2013 46th Hawaii International Conference on System Sciences
Virtual World Entrepreneurship
Andrew Hardin
University of Nevada, Las Vegas
[email protected]
Jennifer Nicholson
Rowan University
[email protected]
Anjala Krishen
University of Nevada, Las Vegas
[email protected]
Darren Nicholson
Rowan University
[email protected]
accessories, furniture, gifts, and pets, as well as
“virtual services” such as teaching courses and
planning in-world weddings. Sales of virtual goods
and services have continued to rise in recent years,
totaling an estimated $1 billion in real money in the
U.S., and $5 billion in China in 2009 alone [7]. One
virtual world entrepreneur, based upon her in-world
holdings and the exchange rate for the virtual
currency and the US dollar, boasted a net worth of
over US$1,000,000 [8]. While the accumulation of
such wealth may be uncommon, it is nonetheless
evidence of the significant potential for launching
new business opportunities in virtual world
environments.
Exploiting these virtual world
opportunities may also provide fertile testing ground
for real world entrepreneurs who wish to try out their
ideas in the relatively low risk environment of virtual
worlds.
Despite the acknowledged potential of virtual
worlds, little is known about the factors influencing
entrepreneurship in these environments. The current
study attempts to address this issue by extending the
work of Zhao, Seibert, and Hills [1] to the context of
virtual worlds. In doing so, this study contributes to
the research fields on both entrepreneurship and
virtual worlds. First, while entrepreneurial selfefficacy has been established as a predictor of
entrepreneurial intentions in a real world context, this
relationship has not been confirmed in virtual worlds,
where a certain level of technological proficiency is
required for entrepreneurial success. To address this
gap in the literature, we developed a new measure of
virtual world technology self-efficacy, and then
evaluated its predictive validity within the framework
of the Zhao et al. [1] model of entrepreneurial
intentions. Second, we evaluated these relationships
during a comprehensive, collaborative project that
required teams to create businesses within the virtual
world, Second Life. More precisely, teams were
charged with building businesses that could facilitate
a viable consumer experience not easily replicated on
the traditional Internet. This immersive learning
Abstract
Virtual
worlds
are
three-dimensional
environments in which individuals represented by
avatars can buy and sell virtual content and real
world products. Virtual world entrepreneurs have
been able to generate significant, real world profits
in these simulated environments. Extending the work
of Zhao, Seibert, and Hills [1], the authors examine
the role of virtual world technology self-efficacy and
virtual world entrepreneurial learning as indirect
predictors of virtual world entrepreneurial
intentions. Findings from three waves of data
collected during a field study reveal that virtual
world entrepreneurial self-efficacy mediates these
relationships. Implications and future research on
entrepreneurship in virtual worlds are discussed.
1. Introduction
A virtual world is a three-dimensional, Internetbased, simulated environment where participants, in
the form of avatars, can communicate, collaborate,
and conduct business. Despite admonitions about the
increased reliance of humans on computer
technology [2], there has and continues to be much
publicity surrounding the potential of virtual worlds.
This has spawned an increase in research on virtual
worlds where topics such as enhancing brand
perceptions [3], understanding users’ intentions to
purchase virtual goods [4], as well as intentions to
return to virtual worlds [5], have been explored.
Researchers have even predicted that by 2018, virtual
worlds will be the principal platform for business
applications and opportunities [6].
Virtual worlds present a new opportunity for those
with entrepreneurial aspirations. In these virtual
environments, individuals can create and run their
own small businesses with relatively little start-up
capital. Virtual world entrepreneurs can earn real
world money selling “virtual items,” such as clothing,
1530-1605/12 $26.00 © 2012 IEEE
DOI 10.1109/HICSS.2013.596
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Figure 1: Hypothesized model. Arrows
represent hypothesized paths. Dotted arrows
represent indirect effects. H = Hypothesis; T =
Time.
experience allowed us to examine whether virtual
world entrepreneurial learning could indirectly
predict virtual world entrepreneurial intentions
through virtual world entrepreneurial self-efficacy. It
also addressed limitations of prior research by
allowing for a more focused examination of the
impact of entrepreneurial learning on entrepreneurial
intentions, as perceptions of entrepreneurial learning
were assessed during a specific learning opportunity
rather than retrospectively after the completion of an
entire entrepreneurship program [1].
The model in Figure 1 sets the stage for this
research. Similar to Zhao et al. [1], the authors
examine virtual world experience, risk, and gender,
as predictors of virtual world entrepreneurial selfefficacy. Because a level of comfort with the
technology is necessary for building in-world
businesses, we also examined the role of virtual
world technology self-efficacy as an indirect
predictor of virtual world entrepreneurial intentions
through virtual world entrepreneurial self-efficacy.
Virtual world entrepreneurial learning was examined
as a predictor of virtual world technology selfefficacy, and as an indirect predictor of virtual world
entrepreneurial intentions through virtual world
entrepreneurial self-efficacy.
As illustrated in the model, data was collected at
three different time periods throughout a semesterlong project during which participants worked in
teams to develop virtual world businesses. Time 1
data was collected two weeks after the project began.
Time 2 data was collected after the participants had
time to familiarize themselves with the technology
and to develop their businesses (approximately 8
weeks later). Time 3 data was collected at week 14,
just prior to the final project deliverable.
2. Antecedents to Virtual
Entrepreneurial Self-Efficacy
World
Zhao et al. [1] suggests that gender,
entrepreneurial experience, and risk propensity are
indirectly related to entrepreneurial intentions
through entrepreneurial self-efficacy. Consistent with
these findings, we expect that similar relationships
will exist among these variables in virtual world
settings. Thus we retained these relationships in our
extended model.
Hypothesis 1: Women will report lower levels of
virtual world entrepreneurial self-efficacy than men.
Hypothesis 2: Virtual world entrepreneurial
experience will be positively related to virtual world
entrepreneurial self-efficacy.
Hypothesis 3: Risk propensity will be positively
related to virtual world entrepreneurial self-efficacy.
To extend the Zhao et al. [1] model to the context
of virtual worlds, we include an additional predictor,
virtual world technology self-efficacy. Creating
businesses in virtual worlds requires a certain level of
technology proficiency.
While virtual world
consumers can learn to navigate the environment by
visiting virtual world “learning regions” designed to
introduce new users to the environment, creating
businesses requires detailed knowledge of specific
virtual world applications.
In the information systems literature, computer
self-efficacy has been demonstrated to influence
outcomes such as behavioral intentions [9-11]. While
computer self-efficacy is a general level construct,
more specific measures have been used to predict
activities such as spreadsheet performance [12], and
creative performance in employees [13]. Specific
computer self-efficacy measures have been
demonstrated to have greater predictive ability than
more general measures [11], and specific and general
measures have been shown to be predictive of one
another [14-16]. In a similar manner, we expect that a
context specific virtual world technology selfefficacy measure will best predict virtual world
entrepreneurial self-efficacy. Business creation in
virtual worlds requires a certain level of
technological skill. Thus, one’s perception of their
technological abilities should be predictive of beliefs
in their ability to create in-world businesses.
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Hypothesis 4: Virtual world technology selfefficacy will be positively related to virtual world
entrepreneurial self-efficacy.
3. Method
Much like embarking on the creation of a new
venture, virtual world entrepreneurs need to learn
how to start and run successful businesses. Social
cognitive theory (SCT) suggests that efficacy is
developed through four processes: enactive mastery,
vicarious experience, social persuasion, and affective
states. Enactive mastery and vicarious experience are
developed through behavioral modeling training and
have been shown to be the strongest predictors of
self-efficacy beliefs [17-19].
Hands-on activities
and/or observing others building infrastructure inworld should increase ones virtual world technology
self-efficacy beliefs.
This study was conducted as part of a
collaborative project between universities located on
the east and west coasts of the United States.
Graduate and undergraduate students enrolled in
ecommerce focused business courses participated in
the study to satisfy part of the requirements. The
project required student teams to create virtual world
businesses that could be supported by a
complimentary web presence on the Internet. To
provide business development areas in Second Life
for the15 randomly generated teams, two virtual
world regions were purchased by the respective
universities (approximately $2,500 per region, $5,000
total). Teams were each allotted ~7500 Linden
Dollars (US $30.00, $450 total), to seed their
businesses. The regions were equally divided into
parcels, with each team receiving an allocation of 452
prims1. A series of specific deliverables ensured that
students learned skills needed to use the Second Life
platform,
and
to
understand
important
entrepreneurship principles. The first deliverable
required students to complete the Second Life
registration process which included the completion of
specific learning tasks on Orientation Island2.
Students were then asked to customize their avatars,
and teams were required to submit a screenshot of a
team meeting in Second Life. The second deliverable
required students to submit an executive summary
proposing a business idea, along with a financial
model that explained how they planned to utilize
their seed funds to create a profitable business. This
necessitated learning about the sale and purchase of
goods and services within Second Life. Following the
approval of their business concept, the third
deliverable required students to build a virtual place
of business within Second Life. This necessitated
learning how to manipulate prims to create an
infrastructure particular to the business chosen by the
team (e.g., buildings, floating platforms, in-world art,
theaters, etc.). To aid in this process, students were
directed to the Second Life knowledge database
where they could review videos and read detailed
textual explanations on how to effectively use the
software to build businesses. Students were also
3.1 Sample and Study Details
Hypothesis 5: Virtual world entrepreneurial learning
will be positively related to virtual world technology
self-efficacy.
In a similar fashion, hands-on experience
implementing virtual world business models using
entrepreneurial principles learned during the project
should influence the development of virtual world
entrepreneurial self-efficacy.
Hypothesis 6: Virtual world entrepreneurial learning
will be positively related to virtual world
entrepreneurial self-efficacy.
Consistent with Zhao et al. [1], entrepreneurial
self-efficacy should predict intentions to pursue
entrepreneurial activities, albeit in a virtual world
environment. In addition, any direct effect of virtual
world learning or virtual world technology selfefficacy is predicted to be mediated by virtual world
entrepreneurship self-efficacy. Although these
relationships are known, they have not been
established in virtual worlds, and are critical to
extending the Zhao et al. [1] model.
Hypothesis 7: Virtual world entrepreneurship selfefficacy will be positively related to virtual world
entrepreneurial intentions.
Hypothesis 8: Virtual world entrepreneurship selfefficacy will mediate the relationship between virtual
world technology self-efficacy and virtual world
entrepreneurial intentions.
Hypothesis 9: Virtual world entrepreneurship selfefficacy will mediate the relationship between virtual
world entrepreneurial learning and virtual world
entrepreneurial intentions.
1
Prims are a single object in Second Life. Regions
are limited in Second Life based upon the number of
prims they can support.
2
New Second Life users are sent to Orientation
Island to learn the skills needed to use the software 4317
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asked to prrovide details regarding
r
the use
u of the seed
d
funds to date,
d
and to prrovide screen shots of theirr
respective in-world busiinesses. The laast deliverablee
vide final expen
nditure figures,,
required sttudents to prov
and to prov
vide screensho
ots of the team at the businesss
location.
w
of dataa were colleccted from 77
7
Three waves
participantts over the cou
urse of the pro
oject (68% (n=
=
53) male, 32% (n = 24)
2 female). As
A previously
y
mentioned, Time 1 dataa was collecteed two weekss
after the project
p
began. Time 2 data was collected
d
after the participants
p
had
d sufficient tim
me to learn thee
software and to develop
d
their businessess
(approximaately 8 weeks later). Timee 3 data wass
collected at week 14, just prior to the finall
deliverablee.
3.2 Measu
ures
Genderr: Subjects were
w
asked to
o report theirr
gender at Time 1. Males were cod
ded as 1, and
d
females weere coded as 0.
Virtual World Entrep
preneurial Exp
perience: Thiss
scale was adapted from Zhao et al. [1]. Four itemss
xperience. Onee
were used to measure viirtual world ex
m is: I have exxperience with
h virtual world
d
sample item
new-venturre start-ups. A Likert type 7-point scale (1
1
= strongly disagree to 7 = strongly ag
gree) was used
d
o measure this variable at Tim
me 1.
( = .96) to
Risk Prropensity: Thiss measure wass adapted from
m
Zhao et al.. [1]. Four item
ms were used to measure risk
k
propensity. An examp
ple item is: I enjoy thee
excitementt of uncertaintyy and risk. A Likert type 7-point scalee (1 = strongly disagree to
o 7 = stronglyy
agree) wass used ( = .80
0) to measure this
t variable att
Time 1.
hnology Self-E
Efficacy: Thee
Virtual World Tech
t measure were
w
generated by the authorss
items for this
based on an
a existing speecific computeer self-efficacy
y
measure deeveloped by Jo
ohnson and Marakas [12], ass
well as a careful rev
view of the Second Lifee
knowledgee base. Specifically, 10 items weree
developed based upon a review of the frequently
y
asked quesstions section of the knowleedge base. Thee
confirmato
ory factor analy
ysis discussed in
i Appendix A
resulted in
n seven items being
b
retained for the study.
A sample item is: I beelieve I have the ability to
o
A is common
n
manipulatee primitives in Second Life. As
for self-effficacy scaless [20], a 0 to 100 scalee
anchored by,
b I cannot do
o and very conffident was used
d
( = .93) to
o measure this variable at Tim
me 2.
Virtual World Entrrepreneurial Learning:
L
A
s
was ussed to assesss
semantic differential scale
perceptions of virtual world
w
learning
g. The primerr
ur perception of
o the in-world
d
was: Pleasse indicate you
entrepreneeurial training
g you were provided in
n
Seconnd Life. Four items were uused to measuure the
consttruct at Time 22, with anchorrs such as: suffficient,
insuffficient. ( = .996).
Viirtual World E
Entrepreneuriall Self-Efficacyy: This
meassure was adaptted from Zhao et al. [1]. Fourr items
weree used to measure virtual w
world entreprenneurial
me 3. A sample item is: I beelieve I
self-eefficacy at Tim
have the ability to iidentify new buusiness opportuunities
in vvirtual worlds.. Similar to our previouss selfefficaacy measure, a 0 to 100 scale anchoredd by, I
cannnot do and verry confident w
was used ( = .95)
(Banndura, 2005).
Viirtual World Entrepreneurial Intentions: This
scalee was also adaapted from Zhhao et al. [1]. Four
itemss were useed to measuure virtual world
entreepreneurial inteentions. A sam
mple item wouldd be: I
am iinterested in starting a buusiness in a vvirtual
worldd. A Likert ttype 7-point sscale (1 = strrongly
disaggree to 7 = stroongly agree) w
was used ( = ..98) to
meassure this variabble at Time 3.
3.3 A
Analyses
A
AMOS versionn 19 was used to examinne the
reseaarch model. W
We used single score indicatorrs [21]
to redduce the numbber of parameteers estimated reelative
to thhe sample sizee. Following thhe recommenddations
of B
Bollen [21] wee first conduccted a confirm
matory
factoor analysis (C
CFA) for eachh of the indiividual
meassures. Upon esstablishing thatt the CFAs inddicated
a goood fit, reliabiilities were thhen calculatedd. The
reliabbilities were uused to compuute the variancces for
the rrespective sinngle item scalle scores andd were
enterred into the struuctural model.. Beyond our design
that m
measured speccific variables aat different points of
time,, we assessedd the impact oof common m
method
variaance by determ
mining that a seven factorr CFA
modeel fit the data bbetter than a onne factor modeel. The
meanns, standard deviations annd correlationns are
depiccted in Table 1. Results are ddepicted in Figuure 2.
Table 1: Me
eans, standarrd deviations,
corrrelations, and
d reliabilities o
of study variables.
in
nternal reliabilities are in p
parenthesis. T =
Time.* p < .05. ** p < .01
M
Model fit forr the hypothhesized modell was
excelllent, X2 (8, N = 77) = 10.201, ns), CMIIN/DF
1.1299, CFI = .991,, NFI = .937, G
GFI = .969, A
AGFI =
.893,, RMSEA = .041. Gendeer ( = -.0622, ns),
experrience ( = .0082, ns), and rrisk propensityy ( =
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.034, ns) were not significantly related to virtual
world
entrepreneurship
self-efficacy.
Thus,
Hypotheses 1, 2 and 3 were not supported. The
finding associated with gender is consistent with the
results reported by Zhao et al. [1], and the
relationship is in the expected direction3. However,
the findings associated with experience and risk
propensity were somewhat contrary to expectations.
Experience with virtual world entrepreneurial
activities was not predictive of a person’s belief in
their ability to create ventures in virtual worlds. We
surmise this occurred because the participants had
very little entrepreneurial experience with virtual
worlds (M = 1.96). Zhao et al. [1] found that risk
propensity was only weakly related to EI ( = .18, p
< .05). Given our sample size limitations, finding a
non-significant relationship between risk propensity
and virtual world entrepreneurship self-efficacy is not
completely unexpected. Beyond sample size
limitations, because of the costs associated with
starting a virtual world business, entrepreneurial
activities may be perceived as being less risky.
The addition of the virtual world technology selfefficacy measure produced interesting results beyond
those reported by Zhao et al. [1]. Supporting
Hypothesis 4, virtual world technology self-efficacy
was significantly related to virtual world
entrepreneurial self-efficacy ( = .706, p < .001).
Virtual world entrepreneurial learning was
significantly related to both virtual world technology
self-efficacy ( = .298, p = .011), and virtual world
entrepreneurship self-efficacy ( = .246, p = .003),
supporting Hypotheses 5 and 6. Supporting
Hypothesis 7, virtual world entrepreneurship selfefficacy was significantly related to virtual world
entrepreneurial intentions ( = .634, p < .001, R2 =
.40). The indirect effects of virtual world
entrepreneurial learning ( =.287, p < .01) and virtual
world technology self-efficacy ( =.447, p < .001) on
virtual world entrepreneurial intentions confirm
Hypotheses 8 and 9.
Figure 2: Results: Parameter estimates are
standardized. Solid arrows represent direct
effects; dotted arrows represent indirect effects.
T = Time.
* p < .05. ** p < .01 *** p < .001
4. Discussion
Virtual worlds continue to generate interest as a
potential platform for commerce. Despite this
attention, very little is known about entrepreneurship
in these environments. This study represents an
important first step towards understanding virtual
world entrepreneurial behavior.
Zhao et al. [1] provided valuable insight into the
antecedents of entrepreneurial self-efficacy, and the
relationship between entrepreneurial self-efficacy and
entrepreneurial intentions. Our study builds upon the
Zhao et al. research in three significant ways. First,
we evaluated the model in a virtual world
environment. It has been noted that in order to better
understand entrepreneurial characteristics, future
research should examine the different types of new
ventures that individual’s engage in [22]. Virtual
worlds have been touted as the future of global
commerce by ICANN’s CEO, Paul Twomey. Hence,
they provide a novel yet ideal context in which to test
the model. Three waves of data were collected
during a comprehensive collaborative project
between two universities located on the east and west
coasts of the United States. Undergraduate and
graduate teams enrolled in ecommerce courses were
tasked with developing a viable business plan to
bridge the traditional web and a 3D virtual world
environment. The project lasted a full semester and
the businesses were sophisticated as a result. For
instance, during a demonstration of their project, one
team was joined by an existing virtual world
entrepreneur who decided to join them in creating art
galleries that not only display 3D objects, but also
allow avatars to become part of the exhibits, in
3
Zhou et al. [8] test an alternative model in which gender was
specified as a direct predictor of EI. We tested a similar model
however the relationship between gender and EI was not
significant.
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world entrepreneurial self-efficacy. In virtual worlds
however, this finding may make more sense. Given
the high percentage of female participants in virtual
worlds such as Second Life, females may feel more
confident as entrepreneurs in these settings.
Essentially this “evens the score” between female and
male entrepreneurs.
Finally, prior experience with virtual world
entrepreneurship was not a significant predictor of
virtual world entrepreneurial self-efficacy. We
surmised this occurred because very little prior
experience was reported by the participants. It may
also be related to our explanation regarding risk
propensity, i.e., given the low investment needed to
run businesses, people are more willing to believe
they have the ability to be entrepreneurs in these
settings.
Notwithstanding
these
potential
explanations, these non-significant findings provide
avenues for future research.
essence, become living works of art. Some members
of this team continued to pursue entrepreneurial
activities within Second Life after the project’s
completion. Other projects created during the
collaboration included a dance club, health center,
beauty parlor, and in-world dating site. All projects
had specific elements that could not be supported in a
2D traditional web environment.
Second, virtual world technology self-efficacy
was added to the Zhao et al. [1] model. Various
scholars have suggested that there may be different
types of entrepreneurs and entrepreneurial ventures
and that a diverse set of skills and processes may be
required for these different types of entrepreneurship
(e.g., [23, 24]). The current study provides evidence
to support this notion. In virtual worlds, a certain
level of technological proficiency is necessary to
build infrastructure and products during the creation
of virtual world businesses. As predicted, virtual
world technology self-efficacy was a significant
predictor of virtual world entrepreneurial selfefficacy, and an indirect predictor of virtual world
entrepreneurial
intentions.
Virtual
world
entrepreneurship requires not only a belief in one’s
ability to create a new business, but also in the ability
to use the technology. This technological prowess is
needed whether or not the entrepreneur is the actual
developer of the project. Thorough knowledge of the
technology is necessary for understanding needs for
virtual goods, and for delivering three-dimensional
information related to physical goods.
Third, consistent with Zhao et al.’s findings in
real world settings, virtual world learning was
indirectly related to virtual world entrepreneurial
intentions through virtual world entrepreneurial selfefficacy. In this case, however, virtual world
entrepreneurial learning was gained during a
collaborative project that allowed for the
establishment of specific learning processes as
indirect predictors of virtual world entrepreneurial
intentions. Beyond this, the current study established
that learning was also related to virtual world
technology self-efficacy. This implies that learning
was important from both a technical and business
perspective.
Risk propensity, gender, and prior virtual world
entrepreneurial experience were not significant
covariates. One explanation for the non-significant
relationship between risk propensity and virtual
world entrepreneurial self-efficacy may be the low
level of investment needed to start a virtual world
business. Participants with low risk propensity may
feel more confident in their entrepreneurial abilities
in these environments.
Consistent with the Zhou et al. (1995) findings,
gender was also not significantly related to virtual
4.1 Limitations and Future Research
Relying on self-report information is a limitation
for any study. Although instances of common method
bias were mitigated by measuring specific variables
at different stages in the project, not all
measurements were separated in time. Measuring
objective virtual world entrepreneurial behavior
during future research would be useful for addressing
this issue.
Additionally, because the number of businesses
that could be created was limited by the number of
prims supported by the regions, the sample size was
relatively modest. While the sample size was
sufficient for detecting medium to large effects,
statistical power was nonetheless reduced. It is
possible that gender, risk propensity, and virtual
world experience may be significantly related to
entrepreneurial self-efficacy in a larger sample.
Furthermore, this study cannot address whether
virtual world entrepreneurship translates to realworld entrepreneurship. Future research should
address this issue. Specifically, the development of
in-world businesses could be used as a training tool
in entrepreneurship courses. Creating businesses inworld can be relatively inexpensive and testing
potential business models in these environments
could potentially provide a risk-free method for
entrepreneurial learning. Longitudinal studies that
follow students after the completion of in-world
projects could then address whether in-world
entrepreneurship learning leads to the development of
real-world entrepreneurship skills.
Similarly, future research should investigate
whether personality traits differ between virtual
world entrepreneurs and real-world entrepreneurs.
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Prior research examining the personality of
entrepreneurs has shown that entrepreneurs score
significantly higher than managers on dimensions of
conscientiousness and openness to experience, and
lower on neuroticism and agreeableness [22]. The
openness to experience dimension could be of
particular interest in the context of virtual world
entrepreneurship, as this variable is described as “a
personality dimension that characterizes someone
who is intellectually curious and tends to seek new
experiences and explore new novel ideas” [22], pg.
261. This could be one of many constructs examined
in future research to determine whether entrepreneurs
who seek to take advantage of the unique and novel
opportunities offered by virtual worlds differ from
real-world entrepreneurs.
Virtual worlds have been described as a “blank
slate” where individuals and organizations can
engage in novel and custom situations [25]. Not all
individuals, however, may possess the characteristics
needed to succeed in this environment. As our
results suggest, individuals who intend to become
entrepreneurs in this environment not only need to
believe that they have the ability to create a new
business in this environment, but must also believe
that they have the ability to use the technology. Our
research provides further evidence that different
types of entrepreneurship require different skills and
cognitive processes, and that this topic requires
further exploration.
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Appendix A
A confirmatory factor analysis was conducted
using AMOS 19 to examine the validity of the virtual
world technology self-efficacy measure. Ten items
were generated by the authors based upon a
comprehensive review of the self-efficacy literature,
and the Second Life knowledge base. Second Life
experts, as well as self-efficacy experts were called
upon to review the items for content validity. To
facilitate the CFA, additional data were collected for
virtual world technology self-efficacy before the
project began (time 0). This data was combined with
the data collected at time 2. In all, 155 cases were
used to produce the final seven items for the measure.
X2 (9, N = 154) = 8.369, ns), CMIN/DF .930, CFI =
.999, NFI = .987, GFI = .982, AGFI = .958, RMSEA
= .10.To provide evidence of discriminant validity,
the virtual world technology self-efficacy and virtual
world entrepreneurship self-efficacy measures were
specified in a two construct model, and a chi-square
differences test was conducted. Specifically, a model
with the covariance path between the two constructs
set to one was compared with the model in which the
covariance path was free to vary. The chi-square
difference was then compared to the critical value for
a chi-square distribution with one degree of freedom.
The test was significant (X2=7.50, p < .05),
indicating that the constructs are discriminant.
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