شناسایی و ارزیابی عوامل مؤثر بر تاب‌آوری فناوری در شرایط تحریم با استفاده از رویکرد الگوسازی ساختاری ـ تفسیری

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشجوی کارشناسی ارشد،دانشکده مدیریت،دانشگاه تهران، تهران، ایران

2 استادگروه مدیریت صنعتی، دانشکده مدیریت، دانشگاه تهران، تهران، ایران

3 استادیارمجتمع دانشگاهی مدیریت و مهندسی صنایع، دانشگاه صنعتی مالک اشتر، تهران، ایران

چکیده

در شرایطی که به‌دلیل غیرقابل پیش‌بینی‌بودن وضعیت محیط به‌واسطه اعمال تحریمهای بین‌المللی فشار بر سازمانها روزبه‌روز در حال افزایش است، بررسی ارتباط میان تاب‌آوری و فناوری سازمان و شناسایی عوامل مؤثر بر تاب‌آوری فناوری که همراه با نوسانات و اختلالات شدید است، اهمیت می‌یابد. این تحقیق قصد دارد عواملی را شناسایی کند که تاب‌آوری فناوری سازمان را تقویت می‌کند و ارتباط آنها را مورد بررسی قرار دهد تا میزان تأثیرپذیری این عوامل از یکدیگر و میزان تأثیرگذاری آنها را بر یکدیگر مشخص کند. برای دستیابی به این هدف، پس از بررسی جامع مقالات حوزه تاب‌آوری در تمام زمینه‌ها، فهرستی از عوامل مؤثر بر تاب‌آوری فناوری سازمانی با فناوری پیچیده استخراج شد؛ سپس با استفاده از روش دلفی فازی و با اعمال نظر خبره‌ها، عوامل کم‌اهمیت کنار گذاشته شد. در ادامه با اجرای رویکرد الگو‌سازی ساختاری ـ تفسیری (ISM) بر عوامل شناسایی‌شده، روابط آنها مشخص، و با اعمال تحلیل میک‌‌مک (MICMAC) ارتباطات محرک ـ وابسته میان عوامل هم تعیین و مشخص شد. به‌منظور اعتباربخشی به تحقیق، یکی از سازمانهای دفاعی به‌عنوان مورد مطالعاتی انتخاب شد. نتایج تحقیق حاکی است که عوامل مرتبط با زیرساخت سازمان در جهت تاب‌آوری باید در اولویت اجرا قرار بگیرد؛ هم‌چنین در اجرای دیگر عوامل دقت کافی به‌خرج داد؛ زیرا عوامل پیوندی و واسطه‌ای فراوانی در این الگو یافت شد.

کلیدواژه‌ها


عنوان مقاله [English]

Identifying and Evaluating Factors Affecting the Resilience of Technology in Sanction Situations through Structural-Interpretive Modeling Approach

نویسندگان [English]

  • seyed mehran daei niaki 1
  • ahmad jafarnezhad 2
  • Jafar Gheidar-Kheljani 3
  • mahdie hamedi 1
1 Master student, Faculty of Management, University of Tehran, Tehran, Iran
2 Professor, Department of Industrial Management, Faculty of Management, University of Tehran, Tehran, Iran
3 Assistant Professor, University of Industrial Management and Engineering, Malek Ashtar University of Technology, Tehran, Iran
چکیده [English]

In the unpredictable environmental situation caused by international sanctions, which has put increasing pressures on organizations, it seems quite essential to investigate the relationship between resilience and technology and identify effective factors in technology resilience facing severe fluctuations and disruptions. This study aims at identifying the factors which enhance the technology resilience of organizations and investigating their relationship to define the extent to which these factors are affected by and affect on one another. With this regard, having a comprehensive review of the literature in all fields of resilience, the researchers arranged a list of factors affecting the resilience of organizational technology in relation to complex technology. Afterwards, using Fuzzy-Delphi method and applying the opinion of experts, insignificant factors were eliminated. Applying the structural-interpretive modeling (ISM) approach to the identified factors, the researchers defined relationships between these factors. The stimulus-dependent relationships between the factors were explained through Micmac Analysis. In order to validate the research, a defense organization was selected as the case study. The results indicated that factors related to the organizations infrastructure in relation to resilience should be prioritized for implementation.  Close attention must be paid to other factors as well because many linking and mediating factors are present in this model.
 

کلیدواژه‌ها [English]

  • organization resilience
  • technology resilience
  • Fuzzy Delphi Method
  • interpretive structural modeling
جعفرنژاد چقوشی، ا.؛ رجبانی، ن.؛ خلیلی اسبوئی، ص.، و حکیمی، ن. (1398)، شناسایی و رتبه‌بندی استراتژی‌های مناسب تاب‌آوری زنجیره تأمین؛ رویکردی ترکیبی از نظریه بازی و روش‌های تصمیم‌گیری چندمعیاره فازی. چشم‌انداز مدیریت صنعتی، 9(34): 9 ـ 31.
روانستان، ک.؛ آقاجانی، ح.؛ صفایی قادیکلایی، ع.، و یحیی‌زاده‌فر، م. (1398)، تعیین استراتژی‌های تاب‌آوری و تأثیرات متقابل آنها در زنجیره تأمین ایران خودرو، مدیریت بهره‌وری، 12(48): 105 ـ 142.
کیومرثی، مسعود؛ احمدی شادمهری، محمدطاهر؛ سلیمی‌فر، مصطفی و ابریشمی، حمید (1398)، بررسی اثر تحریمهای مالی و انرژی بر شکاف تولید در اقتصاد ایران، پژوهش های اقتصادی ایران، 66 ـ 33.
Adini, B., Cohen, O., Eide, A. W., Nilsson, S., Aharonson-Daniel, L., & Herrera, I. A. (2017). Striving to be resilient: What concepts, approaches and practices should be incorporated in resilience management guidelines? Technological Forecasting and Social Change, 121, 39–49.
Annarelli, A., & Nonino, F. (2016). Strategic and operational management of organizational resilience: Current state of research and future directions. Omega, 62, 1–18.
Azadeh, A., Heydarian, D., Nemati, K., & Yazdanparast, R. (2018). Performance optimization of unique resilient human resource management system in a coal mine industry. International Journal of Systems Assurance Engineering and Management, 9(5), 1178–1197.
Balland, P.-A. (2012). Proximity and the Evolution of Collaboration Networks: Evidence from R&D projects within the GNSS industry. Regional Studies, 46(2), 741–756.
Bui, T. D., Tsai, F. M., Tseng, M. L., & Ali, M. D. H. (2020). Identifying sustainable solid waste management barriers in practice using the fuzzy Delphi method. Resources, Conservation and Recycling, 154(May 2019), 104625.
Carvalho, H., Maleki, M., & Cruz-Machado, V. (2012). The links between supply chain disturbances and resilience strategies. International Journal of Agile Systems and Management, 5(3), 203–234.
Coutu, D. L. (2002). How Resilience Works. Harvard Business Review, 80(5), 46–56.
Cumming, G. S., Barnes, G., Perz, S., Schmink, M., Sieving, K. E., Southworth, J., … Van Holt, T. (2005). An exploratory framework for the empirical measurement of resilience. Ecosystems, 8(8), 975–987.
Dalkey, N., & Helmer, O. (1963). An Experimental Application of the DELPHI Method to the Use of Experts. Management Science, 9(3), 458–467.
Dinh, L., Pasman, H., Gao, X., & Mannan, M. (2012). Resilience engineering of industrial processes: principles and contributing factors. Journal of Loss Prevention in the Process Industries, 25(2), 233–241.
Duchek, S. (2020). Organizational resilience: a capability-based conceptualization. Business Research, 13(1), 215–246.
Faisal, M. N., Banwet, D. K., & Shankar, R. (2006). Supply chain risk mitigation: Modeling the enablers. Business Process Management Journal, 12(4), 535–552.
Guan, L., Abbasi, A., & Ryan, M. J. (2020). Analyzing green building project risk interdependencies using Interpretive Structural Modeling. Journal of Cleaner Production, 256, 120372.
Hatch, M. J. (2018). Organization theory: Modern, symbolic, and postmodern perspectives. Oxford university press.
Heshmati, A., & Dibaji, S. M. (2019). Science, Technology, and Innovation Status in Iran: Main Challenges. Science, Technology and Society, 24(3), 545-578.
Hills, J. M., Μichalena, E., & Chalvatzis, K. J. (2018). Innovative technology in the Pacific: Building resilience for vulnerable communities. Technological Forecasting and Social Change, 129(January), 16–26.
Holling, C. S. (1973). Resilience and stability of ecological systems. Annual Review of Ecology and Systematics, 4(1), 1–23.
Hsu, Y. L., Lee, C. H., & Kreng, V. B. (2010). The application of Fuzzy Delphi Method and Fuzzy AHP in lubricant regenerative technology selection. Expert Systems with Applications, 37(1), 419–425.
Iakovou, E., Vlachos, D., & Xanthopoulos, A. (2007). An analytical methodological framework for the optimal design of resilient supply chains. International Journal of Logistics Economics and Globalisation, 1(1), 1.
Lee, S., & Seo, K. K. (2016). A Hybrid Multi-Criteria Decision-Making Model for a Cloud Service Selection Problem Using BSC, Fuzzy Delphi Method and Fuzzy AHP. Wireless Personal Communications, 86(1), 57–75.
Lengnick-Hall, C. A., Beck, T. E., & Lengnick-Hall, M. L. (2011). Developing a capacity for organizational resilience through strategic human resource management. Human Resource Management Review, 21, 243–255.
Malek, J., & Desai, T. N. (2019). Interpretive structural modelling based analysis of sustainable manufacturing enablers. Journal of Cleaner Production, 238, 117996.
Mark, G., & Semaan, B. (2008, November). Resilience in collaboration: Technology as a resource for new patterns of action. In Proceedings of the 2008 ACM conference on Computer supported cooperative work (pp. 137-146).
Meyer, A. D. (1982). Adapting to environmental jolts. Administrative Science Quarterly, 27(4), 515–537.
Mukisa, N., Zamora, R., & Lie, T. T. (2020). Assessment of community sustainable livelihoods capitals for the implementation of alternative energy technologies in Uganda – Africa. Renewable Energy, 160, 886–902.
Murray, T. J., Pipino, L. L., & van Gigch, J. P. (1985). A pilot study of fuzzy set modification of Delphi. Human Systems Management, 5(1), 76–80.
Pal, R., Torstensson, H., & Mattila, H. (2014). Antecedents of organizational resilience in economic crises - An empirical study of Swedish textile and clothing SMEs. International Journal of Production Economics, 147(PART B), 410–428.
Rose, A., & Krausmann, E. (2013). An economic framework for the development of a resilience index for business recovery. International Journal of Disaster Risk Reduction, 5, 73–83.
Ruiz-Benítez, R., López, C., & Real, J. C. (2018). The lean and resilient management of the supply chain and its impact on performance. International Journal of Production Economics, 203, 190–202.
Scholten, K., Scott, P. S., & Fynes, B. (2014). Mitigation processes - antecedents for building supply chain resilience. Supply Chain Management, 19(2), 211–228.
Sharma, S., & Sharma, S. K. (2020). Probing the Links Between Team Resilience, Competitive Advantage, and Organizational Effectiveness: Evidence from Information Technology Industry. Business Perspectives and Research, 2278533719887458.
Sheffi, Y., & Rice Jr, J. (2005). A supply chain view of the resilient enterprise. MIT Sloan Management Review, 47(1), 41.
Swanstrom, T. (2008). Regional resilience: a critical examination of the ecological framework.
Tan, T., Chen, K., Xue, F., & Lu, W. (2019). Barriers to Building Information Modeling (BIM) implementation in China’s prefabricated construction: An interpretive structural modeling (ISM) approach. Journal of Cleaner Production, 219, 949–959.
Tatoglu, E., Bayraktar, E., Golgeci, I., Koh, S. C. L., Demirbag, M., & Zaim, S. (2016). How do supply chain management and information systems practices influence operational performance? Evidence from emerging country SMEs. International Journal of Logistics Research and Applications, 19(3), 181–199.
Teixeira, E. de O., & Werther Jr., W. B. (2013). Resilience: Continuous renewal of competitive advantages. Business Horizons, 56(3), 333–342.
Warfield, J. (1976). Societal Systems, Planning, Policy and Complexity. NW York: Wiley.
Weick, K. E. (1993). The collapse of sensemaking in organizations: The Mann Gulch disaster. Administrative Science Quarterly, 38(4), 628–652.
Yazdani-Chamzini, A., & Yakhchali, S. H. (2012). Tunnel Boring Machine (TBM) selection using fuzzy multicriteria decision making methods. Tunnelling and Underground Space Technology, 30, 194–204.
Zeleny, M. (1986). High technology management. Human Systems Management, 6(2), 109–120.