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E-ISSN : 2233-5382
A Unified Model Combining Technology Readiness Acceptance Model and Technology Paradox Theory
Park, Sang-Bum
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Abstract
Purpose - There are common factors both in Technology Readiness and Acceptance Model and Technology Paradox Theory which can be put together and made in one unified model. The unified model can provide the following merits. First, the unified model is simple but contains factors of the models. Second, the unified model can clarify the process of technology acceptance of common consumers. Third, the unified model can provide the opportunities to analyze the negative sides of new technology, thus find ways to improve the level of acceptance by general consumers. Research design, data, and methodology - The 450 questionnaires were handed out to people around Seoul and 421 were collected. Except insincere and wrong-marked ones, 402 were used to analyze. SPSS program was used to analyze. Factor analysis, regression analysis was conducted to test the hypotheses. Results - By analyzing sub-factors of both models and binding the common factors in one category, we accomplish one model. And we tested the model by empirical method. The results show that the results from the unified model are almost same as the results from the two models. In other words, the unified model works. Conclusions - Explaining one state of affair by two different method is in some sense distracting attention. By devising a new model including factors of both models, we can explain the affair more straightforward and efficiently. At first the technology acceptance model was devised to explain the technology users in an organization and the following tests and revised models were for the similar purposes. However, as on-lone activities including contracts have been expanded and become important, consumers as the technology uses have emerged as first factor to consider. In accordance models to explain this situation has been suggested. The model suggested in this research is one of the models but it has the following merits. That is, it is simple but has strong explanation power, it can clarify the process of technology acceptance of common consumers by containing negative sides of consumer conception, and thus, it can provide the opportunities to analyze the negative sides of new technology, also find ways to improve the level of acceptance by general consumers.
- keywords
- Technology Readiness & Acceptance Model, Technology Paradox Model, Unified Model
Reference
Bandura, A. (1997). Editorial. American Journal of Health Promotion, 12(1), 8-10.
Bart, Y., Shankar, V., Sultan, F., & Urban, G. L. (2005). Are the drivers and role of online trust the same for all web sites and consumers? A large-scale exploratory empirical study. Journal of marketing, 69(4), 133-152.
Chang, H. J., & Noh, K. Y. (2017). Extended Technology Acceptance Model of VR Head-Mounted Display in Early Stage of Diffusion. Journal of Digital Convergence, 15(5), 353-361.
Choi, Y. J., Ra, J. H., & Jung, Y. K. (2011). An Exploratory Study on the Acceptance Factors of the Innovative Technology in Area of Information Technology. Management Science, 28(3), 113-124.
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS quarterly, 319-340.
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.
Folkman, S., & Lazarus, R. S. (1980). An analysis of coping in a middle-aged community sample. Journal of health and social behavior, 219-239.
Han, S. L., & Park, S. M. (2009). Effects of Technology Readiness on the Attitude and Usage Intention of Self Service Technology. Entrue Journal of Information Technology, 8(2), 51-63.
Handy, C. (1995). The Age of Paradox. Boston: Harvard Business School Press.
Hsu, C., & Lin, J. (2008). Acceptance of blog usage: The roles of technology acceptance, social influence and knowledge sharing motivation. Information &Management, 45, 65-74.
Jang, H. Y., & Koh, J. (2017). Factors Affecting the Usage of Elderly People’s Smartphones: Based on UTAUT Model. Journal of Information Research, 26(1), 143-169.
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.
Jarvenpaa, S. L., & Lang, K. R. (2005). Managing the paradoxes of mobile technology. Information systems management, 22(4), 7-23.
Jeong, J. Y., & Noh, T. W. (2017). The Intention of Using Wearable Devices: Based on Modified Technology Acceptance Model. Journal of Digital Convergence, 15(4), 205-212.
Johnson, D. S., Bardhi, F., & Dunn, D. T. (2008). Understanding how technology paradoxes affect customer satisfaction with self‐service technology:The role of performance ambiguity and trust in technology. Psychology & Marketing, 25(5), 416-443.
Johnson, D., & Grayson, K. (2005). Cognitive and affective trust in service relationships. Journal of Business research, 58(4), 500-507.
Kim, H. W., Chan, H. C., & Gupta, S. (2007). Value-based Adoption of Mobile Internet: An empirical investigation. Decision Support Systems, 43(1), 111-126.
Lazarus, R. S. (1991). Progress on a cognitive-motivationalrelational theory of emotion. American psychologist, 46(8), 819.
Lin, C. H., Shih, H. Y., & Sher, P. J. (2007). Integrating technology readiness into technology acceptance:The TRAM model. Psychology & Marketing, 24(7), 641-657.
Loeschner, I. (2017). The technology mismatch paradox of mobile e-mail access: When changed norms of responsiveness meet technology undersupply. The Information Society, 33(3), 133-146.
Looney, C. A., Valacich, J. S., Todd, P. A., & Morris, M. G. (2006). Paradoxes of online investing: Testing the influence of technology on user expectancies. Decision Sciences, 37(2), 205-246.
Luce, M. F. (1998). Choosing to avoid: Coping with negatively emotion-laden consumer decisions. Journal of consumer research, 24(4), 409-433.
Maruping, L. M., Bala, H., Venkatesh, V., & Brown, S. A. (2017). Going beyond intention: Integrating behavioral expectation into the unified theory of acceptance and use of technology. Journal of the Association for Information Science and Technology, 68(3), 623-637.
Mazey, N. C., & Wingreen, S. C. (2017). Perceptions of trust in bionano sensors: Is it against our better judgement? An investigation of generalized expectancies and the emerging technology trust paradox. International Journal of Distributed Sensor Networks, 13(7), 1550147717717388.
McAllister, D. J. (1995). Affect-and cognition-based trust as foundations for interpersonal cooperation in organizations. Academy of management journal, 38(1), 24-59.
McKnight D. H., Carter M., & Thatcher, J. B. (2011). Trust in a specific technology: An investigation of its components and measures. ACM T Manage Inform Sys, 2, 1–25.
McKnight, D. H., Choudhury, V., & Kacmar, C. (2002). Developing and validating trust measures for e-commerce: An integrative typology. Information systems research, 13(3), 334-359.
Mick, D. G., & Fournier, S. (1998). Paradoxes of technology: Consumer cognizance, emotions, and coping strategies. Journal of Consumer research, 25(2), 123-143.
Moon, J., & Kim, Y. (2001). Extending the TAM for a World-Wide-Web context. Information & Management, 38(4), 217-230.
Nam, Y. S. (2012). The Effects of Technology Paradoxes on Technology Trust in the Hotel SST Encounter – Focusing on Mediating Effect of Performance Ambiguity. Tourism Management Research, 52, 97-120.
Nikou, S. A., & Economides, A. A. (2017). Mobile-Based Assessment: Integrating acceptance and motivational factors into a combined model of Self-Determination Theory and Technology Acceptance. Computers in Human Behavior, 68, 83-95.
Parasuraman, A. (2000). Technology Readiness Index (TRI) a multiple-item scale to measure readiness to embrace new technologies. Journal of service research, 2(4), 307-320.
Prikh, M., Fazollahi, B., & Verma, S. (2001). The effectiveness of decisional guidance: An empirical evaluation. Decision Science, 32(2), 303-331.
Raaij, Fred Van W., & Pruyn, A. T. (1998). Customer control and evaluation of service validity and reliability. Psychology & Marketing, 15(8), 811-832.
Schlosser, A. E., White, T. B., & Lloyd, S. M. (2006). Converting web site visitors into buyers: How web site investment increases consumer trusting beliefs and online purchase intentions. Journal of Marketing, 70(2), 133-148.
Shin, C. H., & Lee, H. J. (2012). A Study on Airliners’Self-Service Technology(SST) Quality affecting Customer Satisfaction and Behavior Intention. Tourism Management Research, 51, 97-117.
Speir, C. B., Vessey, I., & Valacich, J. S. (2003). The effect of interruptions. task complexity, and information presentation on computer-supported decision making performance. Decision Sciences, 34(4), 771-797.
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.
Venkatesh, V., & Davis, F. (2000). A Theoretical Extension of the Technology Acceptance Model:Four Longitudinal Field Studies. Management Science, 46(2), 186-204.
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F.D. (2003). User acceptance of information technology: Toward a unified view. MIS quarterly, 425-478.
Weiner, B. (1985). An attributional theory of achievement motivation and emotion. Psychological review, 92(4), 548.
Yang, J. I., Yoon, Y. S., & Lee, T. H. (2009). A study on service satisfaction and loyalty of airline’s multiple channel service technology. Tourism Research Journal, 23(2), 345-359.
You, J. H., & Park, C. (2010). A Comprehensive Review of Technology Acceptance Model Researches. Entrue Journal of Information Technology, 9(2), 31-50.
Yousafzai, S. Y., Pallister, J., & Foxall, G. R. (2005). Strategies for building and communicating trust in electronic banking: A field experiment. Psychology & Marketing, 22(2), 181-201.
Zeithaml, V. A. (1981). How Consumer Evaluation Processes Differ between Goods and Services. in Marketing of Services, Donnelly, J. H., & George, W. R. (Eds.). Chicago, IL.: American Marketing Association.
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