ارزیابی تامین‌کنندگان تاب‌آور با استفاده از سیستم نسبی فازی و فرآیند تحلیل شبکه ای
محورهای موضوعی :
توسعه پایدار
هاشم معزز
1
(استادیار گروه مدیریت صنعتی و مالی، دانشکده مدیریت و حسابداری، پردیس فارابی دانشگاه تهران، قم، ایران)
محمد رضا فتحی
2
(استادیار بخش تخصصی مدیریت صنعتی و فناوری، دانشکده مدیریت و حسابداری، پردیس فارابی دانشگاه تهران، قم، ایران* (مسئول مکاتبات))
داوود رمضانی کرمانی
3
(کارشناس ارشد مدیریت صنعتی، دانشکده مدیریت و حسابداری، پردیس فارابی دانشگاه تهران، قم، ایران)
تاریخ دریافت : 1395/11/30
تاریخ پذیرش : 1396/05/25
تاریخ انتشار : 1400/01/01
کلید واژه:
تصمیم‌گیری چند شاخصه,
تاب‌آوری,
فرآیند تحلیل شبکه‌ای,
تامین‌کننده,
سیستم نسبی فازی,
چکیده مقاله :
زمینه و هدف: مدیریت مناسب یک زنجیره تأمین، ‎ارزیابی و انتخاب تأمین‎کنندگان از اهمیت ویژه‎ای برخوردار است. که می تواند سودآوری سازمان را در بلند مدت تحت تاثیر قرار دهد. این تحقیق با هدف ارایه چارچوبی جهت ارزیابی تامین‌کنندگان تاب‌آور انجام گرفته است.روش بررسی: محقق از طریق مطالعات کتابخانه ای و مصاحبه با کارشناسان و خبرگان شرکت و تهیه پرسش نامه به شناسایی عوامل موثر در انتخاب تامین کننده تاب آور پرداخته است.در این تحقیق از دو تکنیک فرآیند تحلیل شبکه ای جهت تعیین وزن معیارها و سیستم نسبی فازی جهت رتبه بندی گزینه ها استفاده شده است.یافته ها: معیارها و عوامل تاثیر گذار در انتخاب تامین کننده تاب آور، شامل فاکتورهای اصلی عملکرد، حداقل سازی ریسک، پاسخ گویی، پشتوانه فنی و قدرت می باشد. در این تحقیق با انجام مقایسات زوجی بین عوامل و با استفاده از فرآیند تحلیل شبکه ای، وزن این معیارها تعیین گردید. به علاوه تکنیک سیستم نسبی فازی به عنوان یک روش نوین تصمیم‌گیری چند شاخصه، به منظور رتبه‌بندی گزینه ها استفاده شده است.بحث و نتیجه گیری: براساس نتایج بدست آمده از روش سیستم نسبی فازی، شرکت الکترونیک خودرو شرق به عنوان بهترین گزینه انتخاب شده است.
چکیده انگلیسی:
Background and Objective: Proper management of a supply chain, assessment and selection of suppliers is an important task which can affect the profitability of organization in the long time. The purpose of this research is to provide a framework for assessing Resilient Suppliers.Material and Methods: Researcher through literature review and interviews with experts of Company and preparing a questionnaire to identify the factors affect to Resilient Suppliers. In this study, two ANP techniques to determine the weighting of criteria and Fuzzy Ratio System method for ranking alternatives are used.Results: The criteria and factors that influence the selection of resilient suppliers include the main factors of performance, minimization of risk, responsiveness, Technical support and power. In this study paired comparisons carried out by ANP. In addition, Fuzzy Ratio System as a new method of fuzzy multi-criteria decision-making, in order to rank the options is used.Conclusion: According to the results of Fuzzy Ratio System, S2 has been chosen as the best option.
منابع و مأخذ:
Gong, J., Mitchell, J. E., Krishnamurthy, A., & Wallace, W. A. (2014). An interdependent layered network model for a resilient supply chain. Omega, 46, 104-116.
Haldar, A., Ray, A., Banerjee, D., & Ghosh, S. (2014). Resilient supplier selection under a fuzzy environment, International Journal of Management Science and Engineering Management, 9(2), 147-156.
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Mitroff, I.I. and Alpasan, M. . (2003). Preparing for the evil, Harvard Business Review, 81(4), 109–115.
Manuj, I. and Mentzer, J. (2008). Global supply chain risk management strategies. International Journal of Physical Distribution & Logistics Management, 38(3), 192–223.
Sheffi, Y. (2005). Building a resilient supply chain, Harvard Business Review Supply Chain Strategy 1(5), 1-11.
Briano, E., Caballini, C., & Revetria, R. (2009). Literature review about supply chain vulnerability and resiliency. In Proceedings of the 8th WSEAS international conference on System science and simulation in engineering, 191-197.
Banaeian, N., Mobli, H., Fahimnia, B., Nielsen, I. E., & Omid, M. (2016). Green Supplier Selection Using Fuzzy Group Decision Making Methods: A Case Study from the Agri-Food Industry, Computers & Operations Research, 89, 337-347.
Rajabani, N., & Fathi, M. R. (2014). Proposing the Framework for Selecting the Best Sustainable Supplier Using Fuzzy Prioritization Method, Global Journal of Management Studies and Researches, 1(2), 100-108.
Mohaghar, A., Fathi, M. R., & Jafarzadeh, A. H. (2013). A supplier selection method using ar-dea and fuzzy vikor, International Journal of Industrial Engineering, 20(5), 387-400.
Chaghooshi, A. J., Fathi, M. R., Faghih, A., & Zarchi, M. K. (2012). Applying a New Integration of MCDM Techniques for Supplier Selection (Case Study: Pars Tire Company), Australian Journal of Basic and Applied Sciences, 6(2), 9-19.
Chaghooshi, A., Fathi, M. R., Avazpour, R., & Ebrahimi, E. (2014). A Combined Approach for Supplier Selection: Fuzzy AHP and Fuzzy VIKOR, International Journal of Engineering Sciences, 3(8), 67-74.
Safari, H., Fagheyi, M. S., Ahangari, S. S., & Fathi, M. R. (2012). Applying Promethee method based on entropy weight for supplier selection, Business management and strategy, 3(1), 97-106.
Chen, C. T., Lin, C. T., & Huang, S. F. (2006). A fuzzy approach for supplier evaluation and selection in supply chain management, International journal of production economics, 102(2), 289-301.
Rajesh, R., & Ravi, V. (2015). Supplier selection in resilient supply chains: a grey relational analysis approach, Journal of Cleaner Production, 86, 343-359.
Wang, Y. X., (2005). Application of fuzzy decision optimum model in selecting supplier, The Journal of Science Technology and Engineering 5(15), 1100-1103.
Yang, C. C., Chen, B. S. (2006). Supplier selection using combined analytical hierarchy process and grey relational analysis, Journal of Manufacturing Technology Management, 17(7), 926-941.
Li, G. D., Yamaguchi, D., Nagai, M. (2007). A grey-based decision-making approach to the supplier selection problem, Mathematical and computer modelling, 46(3), 573-581.
Demirtas, E. A., Üstün, Ö. (2008). An integrated multiobjective decision making process for supplier selection and order allocation, Omega, 36(1), 76-90.
Wu, D. (2009). Supplier selection: A hybrid model using DEA, decision tree and neural network, Expert Systems with Applications, 36(5), 9105-9112.
Boran, F. E., Genç, S., Kurt, M., Akay, D. (2009). A multicriteria intuitionistic fuzzy group decision making for supplier selection with TOPSIS method, Expert Systems with Applications, 36(8), 11363-11368.
Kokangul, A., Susuz, Z. (2009). Integrated analytical hierarch process and mathematical programming to supplier selection problem with quantity discount, Applied mathematical modelling, 33(3), 1417-1429.
Thanaraksakul, W., Phruksaphanrat, B. (2009). Supplier evaluation framework based on balanced scorecard with integrated corporate social responsibility perspective, Proceedings of the International MultiConference of Engineers and Computer Scientists, 2, 5-10.
Vinodh, S., Anesh Ramiya, R., Gautham, S. G. (2011). Application of fuzzy analytic network process for supplier selection in a manufacturing organisation, Expert Systems with Applications, 38(1), 272-280.
Golmohammadi, D., Mellat-Parast, M. (2012). Developing a grey-based decision-making model for supplier selection, International Journal of Production Economics, 137(2), 191-200.
Brauers, W. K. M., & Zavadskas, E. K. (2006). The MOORA method and its application to privatization in a transition economy, Control and Cybernetics, 35(2), 445–469.
Brauers, W. K. M., & Zavadskas, E. K. (2010a). Project management by MULTIMOORA as an instrument for transition economies, Technological and Economic Development of Economy, 16(1), 5–24.
Brauers, W. K. M., Balezˇentis, A., & Balezˇentis, T. (2011). MULTIMOORA for the EU Member States updated with fuzzy number theory, Technological and Economic Development of Economy, 17(2), 259–290.
Baležentis, A., Baležentis, T., & Brauers, W. K. (2012). Personnel selection based on computing with words and fuzzy MULTIMOORA, Expert Systems with Applications, 39(9), 7961-7967.
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Gong, J., Mitchell, J. E., Krishnamurthy, A., & Wallace, W. A. (2014). An interdependent layered network model for a resilient supply chain. Omega, 46, 104-116.
Haldar, A., Ray, A., Banerjee, D., & Ghosh, S. (2014). Resilient supplier selection under a fuzzy environment, International Journal of Management Science and Engineering Management, 9(2), 147-156.
Hamel, G. and Valikangas, L. (2003). The quest for resilience, Harvard Business Review, 81(9), 52–63.
Mitroff, I.I. and Alpasan, M. . (2003). Preparing for the evil, Harvard Business Review, 81(4), 109–115.
Manuj, I. and Mentzer, J. (2008). Global supply chain risk management strategies. International Journal of Physical Distribution & Logistics Management, 38(3), 192–223.
Sheffi, Y. (2005). Building a resilient supply chain, Harvard Business Review Supply Chain Strategy 1(5), 1-11.
Briano, E., Caballini, C., & Revetria, R. (2009). Literature review about supply chain vulnerability and resiliency. In Proceedings of the 8th WSEAS international conference on System science and simulation in engineering, 191-197.
Banaeian, N., Mobli, H., Fahimnia, B., Nielsen, I. E., & Omid, M. (2016). Green Supplier Selection Using Fuzzy Group Decision Making Methods: A Case Study from the Agri-Food Industry, Computers & Operations Research, 89, 337-347.
Rajabani, N., & Fathi, M. R. (2014). Proposing the Framework for Selecting the Best Sustainable Supplier Using Fuzzy Prioritization Method, Global Journal of Management Studies and Researches, 1(2), 100-108.
Mohaghar, A., Fathi, M. R., & Jafarzadeh, A. H. (2013). A supplier selection method using ar-dea and fuzzy vikor, International Journal of Industrial Engineering, 20(5), 387-400.
Chaghooshi, A. J., Fathi, M. R., Faghih, A., & Zarchi, M. K. (2012). Applying a New Integration of MCDM Techniques for Supplier Selection (Case Study: Pars Tire Company), Australian Journal of Basic and Applied Sciences, 6(2), 9-19.
Chaghooshi, A., Fathi, M. R., Avazpour, R., & Ebrahimi, E. (2014). A Combined Approach for Supplier Selection: Fuzzy AHP and Fuzzy VIKOR, International Journal of Engineering Sciences, 3(8), 67-74.
Safari, H., Fagheyi, M. S., Ahangari, S. S., & Fathi, M. R. (2012). Applying Promethee method based on entropy weight for supplier selection, Business management and strategy, 3(1), 97-106.
Chen, C. T., Lin, C. T., & Huang, S. F. (2006). A fuzzy approach for supplier evaluation and selection in supply chain management, International journal of production economics, 102(2), 289-301.
Rajesh, R., & Ravi, V. (2015). Supplier selection in resilient supply chains: a grey relational analysis approach, Journal of Cleaner Production, 86, 343-359.
Wang, Y. X., (2005). Application of fuzzy decision optimum model in selecting supplier, The Journal of Science Technology and Engineering 5(15), 1100-1103.
Yang, C. C., Chen, B. S. (2006). Supplier selection using combined analytical hierarchy process and grey relational analysis, Journal of Manufacturing Technology Management, 17(7), 926-941.
Li, G. D., Yamaguchi, D., Nagai, M. (2007). A grey-based decision-making approach to the supplier selection problem, Mathematical and computer modelling, 46(3), 573-581.
Demirtas, E. A., Üstün, Ö. (2008). An integrated multiobjective decision making process for supplier selection and order allocation, Omega, 36(1), 76-90.
Wu, D. (2009). Supplier selection: A hybrid model using DEA, decision tree and neural network, Expert Systems with Applications, 36(5), 9105-9112.
Boran, F. E., Genç, S., Kurt, M., Akay, D. (2009). A multicriteria intuitionistic fuzzy group decision making for supplier selection with TOPSIS method, Expert Systems with Applications, 36(8), 11363-11368.
Kokangul, A., Susuz, Z. (2009). Integrated analytical hierarch process and mathematical programming to supplier selection problem with quantity discount, Applied mathematical modelling, 33(3), 1417-1429.
Thanaraksakul, W., Phruksaphanrat, B. (2009). Supplier evaluation framework based on balanced scorecard with integrated corporate social responsibility perspective, Proceedings of the International MultiConference of Engineers and Computer Scientists, 2, 5-10.
Vinodh, S., Anesh Ramiya, R., Gautham, S. G. (2011). Application of fuzzy analytic network process for supplier selection in a manufacturing organisation, Expert Systems with Applications, 38(1), 272-280.
Golmohammadi, D., Mellat-Parast, M. (2012). Developing a grey-based decision-making model for supplier selection, International Journal of Production Economics, 137(2), 191-200.
Brauers, W. K. M., & Zavadskas, E. K. (2006). The MOORA method and its application to privatization in a transition economy, Control and Cybernetics, 35(2), 445–469.
Brauers, W. K. M., & Zavadskas, E. K. (2010a). Project management by MULTIMOORA as an instrument for transition economies, Technological and Economic Development of Economy, 16(1), 5–24.
Brauers, W. K. M., Balezˇentis, A., & Balezˇentis, T. (2011). MULTIMOORA for the EU Member States updated with fuzzy number theory, Technological and Economic Development of Economy, 17(2), 259–290.
Baležentis, A., Baležentis, T., & Brauers, W. K. (2012). Personnel selection based on computing with words and fuzzy MULTIMOORA, Expert Systems with Applications, 39(9), 7961-7967.
