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کد مقاله : 537166 بازدید : 105 صفحه: 25 - 34

نوع مقاله: پژوهشی

شناسایی و رتبه‌بندی عوامل مؤثر بر اجرای لجستیک معکوس در صنعت خودروسازی ایران با رویکرد تحلیل شبکه‌ای فازی

محورهای موضوعی : مدیریت صنعتی

Maghsood Amiri 1 (Allameh Tabatabyi University, Faculty of Accounting and Management, Tehran, Iran)
Marziyeh Bagheri 2 (Allameh Tabatabyi University, Faculty of Accounting and Management, Tehran, Iran)
Hedi Dehnad 3 (Allameh Tabatabyi University, Faculty of Accounting and Management, Tehran, Iran)

تاریخ دریافت : 1394/09/11 تاریخ پذیرش : 1395/04/28 تاریخ انتشار : 1395/06/04

کلید واژه: رتبه‌بندی, Reverse logistics, Prioritizing, تصمیم‌گیری چند معیاره, لجستیک معکوس, Fuzzy Network Analysis Process, فرایند تحلیل شبکه‌ای فازی, Multi-criteria decision-making approach,

چکیده مقاله :

امروزه لجستیک معکوس به یکی از چالش‌برانگیزترین موضوعات در حوزه زنجیره تأمین صنعت خودرو تبدیل شده است. از این ‌رو شناخت عواملی که در اجرای لجستیک معکوس تأثیرگذار می‌باشند حائز اهمیت می باشد. در دهه گذشته به موضوع لجستیک معکوس توجه زیادی شده است. از دلایلی که باعث تمرکز سازمان‌ها بر این موضوع شده است می‌توان به این موارد اشاره نمود: انگیزه‌های رقابتی، انگیزه‌های اقتصادی مستقیم و دلایل زیست‌محیطی. هم‌چنین در بسیاری از موارد وجود قوانین و مقررات خاص در حوزه برگشتی‌ها، سازمان‌ها را وادار کرده است توجه بیشتری به این بخش مبذول دارند.در این تحقیق با گردآوری معیارهای شناسایی‌شده تحقیقات پیشین و همچنین کسب نظرات خبرگان معیارهای اولیه را مشخص کردیم که شامل 3 معیار اقتصادی، محیطی و اجتماعی می‌باشد که هر کدام از این معیارها دارای چندین زیر معیار می باشند. سپس این عوامل در قالب پرسشنامه در اختیار خبرگان قرار داده شده و داده‌های گردآوری‌شده با روش تحلیل عاملی تأییدی مورد تجزیه‌وتحلیل قرار گرفته درنهایت تعدادی از عوامل حذف شده و عوامل نهایی باقی ماندند. به‌منظور رتبه‌بندی شاخص‌ها، مجدداً این عوامل از طریق پرسشنامه ANP به نظرسنجی خبرگان گذارده شده و برای اندازه‌گیری وابستگی‌های متقابل و رتبه‌بندی معیارها از تکنیک ANP فازی استفاده کردیم.

چکیده انگلیسی:

Today reverse logistics has become one of the most challenging issues in the areas of the automotive supply chain. Therefore, understanding the factors that influence the implementation of reverse logistics is important. We can point to the reasons why organizations pay attention to this subject: Competitive incentives, direct economic incentives, and environmental reasons. In many cases, there are certain rules and regulations in the areas returns that have forced the organizations to pay more attention to this sector. In this research, we determined primary criterions with collecting determined criterions of previous studies and also taking experts’ opinions which consists 3 economical, environmental and social criterions and 19 sub criterions. Then these factors were given to experts in the form of a questionnaire. The collected data were analyzed with the confirmatory factor analysis method. Finally, a number of factors have been removed and the final factors remained. In order to rank the factors, these factors were given to experts in the form of ANP (Network Analysis Process) questionnaire again. Then we used fuzzy ANP method for measuring interdependencies and criterions ranking.

منابع و مأخذ:


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_||_

 

 

  1. Bagheri Nezhad Rudbone Z. (2010). Identifying and prioritizing the factors affecting on the implementation of reverse logistics in automotive industry, Master's Thesis, Tarbiat Modares University.
    2.
  2. Bernon M&  Cullen J. (2007). An integrated approach to managing reverse logistics, International Journal of Logistics, 10(1), 41-56.
    3.
  3. Brito, M.P.D. & Dekker, R. (2003). Reverse logistics – A framework, Econometric Institute Report EI, Erasmus University, Rotterdam.
    4.
  4. Chiou C Y, Wang PY, Chen HC, Yeh CY. (2007). Green suppliers selection and assessment in GSCM using Analytic Hierarchy Process for information and electronic industry, Journal of e-Business, 9(1), 147-176.
    5.
  5. Dowlatshahi, S.  (2000). Developing a Theory of Reverse Logistics, Interface, 30, 143-244.
    6.
  6. Frota Neto JQ, Bloemhof-Ruwaard JM, Van Nunen JAEE, & Van Heck E. (2008). Designing and evaluating sustainable logistics networks, International Journal of Production Economics ,111(2), 195-208.
    7.
  7. Fruchter, B. (1954). Introduction to Factor Analysis, Oxford, England: Van.
    8.
  8. Godfrey R. (1998).  Ethical purchasing: developing the supply chain beyond the environment. In: Russel, T. (Ed.), Greener Purchasing: Opportunities and Innovations. Greenleaf Publishing, Sheffield, England.
    9.
  9.  Haghighat,  Lale. (2006). The need for supply chain management and the role of reverse logistics, Conferencing systems, procurement and construction projects and industrial equipment.
    10.
  10. Hu LT, Bentler PM, Kano Y. (1992). Can test statistics in covariance structure analysis be trusted? Psychol Bull ,112(2), 351-62.
    11.
  11. Huscroft JR. (2011). The reverse logistics in the supply chain and managing its implementation, (Doctoral dissertation, Auburn University). Retrieved August 15, from Pro Quest Dissertation.
    12.
  12. Kim Soo Hyun, wan yang jaeh and Dae Lee Kang. (2009). Vehicle Routing In Reverse logistics for Recycling end-of-life consumer electronic goods in south korea, Transportation Research, Vol 9.part D.
    13.
  13. Kulshreshtha, P. & Sarangi, S. (2001). No return, no refund: Analysis of deposit-refund systems, Journal of Economic Behavior and Organization, 46(4), 379-94.
    14.
  14. Kumar S & Putnam V. (2008). Cradle to cradle: Reverse logistics strategies and opportunities across three industry sectors, International Journal of Production Economics, 115(2), 305-315.
    15.
  15. Lattin, J.M ., Carrol, J.D., & Green, P.E. (2003). Developing of RFID- based reverse logistics system, expert systems with Applications, 36, 9299-9307.
    16.
  16. Liu, X., Tanaka,M., and Matsui,Y.  (2006). Electrical and electronic waste management in China: progress and the barriers to overcome, Waste Manag Res, 24, 92-101.
    17.
  17. Ninlawan C., Seksan P., Tossapol K. and Pilada W. (2010). The Implementation of Green Supply Chain Management Practices in Electronics Industry, Proceedings of the international multiconference of engineers and computer scientists (IMECS), 17-19.
    18.
  18. Önüt S, Kara S S, Is_ik E .(2009). Long term supplier selection using a combined fuzzy MCDM approach: A case study for a telecommunication company, Expert Systems with Applications 36, (2009) 3887–3895.
    19.
  19. Paul Wanjora Kariuki, Esther Wangethi Waiganjo .(2014). Factors Affecting Adoption of Reverse Logistics in the Kenya Manufacturing Sector: A Case Study of Coastal Bottlers Company, International Journal of Academic Research in Business and Social Sciences 4, 9.
    20.
  20. Rahman, S., Subramanian, N. (2011). Factors for implementing end-of-life computer recycling operations in reverse supply chains, International Journal of Production Economics,10, 10-16.
    21.
  21. Ravi V, Shankar R, & Tiwari M. (2005). Analyzing alternatives in reverse logistics for end-of-life computers: ANP and balanced scorecard approach. Computers & Industrial Engineering 48(2), 327-356.
    22.
  22. Ravi, V. & Shankar R. (2005). Analysis of interactions among the barriers of reverse logistics. Technological Forecasting and Social Change, 72, 1011–1029.
    23.
  23. Saaty, T. L., & Vargas, L. G. (1998). Diagnosis with dependent symptoms: Bayes theorem and the analytic network process, Operations Research, 46(4), 491–502.
    24.
  24. Subramoniam Ramesh, Donald Huisingh and Babu Chinnam Ratna. (2003). Remanufacturing for the automotive  after market- strategic factors: literature review and future research needs, journal of cleaner production, 11(17), 30-39.
    25.
  25. Tan AWK, Yu WS, Arun K. (2003). Improving the performance of a computer company in supporting its reverse logistics operations in the Asia-Pacific region”, International Journal of Physical & Logistics Management, 33(1/2), 59-74.
    26.
  26. Tibben-Lembke, R. S. and D. S. Rogers. (2002). Differences between Forward and Reverse Logistics in a Retail Environment. Supply Chain Management: An International Journal 7(5), 271-282.
    27.
  27. Yazgan Harun Rsit. (2010). Selection of dispatching rules with fuzzy ANP approach, International journal of advance manufacturing. 170, 2739-7.
    28.
  28. Yu MC, Wu PS. (2010). A simulation study of the factors influencing the design of a waste collection channel in Taiwan, International Journal of Logistics, 13(4), 257-271.
    29.
  29. Yuksel, H. (2009). An Analytical Hierarchy Process Decision Model for E-Waste Collection Center Location Selection, Proceedings of IEEE International Conference on Computers & Industrial Engineering, 6-9 July, Troyes, 10.1109/ICCIE.2009.5223889
    30.
  30. Yüksel, I, Dagdeviren, M. (2007). Using the analytic network process (ANP) in a SWOT analysis – A case study for a textile firm. Information Sciences, 177(16), 3364–3382.
    31.
  31. Zhang, Y. (2007). Analysis of major barriers of automobile reverse logistics based on ISM, Journal of Southeast University (Natural Science Edition), 37, 445-9.
    32.
  32. Zhu Q, Sarkis J, & Lai K-h. (2008). Green supply chain management implications for closing the loop. Transportation Research Part E: Logistics and Transportation Review 44(1), 1-18.
    33.

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