3D Communities as Platforms for Developing Social Capital

Claudia Loebbecke

, Paolo Depaoli

and Marco De Marco

Dept. of Media and Technology Management, University of Cologne, Pohligstr. 1, Cologne, Germany

Department of Earth Science, Life and Environment, University of Urbino, Urbino, Italy

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

 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.

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

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

Sum of

Squares

Mean

Square

Sign.

Adj. R

Std.

Error

Regression

82.552

41.276

40.357

0.000

0.718

0.515

0.502

1.011

Residual

77.730

1.023

Total

160.282

Regression

65.088

16.272

36.184

0.000

0.719

0.517

0.503

0.671

Residual

60.709

135

0.450

Total

125.797

139

Table 3: Regression Coefficients.

Sample

Variable

Tolerance

VIF

Beta

Adj. Beta

Std.

Error

Significance

(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

(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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