value is much higher than the theoretical
values of approximately 3.12 for the CW sample and
2.2 for the SL sample. The level of significance for
both samples is zero; the two models are valid for
the population.
Next, we analyzed the validity of the regression
coefficients (see Table 3). For SL, the t-values are
larger than 2 and the significance levels of the
regression parameters are well below the threshold
of 0.05. The lowest significance level is 0.011
(motivation). For CW, the levels for the two
independent variables are 0.000 and 0.032, i.e., all
independent variables in the two models are
significant at a level of 95%. Overall, the
significance levels for SL are better than those for
CW.
Testing for multi-collinearity, we investigate the
variance inflation factor (VIF) and the
corresponding value for tolerance for each
independent variable and each community (see
Table 3). For CW the highest VIF value is 1.699,
and for SL the highest value is 2.111. All values are
below the threshold value of 10 (Chatterjee et al.,
2006). The tolerance values, which should be
relatively high to indicate an absence of multi-
collinearity, are all above 0.10. There is no
indication of multi-collinearity; none of the variables
is redundant.
We examined the normality of the error terms by
creating graphs (left out due to page limit). Neither
the graph of normal distribution nor the normal
probability plot shows evidence against normality
for the respective model; especially in the normal
probability plot residuals are all very close to the
line through origin.
5.2 Assessment of Hypotheses
According to the regression analysis, there is no
significant relation between opportunity and
integration and the formation or existence of social
capital in CW. Therefore, H1a and H4a cannot be
assessed. However, there is a significant relationship
between motivation and ability and social capital;
H2a and H3a could be supported. Motivation is
highly significant.
For SL, all four factors show a significant
positive relationship with social capital. Therefore,
H1b, H2b, H3b, and H4b are supported.
Figure 1 summarizes the factors which appear to be
significant as source for social capital in each 3D
virtual community. Table 4 summarizes the
assessments of the hypotheses.
Table 2: Regression Model Fit.
Sample
Measure
Df
Mean
Square
F
Sign.
R
R
2
Adj. R
2
Std.
Error
CW
Regression
2
41.276
40.357
0.000
0.718
0.515
0.502
1.011
Residual
76
1.023
Total
78
SL
Regression
4
16.272
36.184
0.000
0.719
0.517
0.503
0.671
Residual
135
0.450
Total
139
Table 3: Regression Coefficients.
Sample
Variable
Tolerance
VIF
Beta
Adj. Beta
Std.
Error
T
Significance
CW
(Constant)
-1.143
0.681
-1.679
0.097
Motivation
0.589
1.699
0.759
0.550
0.144
5.284
0.000
Ability
0.589
1.699
0.431
0.227
0.198
2.184
0.032
SL
(Constant)
-0.889
0.472
-1.883
0.062
Opportunity
0.474
2.111
0.282
0.234
0.096
2.932
0.004
Motivation
0.562
1.780
0.213
0.224
0.083
2.573
0.011
Ability
0.560
1.786
0.511
0.362
0.113
4.536
0.000
Integration
0.994
1.006
0.190
0.178
0.064
2.966
0.004
ICE-B 2012 - International Conference on e-Business
232
We only measured the alpha-error, not the beta-
error. The consequence of a relevant beta-error
would be that a connection between factors is
overseen. The sufficient, but relatively small
sample for CW could be responsible for the non-
significance of two out of four independent
variables (factors). Further, for simplicity reasons,
the individual aspects have not been weighed when
creating the independent variables. Therefore, we
do not know which of the individual aspects of
each factor contribute to the obtained result.
6 DISCUSSION
The results show that in CW, which resembles a
networking platform, only two of the four
proposed factors constitute social capital.
In CW, motivation is determined by trust,
norms, associability, instrumental motivation, and
perceived identity verification, all of which are
present. Trust and norms are presumably likely to
play an important role because of the users' age
structure. Internet users under 18-year-olds are
more trustful online and have fewer concerns about
privacy violations than older Internet users (Youn,
2008). They are likely to share more information.
Norms might encourage participation. Parents
might support their children's participation more in
a monitored environment compared to a more open
one. Associability could also drive motivation.
Net-wide competitions and campaigns run on CW.
For example, the monthly competition 'Cy
Uhlzzang' ('the best looking'), where nominees
often recruit friends and acquaintances, in an
attempt to get votes. CW users also exchange
information for instrumental reasons. Ability
positively influences the development of social
capital as well. There could be no social capital
without anybody knowing anything that they could
share with others. Even though CW is fairly self-
explanatory, some Internet experience helps users
finding their way on the community website and
using the available tools. Cognitive ability is likely
present due to the picture-, music- and video-
sharing applications on the site. Integration is not
significant. A reason could be that there are several
CWs around the world. One needs a Korean social
security number to register as a member on the
Korean CW (Kanellos, 2006); most members
visiting CW U.S. are U.S. Americans or
Canadians. Opportunity, surprisingly, is not
significant. Possibly the ties used in CW are rather
task-specific, whereas the questions asking about
opportunity were rather general. In such case, it
differs from user to user whether strong or weak
Social
Capital
0.2130.213
MotivationMotivationMotivation
0.5110.511AbilityAbilityAbility
0.511
IntegrationIntegrationIntegration
0.2130.190
Opportunity
0.2130.282
AbilityAbilityAbility
MotivationMotivationMotivation
0.431
0.759
Social
Capital
Cyworld Second Life
Social
Capital
0.2130.213
MotivationMotivationMotivation
0.5110.511AbilityAbilityAbility
0.511
IntegrationIntegrationIntegration
0.2130.190
Opportunity
0.2130.282
AbilityAbilityAbility
MotivationMotivationMotivation
0.431
0.759
Social
Capital
Cyworld Second Life
Figure 1: Significant Factors and Respective B-Values [Source: Table 3].
Table 4: Assessment of Hypotheses.
Hypothesis
Result
H1a (Opportunity, CW)
N/A
H1b (Opportunity, SL)
Supported
H2a (Motivation, CW)
Supported
H2b (Motivation, SL)
Supported
H3a (Ability, CW)
Supported
H3b (Ability, SL)
Supported
H4a (Integration, CW)
N/A
H4b (Integration, SL)
Supported
3D Communities as Platforms for Developing Social Capital
233
ones are more useful. However, we would have
expected that opportunity appeals more on a
networking site like CW than on an online gaming-
like platform. Maybe, the level of technical expertise
and Internet experience required explain it. Lower
expertise and experience level may suggest less
interest in opportunity.
In SL, which appears more like an online
gaming platform, ability, opportunity, motivation,
and integration play a role in building social capital.
Ability is the most important determinant of social
capital; it is more important than in CW. There are
several explanations for this. SL users are on
average older and better educated than CW users.
So, they are bound to have more resources available
in terms of knowledge and experience which can be
shared with other users. Furthermore, the more
complex concept of SL requires a high level of
Internet experience for participating on the platform
and for sharing information with other users.
Opportunity, i.e., the ties between people, plays a
weaker role in SL compared to CW. SL users may
spend so much time in SL that they feel as if they
know the others personally, although SL support
remaining anonymous. In fact, in SL both parties
could play specific roles much unlike their real
personalities. Therefore respondents might perceive
the ties with other users as being personal and
impersonal at the same time. This could explain the
significant result in contrast to CW. Motivation is far
less important in SL than in CW. Explanations could
be less trustful adult users or more anonymous
community type. Users only know the other person
as an 'avatar'. In contrast to CW, in SL the sources of
motivation likely lie in the areas of instrumental
motivation and perceived identity verification. Since
SL is fairly complicated, users may help each other
on problems concerning the use of the platform
tools. Perceived identity verification could be more
important than in CW. Many SL users make use of
the option to disguise themselves, i.e., literally live a
'second life'. Likely, these users are more prepared to
interact with others who give them positive feedback
on their avatar and the way they intended to present
themselves. Integration is least important for
developing social capital in SL. But in contrast to
CW, it plays a role. A reason could be the lower
fragmentation. As there is only one SL platform, SL
users have different cultural backgrounds. They are
likely to be more open about sharing information
with people who are different from themselves
because they are more used to it.
In summary, the factors driving the
development of social capital differ between CW
and SL. While motivation and ability play
significant roles on both platforms; opportunity and
integration constitute social capital only in SL. The
differences may be explained by the specific nature,
layout, and construction of the communities as well
as the age and educational structure of their
members.
In both samples almost 50% of the variation in
social capital is not be explained by the variables in
the model. Other influencing factors must exist.
7 SUMMARY AND OUTLOOK
In this study, we investigate the development of
social capital in 3D virtual communities. We find
that motivation is particularly important for driving
the creation of social capital, followed by the
resources at the nodes of the network, i.e., ability.
Also the users' education and age structure in
particular influence the development of social
capital. Further, it seems to make a difference if the
platform is designed for users living in the same
country or if it is invites users from all over the
world. Beyond those first insights, our results also
suggest that more factors than the ones discovered
here contribute to developing social capital in 3D
virtual communities. Future research should
therefore focus on identifying those factors as well
as look at the already found factors more closely.
ACKNOWLEDGEMENTS
The authors would like to acknowledge the data
provided by E.K. Koehli, Master Student in Media
and Technology Management at the University of
Cologne (graduation 2009).
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