From recreational applications to workplace technologies: An empirical study of cross-context IS continuance in the case of virtual worlds

Journal of Information Technology

Volumn 27, Issue 1, 2012, Pages 74-86

  Nevo, Saggi ^a   Nevo, Dorit ^a   Kim, Henry ^a  

^a BA310 ^*  (Canada)

Author keywords

between contexts; cross context IS continuance; post adoption; usage context; virtual worlds; within context

Indexed keywords

BETWEEN-CONTEXTS; IS CONTINUANCE; POST-ADOPTION; USAGE CONTEXT; VIRTUAL WORLDS; WITHIN-CONTEXT;

DIFFUSION;

VIRTUAL REALITY;

EID: 84863069607     PISSN: 02683962     EISSN: 14664437     Source Type: Journal    
DOI: 10.1057/jit.2011.18     Document Type: Article

References (74)

1. Agarwal, R. and Karahanna, E. (2000). Time Flies When you're Having Fun: Cognitive absorption and beliefs about information technology usage, MIS Quarterly 24(4): 665-694.
2. Agarwal, R. and Prasad, J. (1997). The Role ofInnovations Characteristics and Perceived Voluntariness in the Acceptance of Information Technologies, Decision Sciences 28(3): 557-582. (Pubitemid 128000880)
3. Ahuja, M.K. and Thatcher, J.B. (2005). Moving Beyond Intentions and Toward the Theory of Trying: Effects of work environment and gender on postadoption information technology use, MIS Quarterly 29(3): 427-459. (Pubitemid 46063137)
4. Babin, B.J., Darden, W.R. and Griffin, M. (1994). Work and/or Fun: Measuring hedonic and utilitarian shopping value, Journal of Consumer Research 20: 656-664.
5. Backer, T.E. (2000). Finding the Balance: Program Fidelity and Adaptation in Substance Abuse Prevention Report, Center for Substance Abuse Prevention, Washington DC
6. Bagozzi, R.P. (2011). Measurement and Meaning in Information Systems and Organizational Research: Methodological and philosophical foundations, MIS Quarterly 35(2): 261-292.
7. Bagozzi, R.P., Yi, Y. and Phillips, L.W. (1991). Assessing Construct Validity in Organizational Research, Administrative Science Quarterly 36(3): 421-448.
8. Bhattacherjee, A. (2001a). Understanding Information Systems Continuance: An expectation-confirmation model, MIS Quarterly 25(3): 351-370. (Pubitemid 33738440)
9. Bhattacherjee, A. (2001b). An Empirical Analysis of the Antecedents of Electronic Commerce Service Continuance, Decision Support Systems 32(2): 201-214. (Pubitemid 32951237)
10. Bhattacherjee, A. and Premkumar, G. (2004). Understanding Changes in Belief and Attitude Toward Information Technology Usage: A theoretical model and longitudinal test, MIS Quarterly 28(2): 229-254.
11. Bollen, K.A. (2011). Evaluating Effect, Composite, and Causal Indicators in Structural Equation Models, MIS Quarterly 35(2): 359-372.
12. Bowman, D.MJ.S., Balch, J.K., Artaxo, P., Bond, WJ., Carlson, J.M., Cochrane, M.A., D'Antonio, C.M., DeFries, R.S., Doyle, J.C., Harrison, S.P., Johnston, F.H., Keeley, J.E., Krawchuk, M.A., Kull, C.A., Marston, J.B., Moritz, M.A., Prentice, I.C., Roos, C.I., Scott, A.C., Swetnam, T.W., van der Werf, G.R. and Pyne, SJ. (2009). Fire in the Earth System, Science 342: 481-484.
13. Brown, S.A. and Venkatesh, V. (2005). Model of Adoption of Technology in Households: A baseline model test and extension incorporating household life cycle, MIS Quarterly 29(3): 399-426. (Pubitemid 46063136)
14. Burton-Jones, A. and Straub Jr., D.W. (2006). Reconceptualizing System Usage: An empirical approach and empirical test, Information Systems Research 17(3): 228-246. (Pubitemid 44371787)
15. Chin, W.W. (1998). Issues and Opinion on Structural Equation Modeling, MIS Quarterly 22(1): 7-16.
16. Chin, W.W., Marcolin, B.L. and Newsted, P.R. (2003). A Partial Least Squares Latent Variable Modeling Approach for Measuring Interaction Effects: Results from a Monte Carlo Simulation Study and Electronic-Mail Emotion/Adoption Study, Information Systems Research 14(2): 189-217.
17. Cooper, R.B. (2000). Information Technology Development Creativity: A case study of attempted radical change, MIS Quarterly 24(2): 245-276.
18. Davis, A., Murphy, J., Owens, D., Khazanchi, D. and Zigurs, I. (2009). Avatars, People, and Virtual Worlds: Foundations for research in metaverses, Journal of the AIS 10(2): 90-117.
19. Davis, F.D., Bagozzi, R.P. and Warsaw, P.R. (1989). User Acceptance of Computer Technology: A comparison of two theoretical models, Management Science 35(8): 982-1003.
20. Dearing, J.W. and Meyer, G. (1994). An Exploratory Tool for Predicting Adoption Decisions, Science Communication 16(1): 43-57.
21. Deng, L., Turner, D.E., Gehling, R. and Prince, B. (2010). User Experience, Satisfaction, and Continual Usage Intention of IT, European Journal of Information Systems 19(1): 60-75.
22. Dennis, A., Wixom, B.H. and Vandernberg, RJ. (2001). Understanding Fit and Appropriation Effects in Group Support Systems via Meta-analysis, MIS Quarterly 25(2): 167-193. (Pubitemid 33738443)
23. DeSanctis, G. and Poole, M.S. (1994). Capturing the Complexity in Advanced Technology Use - Adaptive structuration theory, Organization Science 5(2): 121-147.
24. Diamantopoulos, A. and Winklhofer, H.M. (2001). Index Construction with Formative Indicators: An alternative to scale development, Journal of Marketing Research 38(2): 269-278.
25. Dillman, D.A. (1999). Mail and Internet Surveys: The tailored design method, New York: John Wiley Company.
26. Doane, D.P. and Seward, L.E. (2010). Applied Statistics in Business & Economics, 3rd edn, New York: McGraw Hill.
27. Dreher, C., Reiners, T., Dreher, N. and Dreher, H. (2009). Virtual Worlds as a Context Suited for Information Systems Education: Discussion of pedagogical experience and curriculum design with reference to second life, Journal of Information Systems Education 20(2): 211-224.
28. Ein-Dor, P. and Segev, E. (1993). A Classification of Information Systems: Analysis and interpretation, Information Systems Research 4(2): 166-204.
29. Eschenbrenner, B.F., Nah, F-H. and Siau, K. (2008). 3-D Virtual Worlds in Education: Applications, benefits, issues, and opportunities, Journal of Database Management 19(4): 91-110.
30. Fornell, C. and Larcker, D.F. (1981). Evaluating Structural Equation Models with Unobservable Variables and Measurement Error: Algebra and statistics, Journal of Marketing Research 18(3): 382-388.
31. Fuller, R.M. and Dennis, A.R. (2009). Does Fit Matter? The impact of task-technology fit and appropriation on team performance in repeated tasks, Information Systems Research 20(1): 2-17.
32. Gilkey, R. and Kilts, C. (2007). Cognitive Fitness, Harvard Business Review 85: 53-66.
33. Hair, J.F., Black, W.C., Babin, BJ. and Anderson, R.E. (2009). Multivariate Data Analysis, 7th edn, Upper Saddle River, NJ: Prentice Hall.
34. Hauser, M. (2009). Origin of the Mind, Scientific American 301(3): 44-51.
35. Hirschman, E.C. and Holbrook, M.B. (1982). Hedonic Consumption: Emerging concepts, methods, and propositions, Journal of Marketing 46: 92-101.
36. Holbrook, M.B. and Hirschman, E.C. (1982). The Experiential Aspects of Consumption: Consumer fantasies, feelings, and fun, Journal ofConsumer Research 9: 132-140.
37. Hong, S., Kim, J. and Lee, H. (2008). Antecedents of Use-Continuance in Information Systems: Toward and integrative view, Journal ofComputer Information Systems 48(3): 61-73.
38. Hong, S.-J. and Tam, K.Y. (2006). Understanding the Adoption ofMultipurpose Information Appliances: The case of Mobile Data Services, Information Systems Research 17(2): 162-179. (Pubitemid 43877855)
39. Ives, B. and Junglas, I. (2008). APC Forum: Business implications ofvirtual worlds and serious gaming, MIS Quarterly Executive 7(3): 151-156.
40. Jarvis, C.B., MacKenzie, S.B. and Podsakoff, P.M. (2003). A Critical Review of Construct Indicators and Measurement Model Misspecification in Marketing and Consumer Research, Journal ofConsumer Research 30(2): 199-218. (Pubitemid 37374305)
41. Jasperson, J., Carter, P.E. and Zmud, R.W. (2005). A Comprehensive Conceptualization of Post-Adoptive Behaviors Associated with Information Technology Enabled Work Systems, MIS Quarterly 29(3): 525-557. (Pubitemid 46063140)
42. Karahanna, E., Straub, D.W. and Chervany, N.L. (1999). Information Technology Adoption Across Time: A cross-sectional comparison of pre-adoption and post-adoption beliefs, MIS Quarterly 23(2): 183-213.
43. Kettinger, WJ. and Grover, V. (1997). The Use of Computer-Mediated Communication in an Organizational Context, Decision Sciences 28(3): 513-555.
44. Kim, S.S. and Malhotra, N.K. (2005). A Longitudinal Model of Continued IS Use: An integrative view of four mechanisms underlying postadoption phenomena, Management Science 51(5): 741-755. (Pubitemid 40867141)
45. Kock, N. (2008). E-Collaboration and E-Commerce in Virtual Worlds: The potential of second life and world of warcraft, International Journal of E-Collaboration 4(3): 1-13.
46. LaBrosse, M. (2008). Managing Virtual Teams, Employment Relations Today 35(2): 81-86.
47. Limayem, M. and Cheung, C.M.K. (2008). Understanding Information Systems Continuance: The case of internet-based learning technologies, Information and Management 45(4): 227-232. (Pubitemid 351615161)
48. Limayem, M., Hirt, S.G. and Cheung, C.M.K. (2007). How Habit Limits the Predictive Power of Intention: The case of information systems continuance, MIS Quarterly 31(4): 705-737. (Pubitemid 351153309)
49. MacKenzie, S.B., Podsakoff, P.M. and Podsakoff, N.P. (2011). Construct Measurement and Validation Procedures in MIS and Behavioral Research: Integrating new and existing techniques, MIS Quarterly 35(2): 293-334.
50. McCrae, R.R. and Costa Jr., P.T. (1983). Social Desirability Scales More Substance than Style, Journal ofConsulting and Clinical Psychology 5(1): 882-888. (Pubitemid 14183156)
51. Messinger, P.R., Stroulia, E., Lyons, K., Bone, M., Niu, R.H., Smirnov, K. and Perelgut, S. (2009). Virtual Worlds - Past, present, and future: New directions in social computing, Decision Support Systems 47(3): 204-228.
52. Mittal, B. (1987). A Framework for Relating Consumer Involvement to Lateral Brain Functioning, Advances in Consumer Research 14: 41-45.
53. Orlikowski, WJ. (2000). Using Technology and Constituting Structures: A practice lens for studying technology in organizations, Organization Science 11(4): 404-428.
54. Ortiz de Guinea, A. and Markus, M.L. (2009). Why Break the Habit of a Lifetime? Rethinking the roles of intention, habit, and emotion in continuing information technology use, MIS Quarterly 33(3): 433-444.
55. Overby, E. (2008). Process Virtualization Theory and the Impact of Information Technology, Organization Science 19(2): 277-292.
56. Parameswaran, M. and Whinston, A.B. (2007). Research Issues in Social Computing, Journal of the AIS 6: 336-350.
57. Petter, S., Straub, D. and Rai, A 2007. Specifying Formative Constructs in Information Systems Research, MIS Quarterly 31(4): 623-656. (Pubitemid 351153306)
58. Podsakoff, P., MacKenzie, S.B., Lee, J. and Podsakoff, N. (2003). Common Method Biases in Behavioral Research: A critical review of the literature and recommended remedies, Journal of Applied Psychology 88: 879-903. (Pubitemid 37239703)
59. Pollitt, D. (2008). Learn-While-You-Play Programme Gets IBM Recruits Up to Speed, Training & Management Development Methods 22(1): 401-403.
60. Rogers, E. (2003). Diffusion ofInnovations, 5th edn, New York, NY: Free Press.
61. Salancik, G.R. and Pfeffer, J. (1977). An Examination of Need-Satisfaction Models of Job Attitudes, Administrative Science Quarterly 22: 427-456.
62. Salisbury, D., Chin, W.W., Gopal, A. and Newsted, P.R. (2002). Research Report: Better theory through measurement - Developing a scale to capture consensus on appropriation, Information Systems Research 13(1): 91-105.
63. Shang, R-A., Chen, Y-C. and Shen, L. (2005). Extrinsic Versus Intrinsic Motivations for Consumers to Shop Online, Information & Management 42: 401-413.
64. Straub, D., Boudreau, M-C. and Gefen, D. (2004). Validation Guidelines for IS Positivist Research, Communications of the AIS 13: 380-427.
65. Torrence, R. (2008). Thinking Big about Small Tools, Archeological Papers of the American Anthropological Association 12(1): 179-189.
66. Trevino, L.K. and Webster, J. (1992). Flow in Computer-Mediated Communication: Electronic mail and voice mail evaluation and impacts, Communication Research 19(5): 539-573.
67. Van der Heijden, H. (2004). User Acceptance ofHedonic Information Systems, MIS Quarterly 28(4): 695-704.
68. Venkatesh, V. and Brown, S.A. (2001). A Longitudinal Investigation ofPersonal Computers in Homes: Adoption determinants and emerging challenges, MIS Quarterly 25(1): 71-102.
69. Venkatesh, V., Brown, S.A., Maruping, L.M. and Bala, H. (2008). Predicting Different Conceptualizations of System Use: The competing roles of behavioral intention, facilitating conditions, and behavioral expectations, MIS Quarterly 32(3): 483-502.
70. Venkatesh, V., Speier, C. and Morris, M.G. (2002). User Acceptance Enablers in Individual Decision Making About Technology: Toward an integrated model, Decision Sciences 33(2): 216-297.
71. Wakefield, R. and Whitten, D. (2006). Mobile Computing: A user study on hedonic/utilitarian mobile device usage, European Journal of Information Systems 15: 292-300. (Pubitemid 44146928)
72. Weick, K.E. (1998). Improvisation as a Mindset for Organizational Analysis, Organization Science 9(5): 543-555.
73. Wild, T.C., Kuiken, D. and Schopflocher, D. (1995). The Role of Absorption in Experiential Involvement, Journal of Personality and Social Psychology 69(3): 569-579.
74. Wixom, B.H. and Todd, P.A. (2005). A Theoretical Integration ofUser Satisfaction and Technology Acceptance, Information Systems Research 16(1): 85-102. (Pubitemid 40701110)