參考文獻
一、中文部分
1. 中央警察大學資訊密碼曁建構實驗室,網路遊戲中的罪與罰,網路通訊,2003/8。
2. 何佩青,以國內電子遊戲業者現況探討線上遊戲營運模式及發展策略之先期研究,國立台灣大學工業工程所,民國90年。3. 吳采芳,修正TAM模型在線上遊戲行為因素分析之研究,國防管理學院資源管理所,民國90年。4. 吳婉汝,台灣遊戲軟體產業分析,國立台北大學經濟所,民國90年。
5. 宋鎮照,團體動力學,五南出版公司,民國89年。
6. 李天凌,網路商品之定價模式-以線上遊戲為例,國防管理學院資源管理所,民國90年。7. 汪宗憲,線上遊戲產業發展概況,產業經濟,民92.05,頁1-15。8. 卓彥銘,我國線上遊戲代表廠商行銷策略之研究,國立台北大學企管所,民國90年。9. 林子凱,線上遊戲「天堂」之使用者參與動機與滿意度研究,國立成功大學企管所,民國90年。10. 林東清,資訊管理-e化企業的核心競爭力,智勝文化出版社,民國92年。
11. 邱揮立,電玩新戰國時代:電玩遊戲商戰手冊,中華民國對外貿易發展協會,民國92年。
12. 邱皓政,結構方程模式-LISREL的理論、技術與應用,雙葉書廊有限公司,民國92年。
13. 胡啟華,線上遊戲參與者拍賣行為研究,輔仁大學資管所,民國91年。14. 胡嘉彬,線上遊戲之顧客忠誠度行為,國立清華大學科技管理所,民國90年。15. 高陳民,遊戲產業創意企劃人員專業能力及人才培育研究,元智大學資訊傳播所,民國91年。16. 張武成,線上遊戲軟體設計因素與使用者滿意度關聯之研究,淡江大學資管所,民國90年。17. 許晉龍,資訊管理增訂版,儒林出版社,民國92年。
18. 許瓊予、陳佳賢、林于勝,「遊戲產業發展現況與展望」,產業透析:軟體與應用透析,民91.08,頁2-12。
19. 陳怡安,線上遊戲的魅力,資訊社會研究,民國91年7月,頁183-214。20. 陳俊良,線上遊戲顧客忠誠度之研究,國立台灣科技大學資管所,民國90年。21. 陳冠中,「天堂」遊戲參與者之動機、沉迷與交易行為關係之研究,國立中正大學企管所,民國91年。
22. 陳軼辰,線上遊戲參與行為-消費者性別角色認同之探討,長庚大學資管所,民國91年。23. 陳慶峰,從心流(flow)理論探討線上遊戲參與者之網路使用行為,南華大學資訊所,民國90年。24. 傅鏡暉,線上遊戲產業H@ppy書,遠流出版社,民國91年。
25. 黃芳銘,結構方程模式理論與應用,五南圖書出版公司,民國92年。
26. 黃啟豪,線上遊戲使用者滿意度與忠誠度之研究,淡江大學企管系,民國91年。27. 楊士良,我國電腦遊戲之關鍵成功因素,國立交通大學經營管理所,民國91年。28. 楊蘊哲,網路遊戲產業人才培育政策之研究,國立台北師範學院教育傳播與科技研究所,民國91年。29. 葉乃菁,從「群體動力學」探討個人對虛擬社群之接受度-以「Cityfamily」為例,國立台灣科技大學資管所,民國91年。30. 董家豪,網路使用者參與網路遊戲行為之研究,南華大學資訊所,民國90年。31. 潘玉華,電子遊戲專家與生手之表現差異研究,國立交通大學傳播所,民國91年。
32. 鄭明松、陳明光與吳思涵,台灣線上遊戲發展契機之探討,軟體產業通訊,民國91年。33. 盧盛忠、余凱成、徐昶與錢冰鴻,組織行為學-理論與實務,五南圖書出版公司,民國86年。
34. 盧希鵬,電子商務之九陰真經,藍鯨出版社,民國90年。
35. 賴柏偉,虛擬社群:一個想像共同體的形成-以線上角色扮演遊戲【網路創世紀】為例,世新大學傳播所,民國91年。36. 謝博亘,台灣線上遊戲產業運作模式之主要價值活動分析,國立台北大學企管所,民國90年。
二、WWW資源
1. Datamonitor (2001)
http://www.find.org.tw/0105/news/0105_news_disp.asp?news_id=1697
2. Datamonitor (2002) http://www.find.org.tw/0105/news/0105_news_disp.asp?news_id=2290
3. FIND (2003)
http://www.find.org.tw/0105/news/0105_news_disp.asp?news_id=2842
4. IDC (2003)
http://www.find.org.tw/0105/news/0105_news_disp.asp?news_id=2682
5. In-stat (2002)
http://www.find.org.tw/0105/news/0105_news_disp.asp?news_id=2056
6. MIC (2003)
http://www.find.org.tw/0105/focus/0105_focus_disp.asp?focus_id=241
7. NetValue (2002)
http://www.find.org.tw/0105/news/0105_news_disp.asp?news_id=2336
8. Pew Internet (2003)
http://www.find.org.tw/0105/news/0105_news_disp.asp?news_id=2757
三、英文部分
1. Adams, D.A., Nelson, R. R., and Todd, P. A. (1992). Perceives Usefulness, Ease of Use, and Usage of Information Technology: A Replication, MIS Quarterly, 16(2). pp. 227-247.
2. 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). pp. 665-694.
3. Agarwal, R. and Prasad, J. (1999). Are Individual Differences Germane to the Acceptance of New Information Technologies? Decision Sciences, 30(2). pp. 361-391.
4. Ajzen, I. (1985). From intention to actions: a theory of planned behavior, in: J. Kuhl, J. Bechmann (Eds.). Action Control: From Cognition to Behavior, Springer, New York, pp. 11-39.
5. Ajzen, I. (1991). The theory of planned behaviour. Organizational Behavior and Human Decision Process, 50, pp. 179-211.
6. Al-Gahtani, S. S. and King, M. (1999). Attitudes, satisfaction and usage: factors contributing to each in the acceptance of information technology. Behaviour & Information Technology, 18(4). pp. 277-297.
7. Armstrong, A. G. and Hagel, III, J. (1996). The real value of on-line communities. Harvard Business Review, May-June, pp. 134-141.
8. Armstrong, A. G.. and Hagel III, J. (1997). Net Gain: Expanding Markets through Virtual Communities. McKinsey Quarterly, 1. pp. 140-153.
9. Bagozzi, R. P. and Yi, Y. (1988). On the Evaluation of Structural Equation Models, Journal of the Academy of Marketing Science, 16, pp. 74-94.
10. Bajaj, A. and Nidumolu, S. R. (1998). A feedback model to understand information system usage. Information & Management, 33(4). pp. 213-224.
11. Balasubramanian, S. and Mahajan, V. (2001). The economic leverage of the virtual community. International Journal of Electronic Commerce, 5(3). pp. 103-137.
12. Barnatt, C. (1998). Virtual communities and financial services-on-line business potentials and strategic choice. International Journal of Bank Marketing, 16, pp. 161-169.
13. Barnett, L. A. (1990). Playfulness: definition, design, and measurement. Play and Culture, 3, pp. 319-336.
14. Bearden, W. O. and Etzel, M. J. (1982). Reference Group Influence on Product and Brand Purchase Decisions. Journal of Consumer Research, 9, pp. 183-194.
15. Bentler, P. M. and Bonett, D. G.. (1980). Significance tests and goodness of fit in the analysis of covariance structures. Psychological Bulletin, 88, pp. 588-606.
16. Bergeron, F., Raymond, L., Rivard, S. and Gara, M-F. (1995). Determinants of EIS use: Testing a behavioural model. Decision Support System, 14, pp. 131-146.
17. Bhattacherjee, A. (2001). An empirical analysis of the antecedents of electronic commerce service continuance. Decision Support Systems, 32(2). pp. 201-214.
18. Blau, P. (1964). Exchange and Power in Social Life. New York: Wiley.
19. Bock, G. W. and Kim, Y.-G. (2002). Breaking the myths of rewards: an exploratory study of attitudes about knowledge sharing. Information Resources Management Journal, Apr-June, pp. 14-21.
20. Bollen, K. A. and Long, J. S. (1993). Testing structural equations models. Newbury Park, CA: Sage.
21. Briggs, R. O., Adkins, M., Mittleman, D. and Kruse, D. (2003). A technology transition model derived from field investigation of GSS use aboard the U.S.S. CORONADO. Journal of Management Information Systems, 15(3). pp. 151-196.
22. Bushnell, N. (1996). Relationships between fun and the computer business. Communication of the ACM, August, 39(8). pp. 31-37.
23. Chau, P. Y. K. and Hu, P. J.-H. (2002). Investigating healthcare professionals’ decisions to accept telemedicine technology: an empirical test of competing theories. Information & Management, 39, pp. 297-311.
24. Chau, P. Y. K. and Hu, P. J.-H. (2002). Examining a model of information technology acceptance by individual professionals: an exploratory study. Journal of Management Information Systems, 18(4). pp. 191-229.
25. Chen, H, Wigand, R. and Nilan, M. (1999). Optimal experience of web activities. Computers in Human Behavior, 15(5). pp. 585-608.
26. Chen, Lei-da, Gillenson, M. L. and Sherrell, D. L. (2002). Enticing online consumers: an extended technology acceptance perspective. Information & Management, 39, pp. 705-719.
27. Cheung, W., Chang, M. K. and Lai, V. S. (2000). Prediction of Internet and World Wide Web usage at work: a test of an extended Triandis model. Decision Support Systems, 30(1). pp. 83-100.
28. Chin, W.W. and Gopal, A. (1995). Adoption Intention in GSS: Relative Importance of Beliefs. the Data Base for Advances in Information Systems, 26(2&3). pp. 42-63.
29. Csikszentmihalyi, M. (1975). Beyond Boredom and Anxiety, Jossey-Bass, San Francisco, CA.
30. Csikszentmihalyi, M. and LeFevre, J. (1989). Optimal experience in work and leisure. Journal of Personality and Social Psychology, 56(5). pp. 815-822.
31. Csikszentmihalyi, M.and Csikszentmihalyi, I. (1988). Introduction to part IV. In M. Csikszentmihalyi, and I. S. Csikszentmihalyi (Eds.). Optimal experience: Psychological studies of flow in consciousness. New York: Cambridge University Press.
32. Csikzentmihalyi, M. (1990). Flow, the Psychology of Optimal Experience. Harper & Row.
33. David, O. S., Jonathan, L. F., and Letitia, A. P. (1986). Social Psychology. University of California, Los Angels.
34. Davis, F. D. (1989). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Quarterly, 13, pp. 319-339.
35. Davis, F.D. (1993). User acceptance of information technology: system characteristics, user perceptions and behavioral impacts. International Journal of Man-Machine Studies, 38(3), pp. 475-487.
36. Davis, F. D., Bagozzi, R. P. and Warshaw, P. R. (1989). User Acceptance of Computer Technology: A Comparison of Two Theoretical Models. Management Science, 35(8). pp. 982-1003.
37. Davis, F. D., Bagozzi, R. P. and Warshaw, P. R. (1992). Extrinsic and Intrinsic Motivation to Use Computers in the Workplace. Journal of Applied Social Psychology, 22(14). pp. 1111-1132.
38. Deci, E. L. and Ryan, R. M. (1987). Accessibility and stability of predictors in the theory of planned behaviour. Journal of Personality and Social Psychology, 63(5). pp. 754-765.
39. Delone, W. and McLean, E. (1992). Information systems success: the quest for the dependent variable. Information Systems Research, 3(1). pp. 60-95.
40. Dermatis, H., Salke, M., Galanter, M. and Bunt, G.. (2001). The role of social cohesion among residents in a therapeutic community. Journal of Substance Abuse Treatment, 21, pp. 105-110.
41. Deutsch, M. and Gerard, H. B. (1995). A Study of Normative and Informational Social Influences upon Individual Judgment. Journal of Abnormal and Social Psychology, 51, pp.624-636.
42. Dick, A. S. and Basu, K. (1994). Customer loyalty: an integrated conceptual framework. Journal of Academy of Marketing Science, 22(2). pp. 99-113.
43. Dishaw, M.T. and Strong, D. M. (1999). Extending the technology acceptance model with task-technology fit constructs. Information & Management, 36(1). pp. 9-21.
44. Doll, W. J., Hendrickson, A. and Deng, X. (1998). Using Davis’s Perceived Usefulness and Ease-of-use Instruments for Decision Making: A Confirmatory and Multigroup Invariance Analysis. Decision Sciences, 29(4). pp. 839-869.
45. Dumas, J. S. and Redish, J. C. (1999). A Practical Guide to Usability Testing (Revised Edition). Exeter, UK: Intellect.
46. Evans, C. R. and Dion, K. L. (1991). Group cohesion and performance: A meta-analysis. Small Group Research, 22(2), pp. 203-216.
47. Evans, N. J. and Jarvis, P. A. (1980). Group cohesion: a review and re-evaluation. Small Group Behavior, 11, pp. 359-370.
48. Festinge, L. (1950). Informal social communication. Psycholo Rev, 57, pp. 271-282.
49. Fishbein, M. and Ajzen, I. (1975). Belief, Attitude, Intention and Behavior: An Introduction to Theory and Research. Addison-Wesley, Reading, MA.
50. Fornell, C. R. (1982). A second generation of multivariate analysis methods: Vols. I and II. New York: Praeger Special Studies.
51. Fornell, C. R. and Larcker, D. F. (1981). Structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18, pp. 39-50.
52. Gefen, D. (2003). Trust and TAM in online shopping: An integrated model. MIS Quarterly, 27(1). pp. 51-90.
53. Gefen, D. and Straub, D. W. (1997). Gender Differences in the Perception and Use of E-Mail: An Extension to the Technology Acceptance Model. MIS Quarterly, 21(4), pp. 389-400.
54. Ghani, J. A. Supnick, R. and Rooney, P. (1991). The experience of flow in computer-mediated and in face-to-face groups. In Degross, J. I., Benbasat, I., Desanctis, G. and Beath, C. M. (Eds). Proceedings of the Twelfth International Conference on Information Systems, ICIS, New York, NY, pp. 229-237.
55. Ghani, J. A. and Deshpande, S. P. (1994). Task characteristics and the experience of optimal flow in human-computer interaction. Journal of Psychology, 128(4). pp. 381-391.
56. Goodman, P. S., Ravlin, E. and Schminke, M. (1987). Understanding groups in organizations Research. Organization Behavior, 9, pp. 121-173.
57. Goodwin, C. (1987). A Social-Influence Theory of Consumer Cooperation. Advances in Consumer Research, 14, pp. 378-381.
58. Hagel III, J, Armstrong, A. G. (1997). Net Gain: Expanding Markets Through Virtual Communities. Harvard Business School Press.
59. Hair, J. F., Anderson, R. E., Tatham, R. L. and Black, W. C. (1992). Multivariate data analysis with readings. New York: MacMillan.
60. Hayduck, L. A. (1987). Structural Equation Modeling with LISREL (Baltimore, MD: Johns. Hopkings University Press.
61. Hoffman, D. L. and Novak, T. P. (1996). Marketing in Hypermedia Computer-mediated environments: conceptual foundations. Journal of Marketing, 60, pp. 50-68.
62. Hoffman, D. L. and Novak, T. P. (1997). A new marketing paradigm for electronic commerce. The Information Society, 13, pp.43-54.
63. Hogg, M. A. (1992). The social psychology of group cohesiveness: From attraction to social identity. New York University Press, New York.
64. Hong, W., Thong, J. Y. L., Wong, W.-M. and Tam, K.-Y. (2002). Determinants of user acceptance of digital libraries: An empirical examination of individual differences and systems characteristics. Journal of Management Information Systems, 18(3), pp. 97-125.
65. Horton, R.P., Buck, T., Waterson, P. E. and Clegg, C. W. (2001). Explaining intranet use with the technology acceptance model. Journal of Information Technology, 16(4), pp. 237-249.
66. Hu, P.J., Chau, P. K. Y., Sheng, O. R. L. and Tam, K. Y. (1999). Examining the Technology Acceptance Model Using Physician Acceptance of Telemedicine Technology. Journal of Management Information Systems, 16(2), pp. 91-112.
67. Hull, J. G., Lehn, D. A. and Tedlie, J. C. (1991). A General Approach to Testing Multifaceted Personality Constructs. Journal of Personality and Social Psychology, 61(6), pp. 932-945.
68. Hunton, J. E., Arnold, V. and Gibson, D. (2001). Collective user participation: a catalyst for group cohesion and perceived respect. International Journal of Accounting Information Systems, 2, pp. 1-17.
69. Igbaria, M., Schiffman, S. J. and Wieckowshi, T. S. (1994). The respective roles of perceived usefulness and perceived fun in the acceptance of microcomputer technology. Behavior and Information Technology, 13(6). 349-361.
70. Igbaria, M. and Iivari, J. (1995). The Effects of Self-efficacy on Computer Usage. OMEGA: International Journal of Management Science, 23(6). pp. 587-605.
71. Igbaria, M., Parasuraman, S. and Baroudi, J. (1996). A Motivational Model of Microcomputer Usage. Journal of Management Information Systems, 13, pp. 127-143.
72. Joreskog, K. G. and Sorborm, D. (1993). LISREL 8, User’s reference guide. Chincago, IL: Scientific Software International.
73. Joreskog, K. G. and Sorbom, D. (1996). LISREL 8: Users’ reference guide. Chicago: Scientific Software Internatioinal.
74. Karahanna, E. and Straub, D. W. (1999). The psychological origins of perceived usefulness and ease-of-use. Information & Management, 35(4), pp. 237-250.
75. Kardaras, D., Karakostas, B. and Papathanassiou, E. (2003). The potential of virtual communities in the insurance industry in the UK and Greece. International Journal of Information Management, pp. 23, 41-53.
76. Kauffman, R. J., McAndrews, J. and Wang, Y-M. (2000). Opening the “Black Box” of Network Externalities in Network Adoption. Information System Research, 11(1), pp. 61-82.
77. Kelman, H. C. (1961). Process of Opinion Change. Public Opinion Quarterly, 25, pp. 57-78.
78. Kenny, D. and Marshall, J. F. (2000). Contextual marketing: the real business of the internet. Harvard Business Review, Nov-Dec.
79. Klein, H. J. and Mulvey, P. W. (1995). Two investigations of the relationships among group goals, goal commitment, cohesion, and performance. Organizational Behavior and Human Decision Processes, 61(1), pp. 44-53.
80. Korzann, M. L. (2003). Going with the flow: predicting online purchase intentions. Journal of Computer Information Systems, Summer, pp. 25-31.
81. Koufaris, M. (2002). Applying the Technology Acceptance Model and Flow Theory to Online Consumer Behavior. Information System Research, 13(2). pp. 205-223.
82. Kusiak, III, F. J. (2002). Virtual historiography: How history is presented in entertainment-based computer games. PhD Dissertation, TRUMAN STATE UNIVERSITY.
83. Kwon, O. B., Kim, C.-R. and Lee, E. J. (2002). Impact of website information design factors on consumer ratings of web-based auction sites. Behaviour & Information Technology, 21(6), pp. 387-402.
84. Laka, C. (1996). Relational Development in Computer-Supported Groups. MIS Quarterly, June.
85. Lascu, D.-N. and Zinkhan, G. (1999). Consumer conformity: Review and applications for marketing theory and practice. Journal of Marketing Theory and Practice, Summer, 7(3). pp. 1-12.
86. Lederer, A.L., Maupin, D. J., Sena, M. P. and Zhuang, Y. (2000). The technology acceptance model and the World Wide Web. Decision Support Systems, 29(3), pp. 269-282.
87. Lee, G. G. and Pai, J.-C. (2003). Effects of organizational context and inter-group behavior on the success of strategic information systems planning: an empirical study. Behaviur & Information Technology, pp. 1-18.
88. Legris, P. Ingham, J. and Collerette, P. (2003). Why do people use information technology? A critical review of the technology acceptance model. Information & Management, 40, pp. 191-204.
89. Liao, S., Shao. Y. P., Wang, H. and Chen, A. (1999). The adoption of virtual banking: an empirical study. International Journal of Information Management, 19, pp. 63-74.
90. Liker, J. K. and Sindi, A. A. (1997). User Acceptance of Expert systems: A Test of the Theory of Reasoned Action. Journal of Engineering and Technology Management, 14, pp. 147-173.
91. Lin, J. C.-C. and Lu, H. (2000). Toward an understanding of the behavioural intention to use a web site. International Journal of Information Management, 20, pp. 197-208.
92. Loebbecke, C. and Powell, P. (2002). E-business in the entertainment sector: the Egmont case. International Journal of Information Management, 22(4), pp. 307-322.
93. Lu, H. and Yeh, Da-Chin. (1998). Enterprise’s Perceptions on Business Process Re-engineering: A Path Analytic Model. OMEGA: International Journal of Management Science, 26(1), pp. 17-27.
94. Lu, H. and Lin, J. C-C. (2003). Predicting customer behavior in the market-space: a study of Rayport and Sviokla’s framework. Information & Management, 40, pp. 1-10.
95. Lu, H., Yu, H.-J. and Lu, S. S.K. (2001). The effects of cognitive style and model type on acceptance: an empirical study. European Journal of Operational Research, 131, pp. 649-663.
96. Lucas, H. C. and Spitler, V. K. (2000). Implementation in a world of workstations and networks. Information & Management, 38(2), pp. 119-128.
97. Luo, W and Strong, D. (2000). Perceived critical mass effect on groupware acceptance. European Journal of Information Systems, 9(2). pp. 91-103.
98. M2 Communications Ltd., Gaming sites most popular in spain, Europemedia, 2002/4/9.
99. Markus, M. J. (1990). Toward a critical mass theory of interactive media. In Fulk, J. and Steinfield, C. (ed.) Organizations and Communication Technology, Newbury Park: Sage, pp.194-218.
100. Marsh, H. W., Balla, J. R. and McDonald, R. P. (1998). Goodness-of-Fit indices in Confirmatory Factory Analysis: The Effect of Sample Size. Psychological Bulletin, 103, pp. 391-410.
101. Mathieson, K. (1991). Predicting User Intentions: Comparing the Technology Acceptance Model with the Theory of Planned Behavior. Information Systems Research, 2(3), pp. 173-191.
102. Mathieson, K. E. P. and Chin, W. C. (2001). Extending the Technology Acceptance Model: The Influence of Perceived User Resources. the Data Base for Advances in Information Systems, 32(3), pp. 86-113.
103. Methlie, L. B. and Nysveen, H. (1999). Loyalty of on-line bank customers. Journal of Information Technology, 14, pp. 375-386.
104. Moon, J.-W. and Kim, Y-G. (2001). Extending the TAM for a World-Wide-Web context. Information & Management, 38(4), pp. 217-230.
105. Mulligan, J. and Patrovsky, B. (2003). Developing Online Games: An Insider''''''''s Guide. New Riders.
106. Narayanan, V. K. and Nath, R. (1984). The influence of group cohesiveness on some changes induced by flexitime: a quasi-experiement. Journal of Applied Behavioral Science, 20(3), pp. 265-276.
107. Nault, B. R. and Dexter, A. S. (1994). Adoption, transfers, and incentives in a franchise network with positive externalities. Marketing Science, 13(4), pp. 412-423.
108. Ng, H.-I., Pan, Y. J. and Wilson, T. D. (1998). Business Use of the World Wide Web. A Report on Further Investigations, 18(5), pp. 291-314.
109. Novak, P. T. and Hoffman, L. D. (1997). Measuring the flow experience among web users. Interval Research Corporation, July 31.
110. Novak, T. P., Hoffman, D. L. and Yung, Y-F. (2000). Measuring the Customer Experience in Online Environments: A Structural Modeling Approach. Marketing Science, 19(1), pp. 22-42.
111. Oliver, P. E., Marwell, G. and Teixeira, R. (1985). A theory of the critical mass: interdependence, group heterogeneity, and the production of collective action. American Journal of Sociology, 91(3), pp. 522-556.
112. Oliver, R. L. (1997). Satisfaction: A Behavioral Perspective on the Consumer, New York: Irwin/Mcgraw-Hill.
113. Park, W. C. and Lessig, V. P. (1977). Students and Housewives Differences in Susceptibility to Reference Group Influence. Journal of Consumer Research, 4, pp. 102-110.
114. Pine II B.J. and Gilmore, J. H. (1998). Welcome to the Experience Economy. Harvard Business Review, July-August, pp. 97-105.
115. Piper, W. E., Marrache, M., LaCroix, R., Richardsen, M. and Jones, B. D. (1983). Cohesion and a basic bond in groups. Human Relations, 36, pp. 93-108.
116. Pitt, L. F. Watson, R. T. and Kavan, C. B. (1995). Service quality: A measure of information systems effectiveness. MIS Quarterly, 19(2), pp. 173-188.
117. Plouffe, C.R., Hulland, J. and Vandenbosch, M. (2001). Richness versus Parsimony in Modeling Technology Adoption Decisions: Understanding Merchant Adoption of a Smart Cart-Based Payment System. Information Systems Research, 12(2), pp. 208-222.
118. Podsakoff, P. M., MacKenzie, S. B. and Ahearne, M. (1997). Moderating effects of goal acceptance on relationship between group cohesiveness and productivity. Journal of Applied Psychology, 82(6), pp. 974-983.
119. Preece, J. (2000). Online Communities: Designing Usability, Support Sociability. Chichester, UK: Wiley.
120. Preece, J. (2001). Sociability and usability in online communities: determining and measuring success. Behavior & Information Technology, 20(5), pp. 347-356.
121. Rayport, J. F. and Sviokla, J. J. (1994). Managing in the Marketspace. Harvard Business Reivew, Nov-Dec, pp. 141-150.
122. Rettie, R. (2001). An exploration of flow during Internet use, Internet Research: Electronic Networking Application and Policy. 11(2), pp. 103-113.
123. Rheingold, H. (1993). The Virtual Community: Homesteading on the Electronic Frontier. Reading, MA: Addison Wesley.
124. Rice, R. E. and Love, G. (1987). Electronic emotion: socioemotional content in a computer-mediated communication network. Communication Research, 14(1), pp. 85-108.
125. Riemenschneider, C. K., Harrison, D. A. and Jr, P. P. M. (2003). Understanding it adoption decisions in small business: integrating current theories. Information & Management, 40, pp. 269-285.
126. Robbins, S. P. (1992). Essentials of organizational behaviour, Prentice-Hall International.
127. Rogers, E. M. (1995). Diffusion of Innovations. 4th ed., New York, The Free Press.
128. Rogers, E. M. (2003). Diffusion of Innovation. 5th ed., New York, The Free Press.
129. Rollings, A. and Adams, E. (2003). Andrew Rollings and Ernest Adams on Game Design, New Riders.
130. Romm, C., Pliskin, N. and Clarke, R. (1997). Virtual Communities and Society: Toward and Integrative three phase model. International Journal of Information Management, 17(4), pp. 261-270.
131. Rubin, K. H., Fein, G. G., and Vandenbert, B. (1983). Play in P. H. Mussen(Ed.). Handbook of child psychology: Socialization, personality and social development. (Vol. 4). 4th ed., pp. 695-774, New York: Wiley.
132. Schiffman, Leon G. and Leslie Lazar Kanuk (2000). Consumer Behavior, Seventh Edition, Upper Saddle River, New Jersey: Prentice-Hall, Inc.
133. Seibert, S. M. Kraimer, R. and Liden, A. (2001). Social capital theory of career success. Academy of Management Journal, 44 (2), pp. 219-237.
134. Sega, V. L. and Zmud, R. W. (1994). The nature and determinants of IT acceptance, Routinization and infusion, IFIP Transaction A: Computer Science and Technology, A-45, pp. 67-86.
135. Scott, J. E. (1994). The measurement of information systems effectiveness: evaluating a measuring instrument. Proceedings of the Fifteenth International Conference on Information Systems, Vancouver, British Columbia, pp. 111-128.
136. Seibert, S. E., Kraimer, M. L. and Liden, R. C. (2001). A social capital theory of career success. Academy of Management Journal; Briarcliff Manor, pp. 219-237.
137. Seyal, A. H., Rahman, M. N. and Rahim, M. M. (2002). Determinants of academic use of the Internet: a structural equation model. Behavior & Information Technology, 21(1), pp. 71-86.
138. Shapiro, C. and Varian, H. R. (1999). Information Rules: A Strategic Guide to the Network Economy. Harvard Business School Press, Cambridge, MA.
139. Solomon, M. (1999). Consumer behavior, Fourth Edition, Upper Saddle River, New Jersey: Prentic-Hall, Inc.
140. Stafford, M. R. and Stern, B. (2002). Consumer bidding behavior on internet auction sites. International Journal of Electronic Commerce, 7(1), pp. 135-150.
141. Szajna, B. (1994). Software Evaluation and Choice: Predictive Validation of the Technology Acceptance Instrument. MIS Quarterly, 18(3), pp. 319-324.
142. Szajna, B. (1996). Empirical Evaluation of the Revised Technology Acceptance Model. Management Science, 42(1), pp. 85-92.
143. Takahashi, D. (2000). E-Commerce (A Special Report): Industry by Industry --- Don''''''''t Shoot! Everybody figured game sites would be hot; The surprise is who''''''''s playing -- and what. Wall Street Journal, New York; 17.
144. Tan, M. and Teo, T. S. H. (2000). Factors Influencing the Adoption of Internet Banking, Journal of the AIS (1:5). http://jais.isworld.org/articles/1-5/.
145. Taylor, S. and Todd, P. (1995). Understanding Information Technology Usage: A Test of Competing Models. Information Systems Research, 6(2), pp. 144-176.
146. Teo, T.S.H., Lim, V. K. G. and Lai, R.Y.C. (1999). Intrinsic and extrinsic motivation in Internet usage. OMEGA International Journal of Management Science, 27(1), pp. 25-37.
147. Trevino, L. K. and Webster, J. (1992). Flow in computer-mediated communication. Communication Research, 19(5), pp. 539-573.
148. Triandis, H. C. (1980). Beliefs, Attitudes, and Values. Univ. Nebraska Press, Lincoln, pp. 195-259.
149. Vellerand, R. J. (1997). Toward a hierarchical model of intrinsic and extrinsic motivation. Adv. Experiment, Soc. Psych, 29, pp. 271-360.
150. Venkatesh, V. (2000). Determinants of Perceived Ease Of Use: Integrating Control, Intrinsic Motivation, And Emotion Into The Technology Acceptance Model. Information Systems Research, 11(4), pp. 342-365.
151. Venkatesh, V. and Morris, M. G. (2000). Why Don''''''''t Men Ever Stop to Ask for Directions? Gender, Social Influence, and Their Role in Technology Acceptance and Usage Behavior. MIS Quarterly, 24(1), pp. 115-139.
152. Venkatesh, V. and Davis, F. D. (2000). A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies. Management Science, 46(2), pp. 186-204.
153. 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), pp. 297-315.
154. Wachter, R. M., Gupta, J. N.D. and Quaddus, M. A. (2000). IT takes a village: virtual communities in support of education. International Journal of Information Management, 20, pp. 437-489.
155. Wang, E. T. and Seidmann, G. A. (1995). Electronic data interchange: Competitive externalities and strategic implementation policies. Management Science, 41(3), pp. 401-418.
156. Wasko, M. M. and Faraj, S. (2000). “It is what one does”: why people participate and help others in electronic communities of practice. Journal of Strategic Information Systems, 9, pp. 155-173.
157. Webster, J., Trevino, L. K. and Ryan, L. (1993). The dimensionality and correlates of flow in human-computer interactions. Computers in Human Behavior, 9, pp. 411-426.
158. Woszczynski, A. B., Roth, P. L. and Segars, A. H. (2002). Exploring the theoretical foundations of playfulness in computer interactions. Computers in Human Behavior, 18, pp. 369-388.
159. Yoo, Y. and Alavi, M. (2001). Media and Group Cohesion: Relative Influences on Social Presence, Task Participation, and Group Consensus. MIS Quarterly, 25(3), pp. 371-390