نوع مقاله : مقاله پژوهشی

نویسندگان

1 استاد، گروه مدیریت صنعتی، دانشگاه علامه طباطبائی، تهران، ایران

2 دانشجوی دکتری رشته مدیریت فناوری اطلاعات، دانشگاه علامه طباطبائی، تهران، ایران

3 استادیار، گروه تعاون و رفاه اجتماعی، دانشگاه علامه طباطبائی، تهران، ایران

چکیده

در چرخه حیاتِ فناوری های اطلاعات شرکتی در سازمان، عوامل مختلفی نظیر مهندسی مجدد فرایندها، تغییر در قوانین، الزامات مربوط به بهبود عملکرد، می توانند سبب دوره هایی از تغییر در این فناوری ها شوند. هدف این پژوهش، بررسی نقش دانش کاربران در مواجه با این دوره های تغییر براساس ارزیابی آن ها از وظایف محوله است. برای نیل به این هدف داده هایی از 153 نفر از کارکنان بانک دولتی الف و چهار شعبه آن در سطح شهر تهران، به روش نمونه گیری تصادفی ساده با استفاده از پرسشنامه جمع آوری شد. پژوهش حاضر از لحاظ هدف توسعه ای-کاربردی و به لحاظ بررسی روابط بین متغیرها،از نوع رابطه ای (همبستگی) است و روابط علی و معلولی، مبتنی بر معادلات ساختاری ارزیابی می شوند. نتایج آزمون فرضیه ها با به کارگیری نرم افزار Smart PLS3، حاکی از آن است که سطوح دانشی "دستور محور"، "روندهای مربوط به ابزار" و "روندهای مربوط به کسب و کار" بر برداشت فرد از سختی وظیفه تاثیرگذار هستند. همچنین تحلیل داده ها نشان می دهد که با بالا رفتن تجربه مرتبط با فناوری، افراد وظیفه/وظایف محوله را کمتر سخت ارزیابی می کنند.

کلیدواژه‌ها

عنوان مقاله [English]

The Role of User’s Knowledge in Evaluation of Task Difficulty in Face of Improvement of Enterprise IT in Organization

نویسندگان [English]

  • Payam Hanafizadeh 1
  • Ahmad Taherianfar 2
  • masood Alami Neisi 3
  • Mohammad Taghi Taghavifard 1

1 Professor Department of Industrial Management, Allameh Tabataba'i University, Tehran, Iran

2 PhD student in Information Technology Management, Allameh Tabataba'i University, Tehran, Iran

3 Assistant Professor, Department of Cooperatives and Social Welfare, Allameh Tabataba'i University, Tehran, Iran

چکیده [English]

In Enterprise information technologies life cycle in organization, Different factors such as reengineering of processes, shift in regulations, performance improvement could cause periods of change in these Information technologies. The purpose of this study is the investigation of the role of user’s knowledge of these change periods based on their perception of task difficulty. For reaching to this purpose, data of 153 staff of one public bank and it’s for subsidiaries in Tehran is collected. this collection is based on a simple random sampling and is accomplishes by means of questionnaire. This study is an applied research which correlate between variables and use structural equation modeling for evaluation of cause and effects. Results by aide of SmartPLS3 software, showed that “command based knowledge”, “tool procedural knowledge” and “business procedural knowledge” affect user’s evaluation of task difficulties. It is also concluded that user’s with more technology experience evaluate tasks less difficult.

کلیدواژه‌ها [English]

  • User’s Knowledge
  • Experience
  • Enterprise IT
  • Task Difficulty
داوری، علی و رضازاده، آرش.(1393). مدل سازی معادلات ساختاری با نرم افزار PLS، سازمان انتشارات جهاد دانشگاهی، اول، تهران.
Aanestad, M. & Jensen, T. (2016). Collective mindfulness in postimplementation IS adaptation processes. Information & Organization, 26, 13–27.
Bagayogo, F.F., Lapointe, L., & Bassellier, G. (2014). Enhanced Use of IT: A New Perspective on PostAdoption. Journal of the Association for Information Systems, 15 (7), 361-387
Bala,H., & Venkatesh, V.(2016). Adaptation to Information Technology: A Holistic Nomological Network from Implementation to Job Outcomes. Management Science 62(1):156-179.
Beaudry, A., & Pinsonneault, A.)2005(.Understanding User Responses to Information Technology: A Coping Model of User Adaptation. MIS Quart. 29(3), 493–524.
Bhattacherjee, A., Davis, C. J., Connolly, A. J. and Hikmet, N.)2017(. User response to mandatory it use: A coping theory perspective. European Journal of Information Systems, 27(4), 395-414
Chin, W. W. (1998). The partial least squares approach to structural equation modeling. In G. A. Marcoulides (Ed.), Modern methods for business research (pp. 295–336). New Jersey: Lawrence Erlbaum Associates.
Chin, W. W., Marcolin, B. L., & Newsted, P. R. (2003). A partial least squares latent variable modeling approach for measuring interaction effects: Results from a monte carlo simulation study and an electronic-mail emotion/adoption study. Information Systems Research, 14(2), 189–217.
Coulson, A., Shayo, C., Olfman, L. and Rohm, C.E.T.(2003).ERP training strategies: conceptual training and the formation of accurate mental models. in ACM SIGMIS conference on Computer personnel research, (Philadelphia, Pennsylvania),ACM, 87-97.
Coulson, T., Olfman, L., Ryan, T., & Shayo, C. (2010). Enterprise Systems Training Strategies: Knowledge Levels and User Understanding. Journal of Organizational and End User Computing (JOEUC), 22(3), 22-39.
Elie-Dit-Cosaque, C. M., & Straub, D. W. (2011). Opening the black box of system usage: user adaptation to disruptive IT. European Journal of Information Systems, 20(5), 589–607
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50.
Fuerst, W. L., and Cheney, P. H. (1982). Factors Affecting the Perceived Utilization of Computer Based Decision Support Systems in the Oil Industry. Decision Sciences, 13(4), pp. 554-569.
Gupta, S., and Bostrom, R.P.(2006).End-user training: What we know, what we need to know? In K. Kaiser and T. Ryan (eds.), Proceedings of the ACM SIGMIS. New York: ACM Press, pp. 172-182.
Hærem, T., Pentland, B. T., & Miller, K. D. (2015). Task complexity: Extending a core concept. The Academy of Management Review, 40(3), 446-460.
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.
Jasperson, J.S., Carter, P.E., & Zmud, R.W.(2005). A comprehensive conceptualization of post-adoptive behaviors associated with information technology enabled work systems. MIS Quarterly, 29(3), 525-557.
Li, Y., & Belkin, N.J. (2008). A faceted approach to conceptualizing tasks in information seeking. Information Processing & Management, 44(6), 1822–1837.
Mateos-Aparicio, G. (2011). Partial least squares (PLS) methods: origins, evolution, and application to social sciences. Communications in Statistics – Theory and Methods, Vol. 40(13), pp. 2305-2317.
Olfman, L., Bostrom, R.P. and Sein, M.K.(2005). Developing training strategies with an HCI perspective. In Galletta, D.F. and Zhang, P. eds. Human-Computer Interaction in  Management Information Systems,, M. E. Sharpe, Inc.
Parkes,A.)2017(. The effect of individual and task characteristics on decision aid reliance. Behav. Inf. Technol. 36)2(,165-177.
Saeed, K. A., & Abdinnour, S. (2011). Understanding post-adoption IS usage stages: an empirical assessment of self – service information systems. Information Systems Journal,1-26.
Sein, M. K., Bostrom, R.P., and Olfman, L. (1999). Rethinking End-user Training Strategy: Applying  Hierarchical Knowledge-level Model. Journal of End User Computing, 11 (1), pp. 32-39.
Sousa, R.D., and Goodhue, D.L.(2003). Understanding exploratory use of ERP systems. Paper Presented at the Ninth Americas Conference on Information Systems. Tampa, FL: Association for Information Systems.
Taylor, S., & Todd, P.(1995). Assessing IT Usage: The Role of Prior Experience. MIS Quarterly, 19(4), 561-570.
Tyre, M. J., and Orlikowski, W. J.(1996). The Episodic Process of Learning by Using. International Journal of Technology Management, 11(7/8),  pp. 790-798.
Van de Ven, A. H., & Delbecq, A. L. (1974). A Task Contingent Model of Work-Unit Structure. Administrative Sciences Quarterly, 19 (2),183–197.
Venkatesh, V., and Davis, F. D.(2000). A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies. Management Science, 46(2), pp. 186-204.
Wetzels, M., Odekerken-Schröder, G., & Van Oppen, C. (2009). Using PLS path modeling for assessing hierarchical construct models: Guidelines and empirical illustration. MIS quarterly, 177-195.
Werts, C. E., Linn, R. L., & Jöeskog, K. G. (1974). Intraclass reliability estimates: Testing structural assumptions. Educational and Psychological Measurement, 34(1), 25–33.
Wood, R. E. (1986). Task complexity: Definition of the construct. Organizational Behavior and Human Decision Processes, 37(1), 60-82.
Wu, Y., Choi, B., Guo, X., and Chang, K.(2017). Understanding User Adaptation toward a New IT System in Organizations: A Social Network Perspective. Journal of the Association for Information Systems, 18(11), pp. 787 – 813.  
Zmud, R. W., Apple, L. E.(1992). Measuring technology incorporation / infusion. Journal of Product Innovation Management, (9), pp. 148-155.
Davari, A., Rezazadeh, A.(2014). Structural equation modeling with PLS software. Iranian Student Book Agency,1st ed.,Tehran.[In Persian].