Intentions to use information technologies: An integrative model

End User Computing Challenges and Technologies: Emerging Tools and Applications

Volumn , Issue , 2007, Pages 79-101

  Thompson, Ron ^a   Compeau, Deborah ^b   Higgins, Chris ^b   Lupton, Nathan ^b  

^a WAKE FOREST UNIVERSITY   (United States)

^b UNIVERSITY OF WESTERN ONTARIO   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 76649118206     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.4018/978-1-59904-295-4.ch006     Document Type: Chapter

References (50)

1. Agarwal, R., & 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., & Prasad, J. (1998, June). A conceptual and operational definition of personal innovativeness in the domain of information technology. Information Systems Research, 9(2), 204-215.
3. Agarwal, R., Sambamurthy, V., & Stair, R.M. (2000, December). Research report: The evolving relationship between general and specific computer self-efficacy: An empirical assessment. Information Systems Research, 11(4), 418-430.
4. Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50, 179-211.
5. Bandura, A. (1986). Social foundations of thought and action. Englewood Cliffs, NJ: Prentice Hall.
6. Bandura, A. (1997). Self-efficacy: The exercise of control. New York: W.H. Freeman & Co.
7. Barclay, D.W., Higgins, C.A., & Thompson, R.L. (1995). The partial least squares approach to causal modeling: Personal computer adoption and use as an illustration. Technology Studies: Special Issue on Research Methodology, 2(2), 285-324.
8. Bhattacherjee, A., & Premkumar, G. (2004). Understanding changes in belief and attitude toward information technology usage: A theoretical model and longitudinal test. Management Information Systems Quarterly, 28(2), 229-254.
9. Chau, P., & Hu, P. (2001). Information technology acceptance by individual professionals: A model comparison approach. Decision Sciences, 32(4), 699-719.
10. Chin, W.W., & Frye, T. (2001). PLS-Graph (Version 03.00). Soft Modeling Inc.
11. Cohen, J. (1988). Statistical power analysis for the behavioral sciences. Hillside, NJ: L. Erlbaum Associates.
12. Compeau, D.R., & Higgins, C.A. (1995a). Application of social cognitive theory to training for computer skills. Information Systems Research, 6(2), 118-143.
13. Compeau, D.R., & Higgins, C.A. (1995b). Computer self-efficacy: Development of a measure and initial test. MIS Quarterly, 19(2), 189-211.
14. Compeau, D.R., Higgins, C.A., & Huff, S. (1999). Social cognitive theory and individual reactions to computing technology: A longitudinal study. MIS Quarterly, 23(2), 145-158.
15. Compeau, D., Marcolin, B., & Kelley, H. (2001). Generalizability of technology acceptance research using student subjects. In A. Ramirez (Ed.), Proceedings of the Administrative Science Association of Canada, 22(4), 35-47.
16. Davis, F.D., Bagozzi, R.P., & Warshaw, P.R. (1989, August). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35(8), 983-1003.
17. Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intentions and behavior: An introduction to theory and research. Boston: Addison-Wesley.
18. Ford, J., Smith, E., Weissbein, D., Gully, S., & Salas, E. (1998). Relationships of goal orientation, metacognitive activity, and practice strategies with learning outcomes and transfer. Journal of Applied Psychology, 83, 218-233.
19. Fornell, C., & Larcker, D. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18, 39-50.
20. Gundlach, M.J., & Thatcher, J.B. (2000). Examining the multi-dimensionality of computer self-efficacy: An empirical test. Unpublished manuscript, Florida State University.
21. Hackbarth, G., Grover, V., & Yi, M.Y. (2003). Computer playfulness and anxiety: Positive and negative mediators of the system experience effect on perceived ease of use. Information and Management, 40, 221-232.
22. Hasan, B. (2006). Delineating the effects of general and system-specific computer self-efficacy beliefs on IS acceptance. Information and Management, 43, 565-571.
23. Hsu, M-H., & Chiu, C-M. (2004). Internet self-efficacy and electronic service acceptance. Decision Support Systems, 38, 369-381.
24. Jasperson, J., Carter, P.E., & Zmud, R.W. (2005). A comprehensive conceptualization of postadoptive behaviors associated with information technology enabled work systems. MIS Quarterly, 29(3), 525-557.
25. Karahanna, E., Straub, D.W., & Chervany, N.L. (1999, June). Information technology adoption across time: A cross-sectional comparison of pre-adoption and post-adoption beliefs. MIS Quarterly, 23(2), 183-213.
26. Klein, K.J., & Sorra, J.S. (1996). The challenge of innovation implementation. Academy of Management Review, 21, 1055-1080.
27. Larsen, T.J., & Sorebo, O. (2005). Impact of personal innovativeness on the use of the Internet among employees at work. Journal of Organizational and End User Computing, 17(2), 43-63.
28. Lippert, S.K., & Forman, H. (2005). Utilization of information technology: Examining cognitive and experiential factors of post-adoption behavior. IEE Transactions on Engineering Management, 52(3), 363-381.
29. Lu, J., Yao, J.E., & Yu, C.-S. (2005). Personal innovativeness, social influences and adoption of wireless Internet services via mobile technology. Strategic Information Systems, 14, 245-268.
30. Marcolin, B.L., Compeau, D.R., Munro, M.C., & Huff, S.L. (2000, March). Assessing user competence: Conceptualization and measurement. Information Systems Research, 11(1), 37-60.
31. Mathieson, K., Peacock, E., & Chin, W.W. (2001). Extending the technology acceptance model: The influence of perceived user resources. The DATA BASE for Advances in Information Systems, 32(3), 86-112.
32. McFarland, D.J., & Hamilton, D. (2006). Adding contextual specificity to the technology acceptance model. Computers in Human Behavior, 22, 427-447.
33. Morris, M.G., Venkatesh, V., & Ackerman, P.L. (2005). Gender and age differences in employee decisions about new technology: An extension to the theory of planned behavior. IEEE Transactions on Engineering Management, 52(1), 69-84.
34. Plouffe, C.R., Hulland, J.S., & Vandenbosch, M. (2001). Richness versus parsimony in modelling technology adoption decisions: Understanding merchant adoption of a smart card-based payment system. Information Systems Research, 12(2), 208-222.
35. Riemenschneider, C.K., Harris, D.A., & Mykytyn, P.P., Jr. (2003). Understanding IT adoption decisions in small business: Integrating current theories. Information and Management, 40, 269-285.
36. Seddon, P.B. (1997). A respecification and extension of the DeLone and McLean model of IS success. Information Systems Research, 8(3), 240-253.
37. Sun, H., & Zhang, P. (2006). The role of moderating factors in user technology acceptance. International Journal of Human-Computer Studies, 64, 53-78.
38. Szajna, B. (1996, January). Empirical evaluation of the revised technology acceptance model. Management Science, 42(1), 85-92.
39. Taylor, S., & Todd, P.A. (1995a, June). Understanding information technology usage: A test of competing models. Information Systems Research, 6(2), 144-176.
40. Taylor, S., & Todd, P.A. (1995b). Assessing IT usage: The role of prior experience. MIS Quarterly, 19, 561-570.
41. Thompson, R.L., Higgins, C.H., & Howell, J.M. (1991, March). Towards a conceptual model of utilization. MIS Quarterly, 15(1), 125-143.
42. Thompson, R.L., Higgins, C.H., & Howell, J.M (1994). Influence of experience on personal computer utilization: Testing a conceptual model. Journal of Management Information Systems, 11, 167-187.
43. Triandis, H.C. (1980). Values, attitudes and interpersonal behavior. In H.E. Howe (Ed.), Nebraska Symposium on Motivation, 1979: Beliefs, Attitudes and Values (pp. 195-259). Lincoln, NE: University of Nebraska Press, 195-259.
44. 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), 342-365.
45. Venkatesh, V. (2006). Where to go from here? Thoughts on future directions for research on individual-level technology adoption with a focus on decision making. Decision Sciences, 37(4), 497-518.
46. Venkatesh, V., & Davis, F.D. (1996). A model of the antecedents of perceived ease of use: Development and test. Decision Sciences, 27(3), 451-482.
47. Venkatesh, V., & Davis, F.D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46, 186-204.
48. Venkatesh, V., Morris, M.G., Davis, G.B., & Davis, F.D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27, 425-478.
49. Workman, M. (2005). Expert decision system use, disuse and misuse: A study using the theory of planned behavior. Computers in Human Behavior, 21, 211-231.
50. Yi, M.Y., Fiedler, K.D., & Park, J.S. (2006). Understanding the role of individual innovativeness in the acceptance of IT-based innovations: Comparative analyses of models and measures. Decision Sciences, 37(3), 393-426.