تحلیل پویایی های فردی مقاومت در برابرکاربست فنّاوری اطلاعات در سازمان

نوع مقاله : پژوهشی ( با رویکردهای کمی)

نویسندگان

1 دانشیار گروه مدیریت دانشگاه ولی عصر (عج)

2 دانش آموخته کارشناسی ارشد مدیریت دولتی (گرایش سیستم های اطلاعاتی) دانشگاه ولی عصر (عج)

چکیده

این پژوهش با هدف تدوین و آزمون مدل عوامل فردی مؤثر در مقاومت در برابر استفاده از فنّاوری اطلاعات در سازمان‌های اجرایی رفسنجان انجام شده است. برای انجام پژوهش، پرسشنامه‌هایی برای سنجش متغیرها تهیه و پس از اطمینان از روایی محتوا، بین نمونة 357 نفری از کارکنان قلمرو مکانی پژوهش توزیع شد. در ادامه، با استفاده از نرم­افزار Smart PLS، پایایی، روایی همگرا و واگرای سنجة پژوهش بررسی، تأیید و سپس داده‌ها به مدل‌ معادلة ساختاری برازش شدند. نتایج نشان داد در سطح اطمینان 95 درصد، ویژگی­های شخصیتی مقاومت در برابر تغییر و ادراک سودمندی فنَاوری اطلاعات در مقاومت در برابر کاربست فنَاوری اطلاعات اثر مثبت دارند؛ ضمن اینکه ادراک سودمندی فنَاوری اطلاعات، خود میانجی اثر مثبت رایانه­ترسی و ادراک سهولت در کاربست فنّاوری اطلاعات در متغیر اصلی وابستة پژوهش است. همچنین، مشخص شد اگر چه ادراک سهولت استفاده از فنَاوری اطلاعات از رایانه­ترسی، رایانه­بازی و ادراک پیچیدگی فنَاوری اطلاعات اثر می­پذیرد، خود اثر مستقیم معناداری در مقاومت در برابر فنَاوری اطلاعات ندارد و تنها از طریق ادراک سودمندی فنّاوری اطلاعات نقش غیرمستقیم ایفا می­کند.

عنوان مقاله [English]

Analyzing individual level dynamics of resistance to information technology usage

نویسندگان [English]

  • Mostafa Hadavinejad 1
  • Zahra Azimi 2

1 Associate professor of Management Department, Vali-e-Asr university

2 MSc of Public Management

چکیده [English]

The purpose of this study was to design and examine a model for individual factors affecting on resistance to information technology usage in Rafsanjan’s public organizations. In this regard, questionnaires related to research variables were prepared and after ensuring the content validity, were distributed among 357 employees as a sample. Using Smart PLS, the questionnaire’s reliability, convergent and divergent validity were tested. Then data were fitted to structural equation model. Results showed that the dispositional factors of resistance to change and IT perceived usefulness affect positively on resistance to IT usage. Moreover, in its turn, perception of IT usefulness mediates the positive effect of computer anxiety. Also, it is uncovered that although IT perceived ease of use is affected from computer anxiety, computer playfulness, and perceived IT complexity, it has no meaningful effect on resistance to IT usage.

  1. جامی‌پور، مونا، شرکت، محمدحسین، و یزدانی، حمیدرضا (1396). ارائۀ مدل مدیریت تغییر در برون‎سپاری خدمات فناوری اطلاعات: رویکرد ساختاری ـ تفسیری، مدیریت فنّاوری اطلاعات، 9، 424-405.
  2. Cazan, A., Cocorada, A., & Maican, C. L. (2016). Computer anxiety and attitudes towards the computer and the internet with Romanian high-school and university students. Computers in Human Behavior, 55(2), 258-267.
  3. Chin, W. W. (1998). The partial least squares approach to structural equation modeling. In G. A. Marcoulides (Ed.), Modern Methods for Business Research, Mahwan. New Jersey: Lawrence Erlbaum Associates, 295-358.
  4. Cohen, J. (1988). Statistical power analysis for the behavioral sciences. Hilsdale, New Jersey: Lawrence Erlbaum Associates.
  5. Coleman, H. L. (2009). The personality traits of instrumentality and expressiveness in relation to microcomputer playfulness. University of Texas Libraries, Austin.
  6. Cook, W.W., & Medley, D. M. (1954). Proposed hostility and pharisaic-virtue scales for the MMPI. Journal of Applied Psychology, 38(6), 414-418.
  7. Cronbach, L. J. (1951). Coefficient alpha and the internal structure of tests. Psychometrika, 16(3), 297-334.
  8. Davis, F.D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340.
  9. De Freitas, S., & Oliver, M. (2006). How can exploratory learning with games and simulations within the curriculum be most effectively evaluated?. Computers & Education, 46(3), 249-264.
  10. Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39-50.
  11. Harman, D. (1967). A single factor test of common method variance. Journal of Psychology, 35(1), 359–378.
  12. Hasan, B. (2007). Examining the effects of computer self-efficacy and system complexity on technology acceptance. Information Resources Management Journal, 20(3), 76-88.
  13. Heinssen, R.K., Glass, C.R., & Knight, L.A. (1987). Assessing computer anxiety: Development and validation of the computer anxiety rating scale. Computers in Human Behavior, 3(1), 49-59.
  14. Henseler, J., Ringle, C. M., & Sinkovics, R. R. (2009). The use of partial least squares path modeling in international marketing. Advances in International Marketing, 20, 277-320.
  15. Hulland, J. (1999). Use of partia least squares (PLS) in strategic management research: A review of four recent studies. Strategic Management Journal, 20(2), 195-204.
  16. Iacobucci D., & Duhachek, A. (2003). Mediation analysis- Round table ACR 2003. Presentation at the round table of the ACR Conference, Toronto.
  17. Igbaria, M. (1993). User acceptance of microcomputer technology: An empirical test, Omega. 21(1), 73-90.
  18. Igbaria, M., & Parasuraman, S. (1989). A path analytic study of individual characteristics, computer anxiety and attitudes toward microcomputers. Journal of Management, 15(4), 373-88.
  19. Jashapara, A., & Tai, W.C. (2006). Understanding the complexity of human characteristics on e-learning systems: an integrated study of dynamic individual differences on user perceptions of ease of use. Knowledge Management Research & Practice, 4(3), 227-239.
  20. Joshi, K. (1991). A model of users’ perspective on change: The case of information systems technology implementation. MIS Quarterly, 15(2), 229-242.
  21. Kanter, D., & Mirvis, P. (1989). The cynical americans: Living and working in an age of discontent and disillusion. San Francisco: Jossey-Bass.
  22. Kenrick, D. T., & Funder, D. C. (1998). Profiting from controversy: Lessons from the person–situation debate. Personality: Critical Concepts, 43(1), 23-34.
  23. Krejcie, R. V., & Morgan, D. W. (1970). Determining sample size for research activities. Educational & Psychological Measurement, 30(3), 607-610.
  24. Mabin, V. J., Forgeson, S., & Green, L. (2001). Harnessing resistance: Using the theory of constraints to assist change management. Journal of European Industrial Training, 25(2-4), 168-191.
  25. Nunnally, J. C., & Bernstein, I. H. (1994). Psychometric theory. New York: McGraw-Hill.
  26. Oreg, S. (2003). Resistance to change: Developing an individual differences measure. Journal of Applied Psychology, 88(4), 680-692.
  27. Piderit, S. K. (2000). Rethinking resistance and recognizing ambivalence: A multidimensional view of attitudes toward an organizational change. Academy of Management Review, 25(4), 783-794.
  28. Preacher, K. J., & Hayes, A. F. (2008). Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models. Behavior Research Methods, 40(3), 879-891.
  29. Rosen, L. D., Sears, D. C., & Weil, M. M. (1987). Computerphobia. Behavior Research Methods, Instruments, & Computers, 19(2), 167-179.
  30. Sacks, C.H., Bellissimo, Y., & Mergendoller, J. (1994). Attitudes toward computers and computer use: The issue of gender. Journal of Research on Computing in Education, 26(2), 256-269.
  31. Spielberger, C.D., & Sydeman, S.J. (1994). State-trait anxiety inventory and state-trait anger expression inventory. In M. E. Maruish (Ed.), The use of psychological testing for treatment planning and outcome assessment (Vol. 1). Hillsdale, NJ,/England: Lawrence Erlbaum Associates, Inc., 292-321.
  32. Suki, N. M., & Suki, N. M. (2011). Exploring the relationship between perceived usefuleness, perceived ease of use, perceived enjoyment, attitude and and subscriber’s intention towards using 3G mobile services, Journal of Information Technology Management, 22(1), 1-7.
  33. Tekinarslan, E. (2008). Computer anxiety: A cross-cultural comparative study of Dutch and Turkish university students. Computers in Human Behavior, 24(4), 1572-1584.
  34. Thompson, R.L., Higgins, C.A., & Howell, J.M. (1991). Personal Computing: Toward a Conceptual Model of Utilization. MIS quarterly, 15(1), 125-143.
  35. Thompson, R. L., Higgins, C. A., & Howell, J. M. (1994). Influence of experience on personal computer utilization: Testing a conceptual model. Journal of Management Information Systems, 11(1), 167-187.
  36. Todman, J., & Day, K. (2006). Computer anxiety: The role of psychological gender. Computers in Human Behavior, 22(5), 856-869.
  37. Tornatzky, L. G., & Klein, K. J. (1982). Innovation characteristics and innovation adoption-implementation: A meta-analysis of findings. Engineering Management, IEEE Transactions, 29(1), 28-45.
  38. 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.
  39. Webster, J., & Martocchio, J. (1992). Microcomputer playfulness: Development of a measure with workplace implications. MIS Quarterly, 16(2): 201-226.
  40. Wetzels, M., Odekerken-Schroder, G., & Van Oppen, C. (2009). Using PLS path modeling for assessing hierarchical construct models: Guidelines and empirical illustration. MIS Quarterly, 33(1), 177-195.
  41. Zhang, N., Guo X., & Chen, G. (2008). IDT-TAM integrated model for IT adoption. Tsinghua Science & Technology, 13(3), 306-311.