بررسی و سنجش کشسانی زنجیره تأمین با رویکرد منطق فازی (شاهد تجربی: صنعت ساخت قطعات اتومبیل در استان مازندران)
محورهای موضوعی :
مدیریت صنعتی
Hassanali Aghajani
1
,
Hossein Samadi Miarkolaei
2
,
Mohamad Farmanzadeh
3
1 - Faculty of Mathematics, Payam Noor University, Hamadan, Hamadan, Iran
2 - M. A in Management, Young Researchers Club, Qameshahar Branch, Islamic Azad University, Qameshahar, Iran
3 - M.A in Business Management
تاریخ دریافت : 1393/07/01
تاریخ پذیرش : 1396/10/22
تاریخ انتشار : 1394/01/20
کلید واژه:
Supply Chain,
fuzzy logic,
منطق فازی,
resilience,
زنجیره تأمین,
Membership function,
کشسانی,
تابع عضویت,
صنعت قطعه سازی,
Automobile parts manufacturing industry,
چکیده مقاله :
زنجیره تأمین برای بقا در بازارهای پویا و متغیر، نیازمند ابزاری است که بتواند با کمک آن بر چالش‌های محیطی فائق آید. چنین ابزاری کشسانی است. در واقع محیط کسب و کار همواره در حال تغییر است و تغییر ایجاد کننده ریسک است. مدیریت این ریسک به سرعت در حال تغییر، یک چالش رقابتی است که نیازمند کشسانی؛ یعنی توانایی زنده ماندن، وفق یافتن و رشد در مواجهه با تغییرات متلاطم می باشد. بر این اساس هدف از تحقیق حاضر، بررسی و ارزیابی کشسانی و کشسانی زنجیره تأمین با انجام آزمونی تجربی در صنعت ساخت قطعات اتومبیل در استان مازندران می باشد. نمونه آماری، 31 شرکت و ابزار جمع آوری داده ها پرسشنامه ای با اجزاء استاندارد و ضریب پایایی 85/0 بوده و داده ها با استفاده آزمون فرضیه فازی مورد تحلیل قرار گرفتند و امکان تاثیرگذاری هر یک از شاخص ها با توجه به درجه (تابع) عضویت پذیرش آن مشخص گردید. در پایان نتیجه‌گیری شده است که مدیران، عوامل توانمندسازی را که دارای درجه عضویت پایینی هستند، تقویت نموده و اثرات عوامل آسیب پذیری را که دارای درجه عضویت بالایی هستند، کاهش دهند تا دارای کشسانی بالاتری در زنجیره تامین خود باشند.
چکیده انگلیسی:
The supply chain needs the cooperative instrument to face environment challenge for survival in turbulent and volatile markets. This instrument is agility. In fact, the business environment is constantly changing and change creates risk. The risk management is rapidly changing, competitive challenges that require elastic; namely ability to survive, adapt and grow in the face of turbulent change. Accordingly, the purpose of present paper is explanation and evaluation of resilience and supply chain resilience by means of an empirical examination in automobile parts manufacturing industry in Mazandaran. The sample in research was 31 companies, and data collection tools were questionnaire including some standard questions with the reliability of 0.85, and data were analyzed using fuzzy hypothesis test. The possibility of the effectiveness of each factor is determined according to their membership functions of acceptance. Finally, it is concluded that managers must to support capability factors that have low membership functions and reduce the effectiveness of vulnerability factors that have high membership functions to receive higher supply chain resilience.
منابع و مأخذ:
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Churchill, G.A. (1979). A paradigm for developing better measures of marketing constructs. Journal of Marketing Research, 16, 64–73.
Christopher, M. (1998). Logistics and supply chain management. 2nd ed., London: FT Prentice-Hall.
Edmondson, A.C. (1999). Psychological safety and learning behavior in work teams. Administrative Science Quarterly, 44, 350–383.
Fiksel, J. (2006). Sustainability and resilience: Toward a systems approach. Sustainability: Science, Practice & Policy, 2(2), 1–8.
Folke, C., & Carpenter, S., & Walker, B., & Scheffer M., & Elmqvist, T., & Gunderson, L. (2004). Regime shifts, resilience and biodiversity in ecosystem management. Annual Review of Ecology, Evolution, & Systematics, 35, 557–581.
Gorman, C., & Sarah, S., & Grossman, W., & Klarreich, K., & McDowell, J., & Whitaker, L. (2005). The importance of Resilience, Time Canada, 165(3), 76–79.
Hamel, G., & Valikangas, L. (2003). The quest for resilience, Harvard Business Review, September. 52–63.
Handfield, R. & Nichols, E. (1999). An introduction to supply chain management, (pp. 10– 15). Upper Saddle River, NJ: Prentice Hall.
Hult, G.M.T. & Ferrell, O.C. (1997). A Global Learning Organization Structure and Market Information Processing, Journal or Business Research, 40, 155–166.
Li, D.F. (2007). Compromise ratio method for fuzzy multi-attribute group decision making, Applied soft computing, 7, 807–817.
Melnyk, S.A., & M. Cooper, B., & Griffis, S.E., & Macdonald, J.R. & Phillips, C.L.M. (2010). Supplier Base Management: A New Competitive Edge. Supply Chain Management Review, July/August, 35–41.
Webster. M. (2007). Merriam-Webster Dictionary, Springfield, MA: Merriam-Webster, Inc.
Nunnally, J. C. (1978). Psychometric theory, Second ed., McGraw-Hill, New York.
Parasuraman, A., & Zeithaml, V. A., & Berry, L. L. (1988). SERVQUAL: a Multi-item Scale for Measuring Consumer Perceptions of Service, Journal of Retailing, 64, 2–40.
Peck, H. (2005). Finding better ways to deal with disasters. Logistics & Transport Focus, 7(10), 19–21.
Peterson, R. A. (1994). A meta-analysis of cronbach,s coefficient alpha. Journal of consumer research, 21, 381–391.
Pettit, T.J., & Fiksel, J., & Croxton, K.L. (2008). Ensuring supply chain resilience: Development of a conceptual framework. Journal of Business Logistics, conditionally accepted.
Pickett, C. (2006). Prepaire for supply chain disruptions before they hit. Logistics Today, 47(6), 22–25.
Ponomorov, S.Y., & Holcomb, M.C. (2009). Undrestanding the concept of supply chain resilience. The International Jornal of Logistics Management. 20(1), 124–143.
Rice, J.B. & Caniato, F. (2003). Building a secure and resilient supply network. Supply Chain Management Review, September/October, 22–30.
Saremi, M., & Mousavi, S.F., & Sansyei, A. (2009). TQM consultant selection in SMEs with TOPSIS under fuzzy environment. Expert systems with Application, 36, 2742–2749.
Sheffi, Y. (2005). The resilient enterprise: Overcoming vulnerability for competitive advantage. Cambridge, MA: MIT Press.
Simchi, L.D. & Kaminsky, P. (2000). Designing and managing the supply chain. New York, Mc Graw Hill.
Shojaei, A., & Beygi, T., & Fotros, M H. (2001). Fuzzy Approach to Ranking the Impact of Intellectual Capital Components on the Performance of a University. Productivity Management (Beyond Management), 5(9), 77–107.
Svensson, G. (2002). Dyadic vulnerability in companies' inbound and outbound logistics flows. International Journal of Logistics and Research Applications, 5(1). 13–44.
Tang, C.S. (2006). Robust strategies for mitigating supply chain disruptions. International Journal of Logistics: Research and Applications, 9(1), 33–45.
Van de ven, A. & Ferry, D. (1979). Measuring and assessing organizations. John Wiley, New York.
Wang, W.Y & Chang, C. (2005). Intellectual Capital and Performance in Causal Models: Evidence from the Information Technology Industry in Taiwan. Journal of Intellectual Capital, 6(2), 222–236.
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Bunderson, J.S., & Sutcliffe, K.M. (2002). Comparing alternative conceptualization of functional diversity in management teams: process and performance effects, Academy of Management Journal, 45, 847–93.
Christopher, M. (2005). Managing risk in the supply chain, in Christopher, M. (Ed.), Logistics & Supply Chain Management, 3rd ed., Prentice-Hall, Harlow.
Christopher, M., & Christine, R. (2004). Creating supply chain resilience through agile six sigma, Critical EYE, Jun-Aug 2004. 24–28.
Christopher, M., & Peck, H. (2004). Building the resilient supply chain, International Journal of Logistics Management, 15(2), 1–13.
Conca, F. J., & Liopis, J., & Tarí, J. J. (2004). Development of a measure to assess quality management in certified firms, European journal of operational research, 156, 683–697.
Cranfield University. (2003). Creating resilient supply chain: A practical guide, Centre for Logistics and Supply Chain Management, School of Business, Cranfield University.
Cronbach, L J. (1951). Coefficient alpha and the internal structure of test, Psychometricka, 16. 297–334.
Churchill, G.A. (1979). A paradigm for developing better measures of marketing constructs. Journal of Marketing Research, 16, 64–73.
Christopher, M. (1998). Logistics and supply chain management. 2nd ed., London: FT Prentice-Hall.
Edmondson, A.C. (1999). Psychological safety and learning behavior in work teams. Administrative Science Quarterly, 44, 350–383.
Fiksel, J. (2006). Sustainability and resilience: Toward a systems approach. Sustainability: Science, Practice & Policy, 2(2), 1–8.
Folke, C., & Carpenter, S., & Walker, B., & Scheffer M., & Elmqvist, T., & Gunderson, L. (2004). Regime shifts, resilience and biodiversity in ecosystem management. Annual Review of Ecology, Evolution, & Systematics, 35, 557–581.
Gorman, C., & Sarah, S., & Grossman, W., & Klarreich, K., & McDowell, J., & Whitaker, L. (2005). The importance of Resilience, Time Canada, 165(3), 76–79.
Hamel, G., & Valikangas, L. (2003). The quest for resilience, Harvard Business Review, September. 52–63.
Handfield, R. & Nichols, E. (1999). An introduction to supply chain management, (pp. 10– 15). Upper Saddle River, NJ: Prentice Hall.
Hult, G.M.T. & Ferrell, O.C. (1997). A Global Learning Organization Structure and Market Information Processing, Journal or Business Research, 40, 155–166.
Li, D.F. (2007). Compromise ratio method for fuzzy multi-attribute group decision making, Applied soft computing, 7, 807–817.
Melnyk, S.A., & M. Cooper, B., & Griffis, S.E., & Macdonald, J.R. & Phillips, C.L.M. (2010). Supplier Base Management: A New Competitive Edge. Supply Chain Management Review, July/August, 35–41.
Webster. M. (2007). Merriam-Webster Dictionary, Springfield, MA: Merriam-Webster, Inc.
Nunnally, J. C. (1978). Psychometric theory, Second ed., McGraw-Hill, New York.
Parasuraman, A., & Zeithaml, V. A., & Berry, L. L. (1988). SERVQUAL: a Multi-item Scale for Measuring Consumer Perceptions of Service, Journal of Retailing, 64, 2–40.
Peck, H. (2005). Finding better ways to deal with disasters. Logistics & Transport Focus, 7(10), 19–21.
Peterson, R. A. (1994). A meta-analysis of cronbach,s coefficient alpha. Journal of consumer research, 21, 381–391.
Pettit, T.J., & Fiksel, J., & Croxton, K.L. (2008). Ensuring supply chain resilience: Development of a conceptual framework. Journal of Business Logistics, conditionally accepted.
Pickett, C. (2006). Prepaire for supply chain disruptions before they hit. Logistics Today, 47(6), 22–25.
Ponomorov, S.Y., & Holcomb, M.C. (2009). Undrestanding the concept of supply chain resilience. The International Jornal of Logistics Management. 20(1), 124–143.
Rice, J.B. & Caniato, F. (2003). Building a secure and resilient supply network. Supply Chain Management Review, September/October, 22–30.
Saremi, M., & Mousavi, S.F., & Sansyei, A. (2009). TQM consultant selection in SMEs with TOPSIS under fuzzy environment. Expert systems with Application, 36, 2742–2749.
Sheffi, Y. (2005). The resilient enterprise: Overcoming vulnerability for competitive advantage. Cambridge, MA: MIT Press.
Simchi, L.D. & Kaminsky, P. (2000). Designing and managing the supply chain. New York, Mc Graw Hill.
Shojaei, A., & Beygi, T., & Fotros, M H. (2001). Fuzzy Approach to Ranking the Impact of Intellectual Capital Components on the Performance of a University. Productivity Management (Beyond Management), 5(9), 77–107.
Svensson, G. (2002). Dyadic vulnerability in companies' inbound and outbound logistics flows. International Journal of Logistics and Research Applications, 5(1). 13–44.
Tang, C.S. (2006). Robust strategies for mitigating supply chain disruptions. International Journal of Logistics: Research and Applications, 9(1), 33–45.
Van de ven, A. & Ferry, D. (1979). Measuring and assessing organizations. John Wiley, New York.
Wang, W.Y & Chang, C. (2005). Intellectual Capital and Performance in Causal Models: Evidence from the Information Technology Industry in Taiwan. Journal of Intellectual Capital, 6(2), 222–236.
