ارزیابی چابکی زنجیره تأمین با رویکرد تصمیم‌گیری تلفیقی دلفی- فازی(مطالعه میدانی: شرکت های شهرک صنعتی اهواز)
الموضوعات :
Nadiya Akbari
1
(Master of Industrial Engineering student at Azad University, Masjed Soleyman)
Arman Sajedinejad
2
(Assistant Professor, Iranian Research Institute for Information Science and Technology (IRANDOC))
تاريخ الإرسال : 12 الثلاثاء , رجب, 1437
تاريخ التأكيد : 13 الإثنين , شوال, 1437
تاريخ الإصدار : 22 الخميس , ذو القعدة, 1437
الکلمات المفتاحية:
Supply Chain,
VIKOR,
فرآیند تحلیل شبکه,
دلفی فازی,
ANP,
چابکی,
ویکور,
Agility,
زنجیره تأمین,
دیماتل,
fuzzy Delphi,
DEMATELT,
ملخص المقالة :
چابکی زنجیره تأمین از جمله موضوعاتی است که در تحقیقات سال های اخیر مورد توجه قرار گرفته و فعالیت‌های تحقیقاتی متنوعی بروی آن انجام شده است. یکی از دلایل این مساله توجه صنعت به این چابکی به عنوان عاملی برای ورود سریع به بازار و جذب رضایت مشتریان از زنجیره است. ارزیابی موثر و کارای چابکی زنجیره تأمین شرکتها امری ضروری و چالش برانگیز برای شرکتها میباشد و هدف این پژوهش ارزیابی چابکی زنجیره تأمین شرکتهای تولیدی شهرک صنعتی اهواز با رویکرد تلفیقی دلفی فازی و تصمیم گیری با معیارهای چندگانه میباشد. در این تحقیق ضمن شناسایی شاخصها و طراحی مدل مفهومی با استفاده از تکنیک دلفی فازی، ارزیابی چابکی زنجیره تأمین شرکتها را با رویکرد تلفیقی دیماتل تجدید نظر شده، FANP و ویکور بررسی می‌نماییم. از نتایج این تحقیق به نقش با اولویت رضایت مشتری در بین ابعاد مختلف و پس از آن بهبود کیفیت و معرفی محصول جدید می‌توان اشاره نمود. لازم به ذکر است که نتایج حاصله با اسناد موجود و نظرات مدیران ارشد همخوانی داشته و این مطلب گویای کارایی بالای رویکرد پیشنهادی پژوهش در رتبه بندی عملکرد میباشد.
المصادر:
Chu, T. C., & Varma, R. (2012). Evaluating suppliers via a multiple levels multiple criteria decision making method under fuzzy environment. Computers & Industrial Engineering, 62(2), 653-660.
Haq, A. N., & Boddu, V. (2015). Analysis of agile supply chain enablers for Indian food processing industries using analytical hierarchy process. International Journal of Manufacturing Technology and Management, 29(1-2), 30-47.
Harrison, A., Christopher, M., & Hoek, R. v. (1999). Creating the Agile Supply Chain: Issues and Challenges. London: Institute of Logistics & Transport.
Jassbi, J., Seyedhosseini, S. M., & Pilevari, N. (2010). An Adaptive Neuro Fuzzy Inference System for Supply chain Agility Evaluation. International Journal of Industrial Engineering & Production Research, 20(4), 187- 196.
Keeney, R. L. (2006). Value-Focused Thinking: A Path to Creative Decision Making. Cambridge: Harvard University Press.
Lin, C. T., Chiu, H., & Tseng, Y. H. (2006). Agility Evaluation Using Fuzzy Logic. International Journal of Production Economics, 101(2), 101, 353- 368.
Mirsayafi, C. E. (2013). Identify and rank the factors affecting supply chain agility. Tehran: Islamic Azad University Central Tehran Branch Master’s thesis.
Mohaghar, E., Malaei, M., & Afzlyan, M. (2014). Ranking of the key factors in the success of agile supply chain design and production of cultural products. Supply Chain Management, 16(43), 54-61.
Ngai, E. W., Chau, D. C., & Chan, T. L. (2011). Information technology, operational, and management competencies for supply chain agility: Findings from case studies. Journal of Strategic Information Systems, 20, 232–249.
Novjavan, M., Hashemi, M., & Teimoori, E. (2014). Measurement of supply chain flexibility combined with AHP model and fuzzy TOPSIS (Case study: Garments). Tenth Conference international industrial Engineering (pp. 1-10). College of Industrial Engineering, 4.
Seyedhoseini, S. M., Jassbi, J., & Pilevari, N. (2010). Application of adaptive neuro fuzzy inference system in measurement of supply chain agility: Real case study of a manufacturing company. African Journal of Business Management, 4(1), 83-95.
Sharifi, H., & Zhang, Z. (1999). A methodology for achieving agility in manufacturing organisations: an introduction. International Journal of Production Economics, 62, 7–22.
Sherehiy, B., Karwowski, W., & Layer, J. K. (2007). A review of enterprise agility: Concepts, frameworks, and attributes. International Journal of Industrial Ergonomics, 37(5), 445-460.
Tizro, A., Azar, A., Ahmadi, R., & Rafie, M. (2010). A model of supply chain agility Case: steel company. Journal of Industrial Management, 3(7), 17-36.
Vinodh, S., & Devadasan, S. R. (2011). Twenty criteria based agility assessment using fuzzy logic approach. The International Journal of Advanced Manufacturing Technology, 54(9), 1219–1231.
Yang, J. (2014). Supply chain agility: Securing performance for Chinese manufacturers. International Journal of Production Economics, 150, 104–
Yusuf, Y. Y., Gunasekaran, A., Musa, A., Dauda, M., El-Berishy, N. M., & Cang, N. (2014). A relational study of supply chain agility, competitiveness and business performance in the oil and gas industry. International Journal of Production Economics, 14, 531-543.
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Chu, T. C., & Varma, R. (2012). Evaluating suppliers via a multiple levels multiple criteria decision making method under fuzzy environment. Computers & Industrial Engineering, 62(2), 653-660.
Haq, A. N., & Boddu, V. (2015). Analysis of agile supply chain enablers for Indian food processing industries using analytical hierarchy process. International Journal of Manufacturing Technology and Management, 29(1-2), 30-47.
Harrison, A., Christopher, M., & Hoek, R. v. (1999). Creating the Agile Supply Chain: Issues and Challenges. London: Institute of Logistics & Transport.
Jassbi, J., Seyedhosseini, S. M., & Pilevari, N. (2010). An Adaptive Neuro Fuzzy Inference System for Supply chain Agility Evaluation. International Journal of Industrial Engineering & Production Research, 20(4), 187- 196.
Keeney, R. L. (2006). Value-Focused Thinking: A Path to Creative Decision Making. Cambridge: Harvard University Press.
Lin, C. T., Chiu, H., & Tseng, Y. H. (2006). Agility Evaluation Using Fuzzy Logic. International Journal of Production Economics, 101(2), 101, 353- 368.
Mirsayafi, C. E. (2013). Identify and rank the factors affecting supply chain agility. Tehran: Islamic Azad University Central Tehran Branch Master’s thesis.
Mohaghar, E., Malaei, M., & Afzlyan, M. (2014). Ranking of the key factors in the success of agile supply chain design and production of cultural products. Supply Chain Management, 16(43), 54-61.
Ngai, E. W., Chau, D. C., & Chan, T. L. (2011). Information technology, operational, and management competencies for supply chain agility: Findings from case studies. Journal of Strategic Information Systems, 20, 232–249.
Novjavan, M., Hashemi, M., & Teimoori, E. (2014). Measurement of supply chain flexibility combined with AHP model and fuzzy TOPSIS (Case study: Garments). Tenth Conference international industrial Engineering (pp. 1-10). College of Industrial Engineering, 4.
Seyedhoseini, S. M., Jassbi, J., & Pilevari, N. (2010). Application of adaptive neuro fuzzy inference system in measurement of supply chain agility: Real case study of a manufacturing company. African Journal of Business Management, 4(1), 83-95.
Sharifi, H., & Zhang, Z. (1999). A methodology for achieving agility in manufacturing organisations: an introduction. International Journal of Production Economics, 62, 7–22.
Sherehiy, B., Karwowski, W., & Layer, J. K. (2007). A review of enterprise agility: Concepts, frameworks, and attributes. International Journal of Industrial Ergonomics, 37(5), 445-460.
Tizro, A., Azar, A., Ahmadi, R., & Rafie, M. (2010). A model of supply chain agility Case: steel company. Journal of Industrial Management, 3(7), 17-36.
Vinodh, S., & Devadasan, S. R. (2011). Twenty criteria based agility assessment using fuzzy logic approach. The International Journal of Advanced Manufacturing Technology, 54(9), 1219–1231.
Yang, J. (2014). Supply chain agility: Securing performance for Chinese manufacturers. International Journal of Production Economics, 150, 104–
Yusuf, Y. Y., Gunasekaran, A., Musa, A., Dauda, M., El-Berishy, N. M., & Cang, N. (2014). A relational study of supply chain agility, competitiveness and business performance in the oil and gas industry. International Journal of Production Economics, 14, 531-543.
