A meta-analysis of the technology acceptance model: Investigating subjective norm and moderation effects

Information and Management

Volumn 44, Issue 1, 2007, Pages 90-103

  Schepers, Jeroen ^a   Wetzels, Martin ^b  

^a EINDHOVEN UNIVERSITY OF TECHNOLOGY   (Netherlands)

^b MAASTRICHT UNIVERSITY   (Netherlands)

Author keywords

Culture; Meta analysis; Moderator analysis; Structural equation modeling; Subjective norm; Technology acceptance model

Indexed keywords

META ANALYSIS; MODERATOR ANALYSIS; STRUCTURAL EQUATION MODELING; TECHNOLOGY ACCEPTANCE MODEL (TAM);

DATA REDUCTION; INFORMATION SCIENCE; METADATA;

INFORMATION MANAGEMENT;

EID: 33845962305     PISSN: 03787206     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.im.2006.10.007     Document Type: Article

References (93)

1. D.A. Adams, R.R. Nelson, P.A. Todd, Perceived usefullness, ease of use, and usage of information, MIS Quarterly 16 (2), 1992, pp. 227-247.
2. R. Agarwal, E. Karahanna, Time flies when you're having fun: cognitive absorption and beliefs about information technology usage, MIS Quarterly 24 (4), 2000, pp. 665-694.
3. R. Agarwal, J. Prasad, The antecedents and consequents of user perceptions in information technology adoption, Decision Support Systems 22 (1), 1998, pp. 15-29.
4. A. Agrell, R. Gustafson, in: M.A. West (Ed.), Innovation and Creativity in Work Groups, Handbook of Work Group Psychology, John Wiley & Sons, Chichester, 1996, pp. 317-343.
5. I. Ajzen, The theory of planned behavior, Organizational Behavior and Human Decision Processes 50 (2), 1991, pp. 179-211.
6. M.A. Al-Khaldi, I.M. Al-Jabri, The relationship of attitudes to computer utilization: new evidence from a developing nation, Computers in Human Behavior 14 (1), 1998, pp. 23-42.
7. A.M. Aladwani, The development of two tools for measuring the easiness and usefulness of transactional web sites, European Journal of Information Systems 11 (3), 2002, pp. 223-234.
8. M. Anandarajan, M. Igbariam, U.P. Anakwe, IT acceptance in a less-developed country: a motivational factor perspective, International Journal of Information Management 22 (1), 2002, pp. 47-65.
9. S.P. Brown, R.A. Peterson, Antecedents and consequences of salesperson job satisfaction: meta-analysis and assessment of causal effects, Journal of Marketing Research 30 (1), 1993, pp. 63-77.
10. P.V. Chang, The validity of an extended technology acceptance model (TAM) for predicting intranet/portal usage, Master Thesis, University of North Carolina, 2004.
11. P.Y.K. Chau, P.J.H. Hu, Investigating healthcare professionals' decisions to accept telemedicine technology: an empirical test of competing theories, Information & Management 39 (4), 2002, pp. 297-311.
12. C.M.K. Cheung, M.K.O. Lee, Z. Chen, Using the Internet as a learning medium: an exploration of gender difference in the adoption of FaBWeb, in: Proceedings of the 35th Hawaii International Conference on System Science, 2002, pp. 475-483.
13. J. Choi, L.V. Geistfeld, A cross-cultural investigation of consumer e-shopping adoption, Journal of Economic Psychology 25 (6), 2004, pp. 821-838.
14. J. Cohen, Statistical Power Analysis for the Behavioral Sciences, 2nd ed., Erlbaum, Hillsdale, NJ, 1988.
15. M.H. Cooper, Statistically combining independent studies: a meta-analysis of sex differences in conformity research, Journal of Personality and Social Psychology 37 (1), 1979, pp. 131-146.
16. P.A. Dabholkar, Consumer evaluations of new technology-based self-service options: an investigation of alternative models of service quality, International Journal of Research in Marketing 13 (1), 1996, pp. 29-51.
17. F.D. Davis, R.P. Bagozzi, P.R. Warshaw, User acceptance of computer technology: a comparison of two theoretical models, Management Science 35 (8), 1989, pp. 982-1003.
18. S. Devaraj, M. Fan, R. Kohli, Antecedents of B2C channel satisfaction and preference: validating e-commerce metrics, Information Systems Research 13 (3), 2002, pp. 316-333.
19. T. Dyba, N.B. Moe, E.M. Mikkelsen, An empirical investigation on factors affecting software developer acceptance and utilization of electronic process guides, in: Proceedings of the 10th IEEE International Symposium on Software Metrics (METRICS'04), 2004, pp. 220-231.
20. R. Dye, The buzz on buzz, Harvard Business Review 78 (6), 2000, pp. 139-146.
21. M.S. Featherman, P.A. Pavlou, Predicting e-services adoption: a perceived risk facets perspective, International Journal of Human-Computer Studies 59 (4), 2003, pp. 451-474.
22. M. Fishbein, I. Ajzen, Belief Attitude, Intention and Behavior: An Introduction to Theory and Research, Addison-Wesley, Reading, MA, 1975.
23. D. Gefen, TAM of just plain habit: a look at experienced online shoppers, Journal of End User Computing 15 (3), 2003, pp. 1-13.
24. M. Gelderman, The relation between user satisfaction, usage of information systems and performance, Information & Management 34 (1), 1998, pp. 11-18.
25. L.V. Hedges, I. Olkin, Statistical Methods for Meta-analysis, Academic Press, Orlando, FL, 1985.
26. R. Henderson, M.J. Divett, Perceived usefullness, ease of use and electronic supermarket use, International Journal of Human-Computer Studies 59 (3), 2003, pp. 383-395.
27. R. Henderson, D. Rickwood, P. Roberts, The beta test of an electronic supermarket, Interacting with Computers 10 (4), 1998, pp. 385-399.
28. G. Hofstede, Cultures and Organizations: Software of the Mind, Mc-Graw Hill, London, 1991.
29. C.L. Hsu, H.P. Lu, Why do people play on-line games? An extended TAM with social influences and flow experience Information & Management 41 (7), 2004, pp. 853-868.
30. L. Hu, P.M. Bentler, Cutoff criteria for fit indexes in covariance structure analysis: conventional criteria versus new alternatives, Structural Equation Modeling 6 (1), 1999, pp. 1-55.
31. J.E. Hunter, F.L. Schmidt, G.B. Jackson, Cumulating Research Findings Across Studies, Sage, Beverly Hills, CF, 1982.
32. M. Igbaria, J. Iivari, The effects of self-efficacy on computer usage, Omega 23 (6), 1995, pp. 587-605.
33. M. Igbaria, J. Iivari, H. Maragahh, Why do individuals use computer technology? A Finnish case study Information & Management 29 (5), 1995, pp. 227-238.
34. M. Igbaria, S. Parasuraman, J.J. Baroudi, A motivational model of microcomputer usage, Journal of Management Information Systems 13 (1), 1996, pp. 127-144.
35. M. Igbaria, N. Zinatelli, P. Cragg, A.L.M. Cavaye, Personal computing acceptance factors in small firms: a structural equation model, MIS Quarterly 21 (3), 1997, pp. 279-305.
36. L.R. James, S.A. Mulaik, J.M. Brett, Causal Analysis: Assumptions Models and Data, Sage, Beverly Hills, CA, 1982.
37. K.G. Jöreskog, D. Sörbom, LISREL 8 User's Reference Guide, Scientific Software, Chicago, IL, 1993.
38. H.C. Kelman, Compliance, identification, and internalization: Three processes of attitude change? Journal of Conflict Resolution 2 (1), 1958, pp. 51-60.
39. M. Koufaris, Applying the technology acceptance model and flow theory to online consumer behavior, Information Systems Research 13 (2), 2002, pp. 205-223.
40. A. Lau, Y. Yen, P.Y.K. Chau, Adoption of on-line trading in the Hong Kong financial market, Journal of Electronic Commerce Research 2 (2), 2001, pp. 58-65.
41. C. Lee, R.T. Green, Cross-Cultural Examination of the Fishbein Behavioral Intentions Model, Journal of International Business Studies 22 (2), 1991, p. p289.
42. Y. Lee, G. O'Connor, New product launch strategy for network effects products, Journal of the Academy of Marketing Science 31 (3), 2003, pp. 241-255.
43. P. Legris, J. Ingham, P. Collerette, Why do people use information technology? A critical review of the technology acceptance model Information & Management 40 (3), 2003, pp. 191-204.
44. W. Lewis, R. Agarwal, V. Sambamurthy, Sources of influence on beliefs about information technology use: an empirical study of knowledge workers, MIS Quarterly 27 (4), 2003, pp. 657-678.
45. S.S. Liaw, H.M. Huang, An investigation of user attitudes toward search engines as an information retrival tool, Computers in Human Behavior 19 (6), 2003, pp. 751-765.
46. K.S. Lim, Validation of the technology acceptance model with academic users, Decision Sciences Institute 2002 Annual Meeting Proceedings, 2002, pp. 1402-1407.
47. J.C.-C. Lin, H. Lu, Towards an understanding of the behavioural intention to use a web site, International Journal of Information Management 20 (3), 2000, pp. 197-208.
48. M.W. Lipsey, D.B. Wilson, Practical Meta-analysis: Applied Social Research Series, (vol. 49), Sage, Thousand Oaks, CA, 2000.
49. S.-P. Liu, D. Tucker, C.E. Koh, L. Kappelman, Standard user interface in e-commerce sites, Industrial Management and Data Systems 103 (8/9), 2003, pp. 600-610.
50. H. Lou, W. Luo, D. Strong, Perceived critical mass effect on groupware acceptance, European Journal of Information Systems 9 (2), 2000, pp. 91-103.
51. J. Lu, C. Liu, C.S. Yu, J.E. Yao, Exploring factors associated with wireless Internet via mobile technology acceptance in mainland China, Communications of the International Information Management Association 3 (1), 2003, pp. 101-120.
52. Q. Ma, L. Liu, The technology acceptance model: a metaanalysis of empirical findings, Journal of Organizational and End User Computing 16 (1), 2004, pp. 59-72.
53. W.W.K. Ma, T.H.K. Clark, Online course acceptance: a paired sample experiment, in: Proceedings of the 2003 TechEd Ontario International Conference and Exposition, 2003.
54. Y. Malhotra, D.F. Galletta, Extending the technology acceptance model to account for social influence: theoretical bases and empirical validation, in: Proceedings of the 32nd Hawaii International Conference on System Sciences, 1999.
55. E. Mao, M. Srite, J.B. Thatcher, O. Yaprak, A research model for mobile phone service behaviors: empirical validation in the U.S. and Turkey, Journal of Global Information Technology Management 8 (4), 2005, pp. 7-28.
56. S. McCoy, A. Everard, B.M. Jones, An examination of the technology acceptance model in Uruguay and the US: a focus on culture, Journal of Global Information Technology Management 8 (2), 2005, pp. 27-45.
57. W. Money, A. Turner, Assessing knowledge management system user acceptance with the technology acceptance model, International Journal of Knowledge Management 1 (1), 2005, pp. 8-26.
58. W. Oakes, External validity and the use of real people as subjects, American Psychologist 27 (7), 1972, pp. 959-962.
59. H.G. Osburn, Coefficient alpha and related internal consistency reliability coefficients, Psychological Methods 5 (3), 2000, pp. 343-355.
60. P.A. Pavlou, Consumer acceptance of electronic commerce: integrating trust and risk with the technology acceptance model, International Journal of Electronic Commerce 7 (3), 2003, pp. 101-134.
61. R. Pennington, A. Kelton, D.D. DeVries, A preliminary study of the mediating effect of qualitative overload on perceived ease of use and intention in the technology acceptance model, in: Proceedings of the 2005 AAA-IS Section Mid-Year Conference, 2004.
62. R.A. Peterson, On the use of college students in social science research: insights from a second-order meta-analysis, Journal of Consumer Research 28 (3), 2001, pp. 450-461.
63. C.R. Plouffe, M. Vandenbosch, J. Hulland, Intermediating technologies and multi-group adoption: a comparison of consumer and merchant adoption intentions toward a new electronic payment system, The Journal of Product Innovation Management 18 (2), 2001, pp. 65-81.
64. C.K. Riemenschneider, D.A. Harrison, P.P. Mykytn Jr., Understanding IT adoption decisions in small business: Integrating current theories, Information & Management 40 (4), 2003, pp. 269-285.
65. P. Roberts, R. Henderson, Information technology acceptance in a sample of government employees: a test of the technology acceptance model, Interacting with Computers 12 (5), 2000, pp. 427-443.
66. D.C. Robertson, Social determinants of information systems use, Journal of Management Information Systems 5 (4), 1989, pp. 55-71.
67. L. Robinson Jr., G.W. Marshall, M.B. Stamps, Sales force use of technology: antecedents to technology acceptance, Journal of Business Research 58 (12), 2005, pp. 1623-1631.
68. E.M. Rogers, The Diffusion of Innovations, 3rd ed., Free Press, New York, 1983.
69. R. Rosenthal, Writing meta-analytic reviews, Psychological Bulletin 118 (2), 1995, pp. 183-192.
70. D.P. Schultz, The human subject in psychological research, Psychological Bulletin 72 (5), 1969, pp. 214-228.
71. D.O. Sears, College sophomores in the laboratory: influences of a narrow data base on social psychology's view of human nature, Journal of Personality and Social Psychology 51 (3), 1986, pp. 515-530.
72. H.M. Selim, An empirical investigation of student acceptance of course websites, Computers & Education 40 (4), 2003, pp. 343-360.
73. M.R. Stafford, B. Stern, Consumer bidding behavior on Internet auction sites, International Journal of Electronic Commerce 7 (1), 2002, pp. 135-150.
74. Standish Group Inc., CHAOS: A Recipe for Success, 1998.
75. D. Straub, M. Keil, W. Brenner, Testing the technology acceptance model across cultures: a three country study, Information & Management 33 (1), 1997, pp. 1-11.
76. A.C. Stylianou, S.S. Robbins, P. Jackson, Perceptions and attitudes about eCommerce development in China: an exploratory study, Journal of Global Information Management 11 (2), 2003, pp. 31-47.
77. B. Suh, I. Han, Effect of trust on customer acceptance of Internet banking, Electronic Commerce Research and Applications 1 (3), 2002, pp. 247-263.
78. B. Szajna, Empirical evaluation of the revised technology acceptance model, Management Science 42 (1), 1996, pp. 85-92.
79. S. Taylor, P.A. Todd, Understanding information technology usage: a test of competing models, Information Systems Research 6 (2), 1995, pp. 144-176.
80. H.H. Teo, H.C. Chan, K.K.Wei, Z. Zhang, Evaluating information accessibility and community adaptivity features for sustaining virtual learning communities, International Journal of Human-Computer Studies 59 (5), 2003, pp. 671-697.
81. T.S.H. Teo, V.K.G. Lim, R.Y.C. Lai, Intrinsic and extrinsic motivation in Internet usage, Omega 27 (1), 1999, pp. 25-37.
82. H.C. Triandis, Attitude and Attitude Change, John Wiley & Sons, New York, 1971.
83. E.M. Van Raaij, J.J.L. Schepers, The acceptance and use of a virtual learning environment in China, Computers & Education, in press, doi:10.1016/j.compedu.2006.09.001.
84. V. Venkatesh, Determinants of perceived ease of use: Integrating control, intrinsic motivation, and emotion into the technology acceptance model, Information Systems Research 11 (4), 2000, pp. 342-365.
85. V. Venkatesh, F.D. Davis, A theoretical extension of the technology acceptance model: four longitudinal field studies, Management Science 46 (2), 2000, pp. 186-204.
86. V. Venkatesh, M.G. Morris, 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), 2000, pp. 115-139.
87. V. Venkatesh, M.G. Morris, G.B. Davis, F.D. Davis, User acceptance of information technology: toward a unified view,MIS Quarterly 27 (3), 2003, pp. 425-478.
88. C. Viswesvaran, D.S. Ones, Theory testing: combining psychometric meta-analysis and structural equations modeling, Personnel Psychology 48 (4), 1995, pp. 865-883.
89. J.E. Woodrow, The influence of programming training on the computer literacy and attitudes of pre-service teachers, Journal of Research on Computing in Education 25 (2), 1992, pp. 200-218.
90. J.H. Wu, S.C. Wang, What drives mobile commerce? An empirical evaluation of the revised technology acceptance model Information & Management 42 (5), 2005, pp. 719-729.
91. M.Y. Yi, Y. Hwang, Predicting the use of web-based information systems: self-efficacy, enjoyment, learning, goal orientation, and the technology acceptance model, International Journal of Human-Computer Studies 59 (4), 2003, pp. 431-449.
92. Y. Yi, L.L. Tung, Z. Wu, Incorporating technology readiness (TR) into TAM: are individual traits important to understand technology acceptance? Diffusion Interest Group in Information Technology (DIGIT) Workshop Seattle, 2003.
93. A.H.K. Yuen, W.W.K. Ma, Gender differences in teacher computer acceptance, Journal of Technology and Teacher Education 10 (3), 2002, pp. 365-382.