Paradoxes of online investing: Testing the influence of technology on user expectancies

Decision Sciences

Volumn 37, Issue 2, 2006, Pages 205-246

  Looney, Clayton Arlen ^a   Valacich, Joseph S ^b   Todd, Peter A ^c   Morris, Michael G ^d  

^a UNIVERSITY OF MONTANA   (United States)

^b WASHINGTON STATE UNIVERSITY   (United States)

^c MCGILL UNIVERSITY   (Canada)

^d UNIVERSITY OF VIRGINIA   (United States)

Author keywords

Electronic commerce; Expectancy; Online investing; Para dox; Self efficacy; Social cognitive theory

Indexed keywords

EID: 33746256212     PISSN: 00117315     EISSN: 15405915     Source Type: Journal    
DOI: 10.1111/j.1540-5915.2006.00122.x     Document Type: Article

References (88)

1. Agarwal, R., Sambamurthy, V., & Stair, R. M. (2000). Research report: The evolving relationship between general and specific computer self-efficacy - An empirical assessment. Information Systems Research, 11(4), 418-430.
2. Ahmed, A. S., Schneible, R. A., Jr., & Stephens, D. E. (2003). An empirical analysis of the affects of online trading on stock price and trading volume reactions to earnings announcements. Contemporary Accounting Research, 20(3), 413-439.
3. Balasubramanian, S., Konana, P., & Menon, N. M. (2003). Consumer satisfaction with virtual environments: A study of online investing. Management Science, 49(7), 871-889.
4. Bandura, A. (1986). Social foundation of thought and action: A social cognitive theory. Englewood Cliffs, NJ: Prentice Hall.
5. Bandura, A. (1997). Self-efficacy: The exercise of control. New York: W.H. Freeman and Company.
6. Bandura, A. (2001a). Social cognitive theory: An agentic perspective. Annual Review of Psychology, 52(1), 1-26.
7. Bandura, A. (2001b). Guide for constructing self-eflicacy scales, accessed September 10, 2004 [available at: http://www.emory.edu/EDUCATION/mfp/ self-efficacy.html#effguide].
8. Barber, B. M., & Odean, T. (2000). Trading is hazardous to your wealth: The common stock investment performance of individual investors. Journal of Finance, 55(2), 773-806.
9. Barber, B. M., & Odean, T. (2001). The internet and the investor. Journal of Economic Perspectives, 15(1), 41-54.
10. Barber, B. M., & Odean, T. (2002). Online investors: Do the slow die first? Review of Financial Studies, 15(2), 455-487.
11. Barber, B. M., Lee, Y., Liu, Y., & Odean, T. (2004). Do individual day traders make money? Evidence from Taiwan. Working Paper, University of California -Davis.
12. Barclay, D., Higgins, C., & Thompson, R. (1995). Partial least squares approach to causal modeling: Personal computer adoption and use as an illustration. Technology Studies, 2(2), 285-324.
13. Barling, J., & Abel, M. (1983). Self-efficacy beliefs and tennis performance. Cognitive Therapy and Research, 7(3), 265-272.
14. Baroudi, J., & Orlikowski, W. (1988). A short-form measure of user information satisfaction: A psychometric evaluation and notes on use. Journal of Management Information Systems, 4(4), 44-59.
15. Boudreau, M. C., Gefen, D., & Straub, D. W. (2001). Validation in information systems research: A state-of-the-art assessment. MIS Quarterly, 25(1), 1-16.
16. Byrnes, N. (2006). The rush to shut down pensions. Business Week Online, accessed May 4, 2006 [available at: http://www.businessweek.com/bwdaily/dnflash/ jan2006/nf2006019_3388_db035.htm].
17. Carlson, L. (2005). Employees' knowledge gap impairs investment decisions. Employee Benefit News, accessed January 16, 2006 [available at: http://www.careerjournal.com/hrcenter/benefitnews/20051021-bn.html].
18. Chin, W. W., Gopal, A., & Salisbury, W. D. (1997). Advancing the theory of adaptive structuration: The development of a scale to measure faithfulness of appropriation. Information Systems Research, 8(4), 342-367.
19. Choi, J. J., Laibson, D., & Metrick, A. (2000). How does the Internet affect trading? Evidence from investor behavior in 401(k) plans. Journal of Financial Economics, 64(3), 391-421.
20. Clark, L. A., & Watson, D. (1995). Construct validity: Basic issues in scale development. Psychological Assessment, 7(3), 309-319.
21. Compeau, D. R., & Higgins, C. A. (1995a). Application of social cognitive theory to training for computer skills. Information Systems Research, 6(2), 118-143.
22. Compeau, D. R., & Higgins, C. A. (1995b). Computer self-efficacy: Development of a measure and initial test. MIS Quarterly, 19(2), 189-211.
23. Compeau, D. R., Higgins, C. A., & Huff, S. (1999). Social cognitive theory and individual reactions to computing technologies. MIS Quarterly, 23(2), 145-158.
24. Conway, J. M., & Huffcutt, A. I. (2003). A review and evaluation of exploratory factor analysis in organizational research. Organizational Research Methods, 6(2), 147-168.
25. Dennis, A. R., Wixom, B. H., & Vandenberg, R. J. (2001). Understand fit and appropriation effects in group support systems via meta-analysis. MIS Quarterly, 25(2), 167-197.
26. Dennis, A. R., & Valacich, J. S. (2001). Conducting experimental research in information systems. Communications of the AIS, 7(5), 1-41.
27. Devaraj, S., Fan, M., & Kohli, R. (2002). Antecedents of B2C channel satisfaction and preference: Validation e-commerce metrics. Information Systems Research, 13(3), 316-333.
28. Fama, E. F. (1991). Efficient capital markets II. Journal of Finance, 46(5), 1575-1617.
29. Fenton-O'Creevy, M., Nicholson, N., Soane, E., & Willman, P. (2003). Trading on illusion: Unrealistic perceptions of control and trading performance. Journal of Occupational and Organizational Psychology, 55(1), 53-68.
30. Fogg, B. J. (2003). Persuasive technologies. Amsterdam: Morgan Kaufman.
31. Fornell, C., & Larker, D. F. (1981). Evaluating structural equation models with unobserved variables and measurement error. Journal of Marketing Research, 18(1), 39-50.
32. Furnham, A., & Argyle, M. (1998). The psychology of money. London: Routledge.
33. Gefen, D., Straub, D. W., & Boudreau, M. C. (2000). Structural equation modeling and regression: Guidelines for research practice. Communications of the AIS, 4(7), 1-77.
34. Gist, M., Shwoerer, C., & Rosen, B. (1989). Effects of alternate training methods on self-efficacy and performance in computer software training. Journal of Applied Psychology, 74(6), 884-891.
35. Gordon, M., Slade, L., & Schmitt, N. (1986). The 'science of the sophomore' revisited: From conjecture to empiricism. Academy of Management, 11(1), 191-207.
36. Gordon, M., Slade, L., & Schmitt, N. (1987). Students guinea pigs: Porcine predictors and particularist phenomena. Academy of Management, 12(1), 160-163.
37. Greenberg, J. (1987). The college sophomore as guinea pig: Setting the record straight. Academy of Management, 12(1), 157-159.
38. Hess, T., Fuller, M., & Mathew, J. (2005-2006). Involvement and decision-making performance with a decision aid: The influence of social multimedia, and gender. Journal of Management Information Systems, 22(3), 15-54.
39. Hoch, S. J., & Schkade, D. A. (1996). A psychological approach to decision support systems. Management Science, 42(1), 51-64.
40. Jarvenpaa, S. (1989). The effect of task and graphical format congruency on information processing strategies and decision making performance. Management Science, 35(3), 285-303.
41. Johnson, R. D., & Marakas, G. M. (2000). Research report: The role of behavioral modeling in computer skill acquisition: Toward refinement of the model. Information Systems Research, 11(4), 402-417.
42. Kim, J., Lee, J., Han, K., & Lee, M. (2002). Business as buildings: Metrics for the architectural quality of internet businesses. Information Systems Research, 13(3), 239-254.
43. Klein, W. M., & Kunda, Z. (1994). Exaggerated self-assessments and the preference for controllable risks. Organizational Behavior and Human Decision Processes, 59(3), 410-427.
44. Konana, P., & Balasubramanian, S. (2005). The social-economic- psychological (SEP) model of technology adoption and usage: An application to online investing. Decision Support Systems, 39(3), 505-524.
45. Konana, P., Menon, N. M., & Balasubramanian, S. (2000). The implications of online investing. Communications of the ACM, 43(1), 34-41.
46. Korn, D. J. (2001). High-rolling your own. Financial Planning, accessed June 9, 2006 [available at http://www.keepmedia.com/pubs/financialPlanning/2001/ 05/01].
47. Kottemann, J. E., Davis, F. D., & Remus, W. E. (1994). Computer-assisted decision making: Performance, beliefs, and the illusion of control. Organizational Behavior and Human Decision Processes, 57(1), 26-37.
48. Krueger, D. W. (1986). Money, success, and success phobia. In D.W. Krueger (Ed.), The last taboo: Money as a symbol and reality in psychotherapy and psychoanalysis. New York: Brunner/Mazel, 3-16.
49. Langer, E. J. (1975). The illusion of control. Journal of Personality and Social Psychology, 32(2), 311-328.
50. Looney, C. A., & Chatterjee, D. (2002). Web-enabled transformation of the brokerage industry. Communications of the ACM, 45(8), 75-81.
51. Looney, C. A., Jessup, L. M., & Valacich, J. S. (2004). Emerging business models for mobile brokerage services. Communications of the ACM, 47(8), 71-77.
52. Mackay, J. M., & Elam, J. J. (1992). A comparative study of how experts and novices use a decision aid to solve problems in complex knowledge domains. Information Systems Research, 3(2), 150-172.
53. Marakas, G. M., Yi, M. Y., & Johnson, R. D. (1998). The multilevel and multifaceted character of computer self-efficacy: Toward a clarification of the construct and an integrated framework for research. Information Systems Research, 9(2), 126-162.
54. McGrath, J. E. (1982). Dilemmatics: The study of research choices and dilemmas. In J. E. McGrath (Ed.), Judgment calls in research. Beverly Hills, CA: Sage, 69-80.
55. Mick, D. G., & Fournier, S. (1998). Paradoxes of technology: Consumer cognizance, emotions, and coping strategies. Journal of Consumer Research, 25(2), 123-143.
56. Minch, P. R., & Sanders, G. L. (1986). Computerized information systems supporting multicriteria decision making. Decision Sciences, 17(2), 395-413.
57. Mitchell, T. R., & Mickel, A. E. (1999). The meaning of money: An individual-difference perspective. Academy of Management Review, 24(3), 568-578.
58. Netemeyer, R. G., Bearden, W. O., & Sharma, S. (2003). Scaling procedures: Issues and applications. Thousand Oaks, CA: Sage.
59. Nunnally, J. C. (1978). Psychometric theory (2nd ed.). New York: McGraw-Hill.
60. Odean, T. (1998). Volume, volatility, price and profit when all traders are above average. Journal of Finance, 53(6), 1887-1934.
61. Oskamp, S. (1965). Overconfidence in case study judgments. Journal of Consulting Psychology, 29(2), 261-265.
62. Pajares, F. (1996). Current directions in self-efficacy research. In M. Maehr & P. R. Pintrich (Eds.), Advances in motivation and achievement. Greenwich, CT: JAI Press, 221-251.
63. Parikh, M., Fazlollahi, B., & Verma, S. (2001). The effectiveness of decisional guidance: An empirical evaluation. Decision Sciences, 32(2), 303-331.
64. Pettit, D., & Jaroslovsky, R. (2002). The Wall Street Journal Online's guide to online investing. New York: Three Rivers Press.
65. Rothbaum, F., Weisz, J. R., & Snyder, S. S. (1982). Changing the world and changing the self - A 2-process model of perceived control. Journal of Personality and Social Psychology, 42(1), 5-37.
66. Rubaltelli, E., Rubichi, S., Savadori, L., Tedeschi, M., & Ferretti, R. (2005). Numerical information format and investment decisions: Implications for the disposition effect and the status quo bias. Journal of Behavioral Finance, 6(1), 19-26.
67. Settle, R. B., & Alreck, P. L. (1988). Hyperchoice shapes the marketplace. Marketing Communications, 13(5), 15-20, 61.
68. Shiller, R. J. (2003). The new financial order: Risk in the 21st century. Princeton, NJ: Princeton University Press.
69. Silver, M. S. (1990). Decisional support systems: Directed and nondirected change. Information Systems Research, 1(1), 47-70.
70. Silver, M. S. (1991). Decisional guidance for computer-based decisional support. MIS Quarterly, 15(1), 105-122.
71. Speier, C. B., Valacich, J. S., & Vessey, I. (1999). Information overload through interruptions: An empirical examination of decision making. Decision Sciences, 30(2), 337-360.
72. Speier, C. B., Vessey, I., & Valacich, J. S. (2003). The effects of interruptions, task complexity, and information presentation on computer-supported decision making performance. Decision Sciences, 34(4), 771-797.
73. Stajkovic, A. D., & Luthans, F. (1998). Self-efficacy and work performance: A meta-analysis. Psychological Bulletin, 124(2), 240-261.
74. Strader, T. J., & Ramaswami, S. N. (2004). Investor perceptions of traditional and online channels. Communications of the ACM, 47(7), 73-76.
75. Taylor, S., & Todd, P. A. (1995). Understanding information technology usage: A test of competing models. Information Systems Research, 6(2), 144-176.
76. Thaler, R. H. (1999). Mental accounting matters. Journal of Behavioral Decision Making, 12(3), 183-206.
77. Thaler, R. H., Tversky, A., Kahneman, D., & Schwartz, A. (1997). The effect of myopic loss aversion on risk taking: An experimental test. Quarterly Journal of Economics, 11(2), 647-661.
78. Todd, P. A., & Benbasat, I. (1999). Evaluating the impact of DSS, cognitive effort, and incentives on strategy selection. Information Systems Research, 10(4), 356-374.
79. U.S. Securities and Exchange Commission. (2006). The impact of recent technological advances on the securities markets, accessed May 4, 2006 [available at: http://www.sec.gov/news/studies/techrp97.htm].
80. Vancouver, J. B., Thompson, C. M., Tischner, E. C., & Putka, D. J. (2002). Two studies examining the negative effects of self-efficacy on performance. Journal of Applied Psychology, 87(3), 506-516.
81. Venkatesh, V., & Davis, F. D. (1996). A model of the antecedents of perceived ease of use: Development and test. Decision Sciences, 27(3), 451-481.
82. Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425-478.
83. Whyte, G., Saks, A., & Hook, S. (1997). When success breeds failure: The role of self-efficacy in escalating commitment to a losing course of action. Journal of Organizational Behavior, 18(5), 415-432.
84. Wixom, B. H., & Todd, P. A. (2005). A theoretical integration of user satisfaction and technology acceptance. Information Systems Research, 16(1), 85-102.
85. Wold, H. (1985). Systems analysis by partial least squares. In P. Nijkamp, L. Leitner, & N. Wrigley (Eds.), Measuring the unmeasurable. Dordrecht, Germany: Marinus Nijhoff, 221-251.
86. Wood, R. (1986). Task complexity: Definition of the construct. Organizational Behavior and Human Decision Processes, 37(1), 60-82.
87. Wood, R. E., & Bandura, A. (1989). Social cognitive theory of organizational management. Academy of Management Review, 14(3), 361-384.
88. Xia, W., & Lee, G. (2005). Complexity of information systems development projects: Conceptualization and measurement development. Journal of Management Information Systems, 22(1), 45-83.