The effects of persuasive messages on system acceptance

PACIS 2011 - 15th Pacific Asia Conference on Information Systems: Quality Research in Pacific

Volumn , Issue , 2011, Pages

  Li, Chia Ying ^a   Ku, Yi Cheng ^a  

^a PROVIDENCE UNIVERSITY   (Taiwan)

Author keywords

Argument quality; Flow theory; Source credibility; Technology acceptance model

Indexed keywords

FLOW THEORIES; PERCEIVED EASE OF USE; PERCEIVED USEFULNESS; SOURCE CREDIBILITY; SYSTEM ACCEPTANCE; TECHNOLOGY ACCEPTANCE MODEL;

INDUSTRY; INFORMATION SYSTEMS;

HUMAN RESOURCE MANAGEMENT;

EID: 84862917823     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (49)

1. Ahn, T., Ryu, S. and Han, I. (2007). The impact of Web quality and playfulness on user acceptance of online retailing. Information & Management, 44, 263-275. (Pubitemid 46705539)
2. Amoako-Gyampah, K. and Salam, A. F. (2001). An extension of the technology acceptance model in an ERP implementation environment. Information & Management, 41, 731-745.
3. Applegate, L. M., Austin, R. D. and McFarlan, W., (2003). Corporate information strategy and management: The challenges of managing in the network economy. Boston: McGraw-Hill.
4. Armstrong, J. S. and Overton, T. S. (1977). Estimating nonresponse bias in mail surveys. Journal of Marketing Research, 14, 396-402.
5. Bhattacherjee, A. and Sanford, C. (2009). The intention-behaviour gap in technology usage: the moderating role of attitude strength. Behaviour & Information Technology, 28 (4), 389-401.
6. Bhattacherjee, A. and Sanford, C. C. (2006). Influence processes for information technology acceptance: An elaboration likelihood model. MIS Quarterly, 30 (4), 805-825. (Pubitemid 46051905)
7. Chaiken, S. and Maheswaran, D. (1994). Heuristic processing can bias systematic processing: Effects of source credibility, argument ambiguity, and task importance on attitude judgment. Journal of Personality and Social Psychology, 66, 460-473.
8. Chu, P. Y., et al. (2004). Exploring success factors for Taiwan's government electronic tendering system: Behavioral perspectives from endusers. Government Information Quarterly, 21 (2), 219- 234.
9. Churchill, G. (1979). A paradigm for developing better measures of marketing constructs. Journal of Marketing Research, 16, 64-73.
10. Churchill, G., (2002). Basic Marketing Research. Brace Jovanovich: Harcourt. Csikszentmihalyi, M., (1990). Flow: The psychology of optimal experience. New York: Harper Perennial.
11. 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 (9), 982-1003.
12. 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), 1111-1132.
13. Davis, R. and Wong, D. (2007). Conceptualizing and measuring the optimal experience of the eLearning environment. Journal of Innovative Education, 5 (1), 97-126.
14. der Heijden, H. (2004). User acceptance of hedonic information systems. MIS Quarterly, 28 (4), 695- 704.
15. Harman, H. H., (1967). Modern factor analysis. Chicago: University of Chicago Press.
16. Hsu, C. L. and Lu, H. P. (2004). Why do people play games? An extended TAM with social influences and flow experience. Information & Management, 41, 853-868.
17. Huang, C.-C. (2009). Knowledge sharing and group cohesiveness on performance: An empirical study oftechnology R&D teams in Taiwan. Technovation, 29, 786-797.
18. Hwang, Y. 2005. Investigating enterprise systems adoption: uncertainty avoidance, intrinsic motivation, and the technology acceptance model. European Journal of Information Systems, 14, 150-161. (Pubitemid 41111289)
19. Ilsever, J., Cyr, D. and Parent, M. (2007). Extending models of flow and e-loyalty. Journal of Information Science and Technology, 3 (4), forthcoming.
20. Klein, R., Rai, A. and Straub, D. W. (2007). Competitive and cooperative positioning in supply chain logistics relationships. DecisionSciences, 38 (4), 611-646.
21. Koufaris, M. (2002). Applying the technology acceptance model and flow theory to online consumer behavior. Information Systems Research, 13 (5), 205-223.
22. Lee, M. K. O., Cheung, C. M. K. and Chen, Z. (2005). Acceptance of Internet-based learning medium: the role of extrinsic and intrinsic motivation. Information and Management, 42, 1095-1104. (Pubitemid 41690943)
23. Lee, M. K. O., et al., How positive informational social influence affects consumers' decision of internet shopping? ed. Proceedings of the 39th Hawaii International Conference on System Sciences, (2006).
24. Liang, H., et al. (2007). Assimilation of enterprise systems: The effect of institutional pressures and the mediating role of top management. MIS Quarterly, 31 (1), 59-87. (Pubitemid 46382518)
25. Liaw, S. S. and Huang, H. M. (2003). An investigation of user attitudes toward search engines as an information retrieval tool. Computers in Human Behavior, 19 (6), 751-765.
26. MacCracken, G. (1989). Who is the celebrity endorser?Cultural foundations of the endorsement process. Journal of Consumer Research, 16 (3), 310-321.
27. Martínez-López, F. J., Luna, P. and Martínez, F. J. (2005). Online shopping, the standard learning hierarchy, and consumers' internet expertise: An American-Spanish comparison. Internet Research, 15 (3), 312-334. (Pubitemid 41017140)
28. Morris, J. D., Woo, C. and Singh, A. J. (2005). Elaboration likelihood model: A missing intrinsic emotional implication. Journal of Targeting, Measurement and Analysis for Marketing, 14 (4), 79- 98.
29. Novak, T. P., Hoffman, D. L. and Yung, Y. F. (2000). Measuring the customer experience in online environments: A structural modelling approach. Marketing Science, 19, 22-42.
30. Oh, S. H., et al. (2009). Consumer adoption of virtual stores in Korea: Focusing on the role of trust and playfulness. Psychology & Marketing, 26 (7), 652-668.
31. Petty, R. E. and Cacioppo, J. T., (1986). The elaboration likelihood model of persuasion. In: L.BERKOVITZ ed. Advances in experimental social psychology New York: Academic Press, 123- 205.
32. Petty, R. E. and Wegener, D. T. (1998). Attitude change: Multiple roles for persuasion variables. Handbook of Social Psychology, 1, 323-390.
33. Ringle, C. M., Wende, S. and Will, A., (2005). SmartPLS 2.0 (beta). www.smartpls.de.
34. Roberts, P. and Henderson, R. (2000). Information technology acceptance in a sample of government employees: a test of the Technology Acceptance Model. nteracting with Computers, 12, 427-443. (Pubitemid 30552334)
35. Rucker, D. D. and Petty, R. E. (2006). Increasing effectiveness of communications to consumers: Recommendations based on the Elaboration Likelihood and attitude certainty perspectives. Journal of Public Policy and Marketing, 25 (1), 39-52. (Pubitemid 43935643)
36. Saade, R. and Bahli, B. (2005). The impact of cognitive absorption on perceived usefulness and perceived ease of use in on-line learning: an extension of the technology acceptance model. Information & Management, 42, 317-327.
37. Sanchez-Franco, M. J. and Roldan, J. L. (2005). Web acceptance and usage model: A comparison between goal-directed and experiential web users. Internet Research, 15 (1), 21-48. (Pubitemid 40687451)
38. Schepers, J. and Wetzels, M. (2007). A meta-analysis of the technology acceptance model: Investigating subjective norm and moderation effects. Information & Management, 44, 90-103. (Pubitemid 46028956)
39. Schroeder, L. M. (2005). Cultivation and the elaboration likelihood model: a test of the learning and construction and availability heuristic models. Communication Studies, 56 (3), 227-242.
40. Shin, D. H. 2009. An empirical investigation of a modified technology acceptance model of IPTV. Behaviour & Information Technology, 28 (4), 361-372.
41. Stephenson, M. T., Benoit, W. L. and Tschida, D. A. (2001). Testing the mediating role of cognitive responses in the Elaboration Likelihood Model. Communication Studies, 52 (4), 324-337.
42. Stewart, T. (2009). Acceptance, emotion and behaviour. Behaviour & Information Technology, 28 (4), 309-310.
43. Sussman, S. W. and Siegel, W. S. (2003). Informational influence in organizations: An integrated approach to knowledge adoption. Information Systems Research 14 (1), 47-65. (Pubitemid 36531431)
44. Tam, K. Y. and Ho, S. Y. (2005). Web personalization as a persuasion atrategy: An elaboration likelihood model perspective. Information Systems Research, 16 (3), 271-291. (Pubitemid 41395567)
45. Tzou, R.-C. and Lu, H.-P. (2009). Exploring the emotional, aesthetic, and ergonomic facets of innovative product on fashion technology acceptance model. Behaviour & Information Technology, 28 (4), 311-322.
46. Venkatesh, V. and Brown, S. A. (2001). A longitudinal investigation of personal computers in homes: Adoption determinants and emerging challenges. MIS Quarterly, 25 (1), 71-102.
47. Venkatesh, V. and Davis, F. D. (1996). A model of the antecedents of perceived ease of use: Development and test. Decision Science, 27 (3), 451-481.
48. Venkatesh, V. and Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46 (2), 186-205.
49. Yu, J., Ha, I., Choi, M. and Rho, J. (2005). Extending the TAM for a T-commence. Information & Management, 42, 965-976. 14.