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
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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.
[7] accessed March 18, 2010. [8] http://www.businessweek.com/the_thread/techbeat/ar chives/2006/11/second_lifes_fi.html, accessed 4/20/2008, 2008. [9] Compeau, D.R., and Higgins, C.A., "Application of Social Cognitive Theory to Training for Computer Skills", Information Systems Research, 6(2), 1995, pp. 118-143. [10] Compeau, D.R., and Higgins, C.A., "Computer Self-Efficacy - Development of a Measure and Initial Test", MIS Quarterly, 19(2), 1995, pp. 189-211. [11] Marakas, G.M., Yi, M.Y., and Johnson, R.D., "The Multilevel and Multifaceted Character of Computer Self-Efficacy: Toward Clarification of the Construct and an Integrative Framework for Research", Information Systems Research, 9(2), 1998, pp. 126-163. [12] Johnson, R.D., and Marakas, G.M., "Research Report: The Role of Behavioral Modeling in Computer Skills Acquisition: Toward Refinement of the Model", Information Systems Research, 11(4), 2000, pp. 402-417. [13] Tierney, P., and Farmer, S., "Creative SelfEfficacy Development and Creative Performance over Time", Journal of Applied Psychology, 96(2), 2010, pp. 277-293. [14] Bandura, A., Self-Efficacy: The Exercise of Control, W. H. Freeman/Times Books/ Henry Holt & Co., New York, NY, 1997. [15] Chen, G., Gully, S.M., and Eden, D., "Validation of a New General Self-Efficacy Scale", Organizational Research Methods, 41(62-83), 2001, [16] Pajares, F., "Current Directions in Self-Efficacy Research", in (Maehr, M., and Pintrich, P.R., 'eds.'): Advances in Motivation and Achievement, JAI Press, Greenwich, 2004, pp. 1-49. [17] Davis, F., and Yi, M.Y., "Improving Computer Skill Training: Behavior Modeling, Symbolic Mental Rehersal, and the Role of Knowledge Structures", Journal of Applied Psychology, 89(3), 2004, pp. 509523. [18] Gist, M., Rosen, B., and Schwoerer, C., "The Influence of Training Method and Trainee Age on the Acquisition of Computer Skills", Personnel Psychology, 41(1988, pp. 255-265. [19] Gist, M., Schwoerer, C., and Rosen, B., "Effects of Alternate Training Methods on Self-Efficacy and Performance in Computer Software Training", Journal of Applied Psychology, 74(6), 1989, pp. 884891. [20] Bandura, A., "Guide for Constructing SelfEfficacy Scales", in (Pajares, F., and Urdan, T., 'eds.'): Adolescence and Education, Self-Efficacy Beliefs of Adolescents., Information Age Publishing, Greenwich, 2005, pp. 1-39.
5. References [1] Zhao, H., Seibert, S.E., and Hills, G.E., "The Mediating Role of Self-Efficacy in the Development of Entrepreneurial Intentions", Journal of Applied Psychology, 90(6), 2005, pp. 1265-1272. [2] Carr, N., The Shallows, W.W. Norton Company, New York, 2010. [3] Nah, F.F., Eschenbrenner, B., and Dewester, D., "Enhancing Brand Equity through Flow and Telepresence: A Comparison of 2d and 3d Virtual Worlds. ", MIS Quarterly, 35(3), 2011, pp. 731-747. [4] Animesh, A., Pinsonneault, A., Yang, S., and Oh, W., "An Odyssey into Virtual Worlds: Exploring the Impacts of Technological and Spatial Environments on Intention to Purchase Virtual Products. ", MIS Quarterly, 35(3), 2011, pp. 789-810. [5] Goel, L., Johnson, N., Junglas, I., and Ives, B., "From Space to Place: Predicting Users’ Intentions to Return to Virtual Worlds. ", MIS Quarterly, 35(3), 2011, pp. 749-771. [6] Ives, B., and Junglas, I., "Ives, B., & Junglas, I. (2008). Apc Forum: Business Implications of Virtual Worlds and Serious Gaming.", MIS Quarterly Executive, 7(3), 2008, pp. 151-156.
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[21] Bollen, K.A., Structural Equations with Latent Variables, Wiley, new York, 1989. [22] Zhao, H., and Seibert, S.E., "The Big Five Personality Dimensions and Entrepreneurial Status: A Meta-Analytical Review", Journal of Applied Psychology, 91(2), 2006, pp. 259-271. [23] Carland, J.W., Hoy, F., Boulton, W.R., and Carland, J.C., "Differentiating Small Business Owners from Entrepreneurs", Academy of Management Review, 9(1984, pp. 354-359. [24] Miner, J.B., A Psychological Typology of Successful Entrepreneurs, Quorum Books, Westport, CT, 1997. [25] Davis, A., Khazanchi, D., Murphy, J., and Zigurs, I., "Avatars, People, and Virtual Worlds: Foundations for Research in Metaverses", Journal of the Association for Information Systems, 10(2), 2009, pp. 90-117.
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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