Self-efficacy as an antecedent of cognition and affect in technology acceptance
Tóm tắt
– This paper aims to examine whether self-efficacy plays an important role in shaping the effect of cognition and affects in high technology adoption. It also examines whether cognition and affect mediate the effect of self-efficacy on attitude toward adoption.
– Using an experimental survey to collect data, subjects performed two different tasks (utilitarian and hedonic) to make sure that they had cognitive and affective experiences to draw upon as they developed attitudes toward the focal innovation. Structural equation modeling was used to analyze the model.
– The result shows that self-efficacy influenced cognitive perceptions and emotional reactions. Specifically, self-efficacy was found to play a substantive role in shaping individuals’ attitudes via a cognitive route (perceived usefulness and ease-of-use) and an affective one (pleasure, arousal and dominance).
– The study of self-efficacy as an external variable provides further insights into the process and is expected to increase the explained variance of the theoretical model.
– This study confirms that a belief about something besides the product also plays a key role; it is the confidence consumers have in their own abilities to understand and effectively use a new piece of technology.
– The research makes important contributions to our understanding of technology acceptance and has implications for marketing managers.
Từ khóa
Tài liệu tham khảo
Agarwal, R. , Sambamurthy, V. and Stair, R. (2000), “The evolving relationships between general and specific computer self-efficacy: an empirical assessment”, Information Systems Research, Vol. 11 No. 4, pp. 418-430.
Ajzen, I. (2002), “Perceived behavioral control, self-efficacy, locus of control, and the theory of planned behavior”, Journal of Applied Social Psychology, Vol. 32 No. 4, pp. 665-683.
Anderson, J. and Gerbing, D. (1998), “Structural equation modeling in practice: a review and recommended two-step approach”, Psychological Bulletin, Vol. 103 No. 3, pp. 411-423.
Bandura, A. (1977), “Self-efficacy: toward a unifying theory of behavioral change”, Psychological Review, Vol. 84 No. 2, pp. 191-215.
Bandura, A. (1982), “Self-efficacy mechanism in human agency”, American Psychologist, Vol. 37 No. 2, pp. 122-147.
Barling, J. and Beattie, R. (1983), “Self-efficacy beliefs and sales performance”, Journal of Organizational Behavior Management, Vol. 5, pp. 41-51.
Bennett, R. (2011), “Brand managers’ mindful self-management of their professional experience: consequences for pay, self-efficacy and job performance”, Brand Management, Vol. 18 No. 8, pp. 545-569.
Bruner, G.C.II and Kumar, A. (2005), “Applying T.A.M. to consumer usage of handheld internet devices”, Journal of Business Research, Vol. 58 No. 5, pp. 553-558.
Byrne, B.M. (1998), Structural Equation Modeling with LISREL, PRELIS and SIMPLIS: Basic Concepts, Applications, and Programming, Lawrence Erlbaum, Mahwah, NJ.
Byrne, Barbara M. (2001), Structural Equation Modeling with EQS: Basic Concepts, Applications, and Programming, SAGE Publications, Inc., Thousand Oaks, California.
Childers, T.L. , Carr, C.L. , Peck, J. and Carson, S. (2001), “Hedonic and utilitarian motivations for online retail shopping behavior”, Journal of Retailing, Vol. 77 No. 4, pp. 511-536.
Colkin, E. (2002), “Teens ace IT shortcuts”, Information Week, Vol. 879 No. 11, p. -.
Compeau, D. and Higgins, C. (1995), “Computer self-efficacy: development of a measure and initial test”, MIS Quarterly, Vol. 19 No. 2, pp. 189-211.
Compeau, D. , Higgins, C. and Huff, S. (1999), “Social cognitive theory and individual reactions to computing technology: a longitudinal study”, MIS Quarterly, Vol. 23 No. 2, pp. 145-158.
Csikszentmihalyi, M. (1975), Beyond Boredom and Anxiety, Jossey-Bass, San Francisco, CA.
Csikszentmihalyi, M. (1990), Flow: The Psychology of Optimal Experience, Harper & Row, New York, NY.
Dabholkar, P.A. and Bagozzi, R. (2002), “An attitudinal model of technology-based self-service: moderating effects of consumer traits and situational factors”, Journal of the Academy of Marketing Science, Vol. 30 No. 3, pp. 184-202.
Davis, F. (1989), “Perceived usefulness, perceived ease of use, and user acceptance of information technology”, MIS Quarterly, Vol. 13 No. 3, pp. 318-341.
Davis, F. , Bagozzi, R. and Warshaw, P. (1989), “User acceptance of computer technology: a comparison of two theoretical models”, Management Science, Vol. 35 No. 8, pp. 982-1004.
Ellen, P.S. , Bearden, W. and Sharma, S. (1991), “Resistance to technological innovations: an examination of the role of self-efficacy and performance satisfaction”, Journal of the Academy of Marketing Science, Vol. 19 No. 4, pp. 297-307.
Fornell, C. and Larcker, D.F. (1981), “Evaluating structural equation models with unobservable variables and measurement error”, Journal of Marketing Research, Vol. 18 No. 1, pp. 39-50.
Foxall, G. and Goldsmith, R. (1994), Consumer Psychology for Marketing, Routledge, London.
Fu, F.Q. , Richards, K.A. , Hughes, D.E. and Jones, E. (2010), “Motivating salespeople to sell new products: the relative influence of attitudes, subjective norms and self-efficacy”, Journal of Marketing, Vol. 74 No. 6, pp. 61-76.
Gao, L. , Wheeler, C.S. and Shiv, B. (2009), “The shaken self: product choices as a means of restoring self-view confidence”, Journal of Consumer Research, Vol. 36 No. 1, pp. 29-38.
Ghani, Jawaid A. and Deshpande, Satish P. (1994), “Task characteristics and the experience of optimal flow in human-computer interaction”, Journal of Psychology, Vol. 128 No. 4, pp. 381-391.
Gist, Marilyn E. (1987), “Self-efficacy: Implications for Organizational Behavior and Human Resource Management”, Academy of Management Review, Vol. 12 No. 3, pp. 472-485.
Gist, M.E. and Mitchell, T.R. (1992), “Self-efficacy: a theoretical analysis of its determinants and malleability”, Academy of Management Review, Vol. 17 No. 2, pp. 183-211.
Hair, J.F. , Anderson, R.E. , Tatham, R.L. and Black, W.C. (1998), Multivariate Data Analysis with Readings, 5th ed, Prentice-Hall, Englewood Cliffs, NJ.
Heinssen, R.K. , Glass, C.R. and Knight, L.A. (1987), “Assessing computer anxiety: development and validation of the computer anxiety rating scale”, Computers and Human Behavior, Vol. 3 No. 1, pp. 49-59.
Henry, J.W. and Stone, R.W. (1994), “A structural equation model of end-user satisfaction with a computer-based medical information system”, Information Resources Management, Vol. 7 No. 3, pp. 21-33.
Hill, T. , Smith, N.D. and Mann, M.F. (1987), “Role of efficacy expectations in predicting the secision to use advanced technologies: the case of computers”, Journal of Applied Psychology, Vol. 72 No. 2, pp. 307-313.
Hill, W.W. and Beatty, S.E. (2011), “A model of adolescents’ online consumer self-efficacy (OCSE)”, Journal of Business Research, Vol. 64 No. 10, pp. 1025-1033.
Hoffman, D.L. and Novak, T.P. (1996), “Marketing in hypermedia computer-mediated environments: conceptual foundations”, Journal of Marketing, Vol. 60 No. 3, pp. 50-68.
Hoyle, R.H. (1995), Structural Equation Modeling: Concepts, Issues and Applications, Sage Publications, Inc. Thousand Oaks, CA.
Hu, L. and Bentler, P.M. (1999), “Cutoff criteria for fit indexes in covariance structure analysis: conventional criteria versus new alternatives”, Structural Equation Modeling, Vol. 6 No. 1, pp. 1-55.
Igbaria, M. and Iivari, J. (1995), “The effects of self-efficacy on computer usage”, Omega, Vol. 23 No. 6, pp. 587-605.
Johnson, R.D. and Marakas, G. (2000), “Research report: the role of behavioral modeling in computer skills acquisition-toward refinement of the model”, Information Systems Research, Vol. 11 No. 4, pp. 402-418.
Kulviwat, S. , Bruner, G.C.II , Kumar, A. , Nasco, S.A. and Clark, T. (2007), “Toward a unified theory of consumer acceptance of technology”, Psychology and Marketing, Vol. 24 No. 12, pp. 1059-1084.
Marcolin, Barbara L. , Compeau, Deborah R. , Munro, Malcolm C. and Huff, Sid L. (2000), “Assessing User Competence: Conceptualization and Measurement,” Journal of Service Research, Vol. 11 No. 1, pp. 37-60.
McKee, D. , Simmers, C.S. and Licata, J. (2006), “Customer self-efficacy and response to service,” Journal of Service Research, Vol. 8 No. 3, pp. 207-220.
Madden, M. (2010), Four or More: The News Demographic, Pew Internet and American Life Project, Washington, DC.
Manyiwa, S. and Brennan, R. (2012), “Fear appeals in anti-smoking advertising: how important is self-efficacy”, Journal of Marketing Management, Vol. 28 Nos 11/12, pp. 1419-1437.
Marquie, J.D. , Jourdan-Boddaert, L. and Huet, N. (2002), “Do older adults underestimate their actual computer knowledge”, Behavior and Information Technology, Vol. 21 No. 4, pp. 273-281.
Mehrabian, Albert and James, A. Russell (1974), An Approach to Environmental Psychology, Cambridge, MA: MIT Press.
Meuter, M.L. , Bitner, M.J. , Ostrom, A.L. and Brown, S.W. (2005), “Choosing among alternative service delivery modes: an investigation of customer trial of self-service technologies”, Journal of Marketing, Vol. 69 No. 2, pp. 61-83.
Nasco, S. , Kulviwat, S. , Kumar, A. and Bruner, G.C.II ( 2008), “The CAT model: extensions and moderators of dominance in technology acceptance”, Psychology and Marketing, Vol. 25 No. 10, pp. 987-1005.
Novak, T. , Hoffman, D. and Yung, Y. (2000), “Measuring the customer experience in online environments: a structural modeling approach”, Marketing Science, Vol. 19 No. 1, pp. 22-42.
Pedersen, P. (2003), “Adoption of mobile Internet services: an exploratory study of mobile commerce early adopters”, Working paper.
Robertson, Thomas S. (1971), Innovative Behavior and Communication. New York: Holt, Rinehart & Winston.
Sinkovics, R. , Stottinger, B. , Schlegelmilch, B. and Ram, S. (2002), “Reluctance to use technology-related products: development of a technophobia scale”, Thunderbird International Business Review, Vol. 44 No. 4, pp. 477-494.
Stumpf, S.A. , Brief, A.P. and Hartman, K. (1987), “Self-efficacy expectations and coping with career-related events”, Journal of Vocational Behavior, Vol. 31 No. 2, pp. 91-108.
Szajna, B. (1996), “Empirical evaluation of the revised technology acceptance model”, Management Science, Vol. 42 No. 1, pp. 85-93.
Taylor, S. and Todd, P. (1995), “Understanding information technology usage: a test of competing models”, Information Systems Research, Vol. 6 No. 2, pp. 144-176.
Tsarenko, Y. and Strizhakova, Y. (2013), “Coping with service failures: the role of emotional intelligence, self-efficacy and intention to complain”, European Journal of Marketing, Vol. 47 Nos 1/2, pp. 71-92.
Venkatesh, V. (2000), “Determinants of perceived ease of use: integrating control, intrinsic motivation and emotion into the technology acceptance model”, Information Systems Research, Vol. 11 No. 4, pp. 342-365.
Venkatesh, V. and Davis, F. (1996), “A model of the antecedents of perceived ease of use: development and test”, Decision Sciences, Vol. 27 No. 3, pp. 451-482.
Webster, J. and Martocchio, J. (1992), “Microcomputer playfulness: development of a measure with workplace implications”, MIS Quarterly, Vol. 16 No. 2, pp. 201-226.
White, K. , Macdonnell, R. and Dahl, D.W. (2011), “It’s the mind-set that matters: the role of construal level and message framing in influencing consumer efficacy and conservation behaviors”, Journal of Marketing Research, Vol. 48 No. 3, pp. 472-485.
Yim, C.K. , Chan, K.W. and Lam, S.S.K. (2012), “Do customers and employees enjoy service participation? Synergistic effects of self- and other-efficacy”, Journal of Marketing, Vol. 76 No. 6, pp. 121-140.
Bagozzi, R.P. and Phillips, L.W. (1982), “Representing and testing organizational theories: a holistic construal”, Administrative Science Quarterly, Vol. 27 No. 3, pp. 459-490.
Bandur, A. (1986), Social foundations of thought and action, Prentice Hall, Englewood Cliffs, NJ.
Bentler, P.M. (1990), “Comparative fit indices in structural models”, Psychological Bulletin, Vol. 107, pp. 238-246.
Bentler, P.M. and Bonett, D.G. (1980), “Significance tests and goodness of fit in the analysis of covariance structures”, Psychological Bulletin, Vol. 88 No. 3, pp. 588-606.
Gist, M.E. , Schwoerer, C.E. and Rosen, B. (1989), “Effects of alternative training methods on self-efficacy and performance in computer software training”, Journal of Applied Psychology, Vol. 74 No. 6, pp. 884-891.
Igbaria, M. , Guimaraes, T. and Davis, G. (1995), “Testing the determinants of microcomputer usage via a structural equation model”, Journal of Management Information Systems, Vol. 11 No. 4, pp. 87-114.
Nunnally, J.C. and Bernstein, I. (1994), Psychometric theory, 3rd ed., McGraw-Hill, New York, NY.
Peterson, R. (1994), “A meta-analysis of cronbach’s coefficient alpha”, Journal of Consumer Research, Vol. 21 No. 1, pp. 381-391.
Rogers, E.M. (1995), The Diffusion of Innovation, 4th ed., Free Press, New York, NY.