طراحی سیستم استنتاج فازی برای ارزیابی زنجیره تأمین سبز شرکت‌های تولیدی صادراتی

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشجوی دکتری، دانشگاه آزاد اسلامی، واحد امارات.

2 دانشیار، دانشگاه آزاد اسلامی، واحد تبریز.

3 دانشیار، دانشگاه آزاد اسلامی، واحد تهران غرب.

4 استادیار، دانشگاه آزاد اسلامی، واحد تهران مرکزی.

چکیده

هدف پژوهش حاضر طراحی سیستم استنتاج فازی برای ارزیابی زنجیره تأمین سبز شرکت­‌های تولیدی صادراتی است. این پژوهش از نظر هدف، کاربردی می‌­باشد. جامعه آماری پژوهش شامل شرکت­‌های تولیدی صادراتی در شمال­‌غرب کشور است که نمونه آماری به­‌صورت هدفمند و به تعداد 143 شرکت تعیین شد. برای جمع­‌آوری داده­‌ها از پرسشنامه پژوهشگر­ساخته مبتنی بر مبانی نظری پژوهش استفاده شد. برای بررسی روایی پرسشنامه از روایی سازه بر اساس تحلیل عاملی تأییدی بهره­گیری شد. برای بررسی پایایی پرسشنامه نیز از ضریب آلفای کرونباخ استفاده شده است. پرسشنامه­‌های پژوهش، پس از تأیید روایی و پایایی در میان اعضای نمونه آماری پژوهش توزیع شد. به­‌منظور ارزیابی زنجیره تأمین سبز شرکت‌ها از سیستم استنتاج فازی، بر اساس توابع عضویت مثلثی و استنتاج ممدانی، بهره گرفته شده است. نتایج نشان می‌­دهد که سیستم طراحی­‌شده قادر است میزان سبز­بودن زنجیره تأمین شرکت‌های صادراتی را بر اساس مقادیر عددی و واژه‌­های زبانی نشان دهد. 

کلیدواژه‌ها


عنوان مقاله [English]

Design of Fuzzy Inference System for Green Supply Chain Evaluation of Export Manufacturing Companies

نویسندگان [English]

  • Easa Narimani Ghourtoular 1
  • Naser Feg-Hi Farahmand 2
  • Nazanin Pilevari 3
  • Kamaleddin Rahmani 2
  • Mohammad Reza Motadel 4
1 Ph.D. Student, Islamic Azad University, UAE Branch.
2 Associate Professor, Islamic Azad University, Tabriz Branch.
3 Associate Professor, Islamic Azad University, West Tehran Branch.
4 Assistant Professor, Islamic Azad University, Central Tehran Branch.
چکیده [English]

This paper aims to design a fuzzy inference system to evaluate the green supply chain of export manufacturing companies. This research has been applied from the point of view of purpose. The statistical population of this study included export manufacturing companies in the northwest of the country. The statistical sample is targeted, and 143 companies are determined. A research questionnaire based on the research literature was used to collect the data. In order to examine the validity of the questionnaire, while using formal validity, the validity of the structure has been used based on confirmatory factor analysis. Cronbach's alpha coefficient was also used to evaluate the reliability of the questionnaire. The research questionnaires were distributed among the statistical sample members of the research after confirming the validity and reliability. In order to evaluate the green supply chain of companies, a fuzzy inference system has been used based on triangular membership functions and Mamdani inference. The results show that the designed system is able to show how green the supply chain of companies is based on numerical values ​​and linguistic terms.

کلیدواژه‌ها [English]

  • Fuzzy Inference System
  • Green Supply Chain
  • Export Manufacturing Companies. Input Operation
  • Production Operations
  • Output Operations
  1. Al-Ghwayeen, W. S., & Abdallah, A. B. (2018). Green supply chain management and export performance. Journal of Manufacturing Technology Management, 29(7), 1233-1252.
  2. Awasthi, A., & Kannan, G. (2016). Green supplier development program selection using NGT and VIKOR under fuzzy environment. Computers & Industrial Engineering, 91, 100-108.
  3. Azevedo, S. G., Carvalho, H., & Machado, V. C. (2011). The influence of green practices on supply chain performance: A case study approach. Transportation research part E: logistics and transportation review, 47(6), 850-871.
  4. Carter C. R. & Easton, P. L. (2011). Sustainable supply chain management: evolution and future directions. International Journal of Physical Distribution & Logistics Management, 41(1), 46-62.
  5. Charkha, P. G., & Jaju, S. B. (2014). Supply chain performance measurement system: an overview. International Journal of Business Performance and Supply Chain Modelling, 6(1), 40-60.
  6. Chou, D. C., & Chou, A. Y. (2012). Awareness of Green IT and its value model. Computer Standards & Interfaces, 34(5), 447-451.
  7. Dangelico, R. M., Pujari, D., & Pontrandolfo, P. (2017). Green product innovation in manufacturing firms: A sustainability‐oriented dynamic capability perspective. Business strategy and the Environment, 26(4), 490-506.
  8. Das, K., & Posinasetti, N. R. (2015). Addressing environmental concerns in closed loop supply chain design and planning. International Journal of Production Economics, 163, 34-47.
  9. Eltayeb, T. K., Zailani, S., & Ramayah, T. (2011). Green supply chain initiatives among certified companies in Malaysia and environmental sustainability: Investigating the outcomes. Resources, conservation and recycling, 55(5), 495-506.
  10. Eydi, A., & Bakhtiari, M. (2016). Evaluating and Selecting Two-Layers of Suppliers in Green Supply Chain using Hierarchical Fuzzy Topsis based on Alpha Levels. Journal Of Industrial Management Perspective, 6(22), 163-185.(In Persian)
  11. Green, K., Morton, B., & New, S. (1996). Purchasing and environmental management: interactions, policies and opportunities. Business strategy and the environment, 5(3), 188-197.
  12. Guyader, H., Ottosson, M., & Witell, L. (2017). You can't buy what you can't see: Retailer practices to increase the green premium. Journal of Retailing and Consumer Services, 34, 319-325.
  13. Hajmohammad, S., Vachon, S., Klassen, R. D., & Gavronski, I. (2013). Reprint of Lean management and supply management: their role in green practices and performance. Journal of Cleaner Production, 56, 86-93.
  14. Hsu, C. C., Tan, K. C., Zailani, S. H. M., & Jayaraman, V. (2013). Supply chain drivers that foster the development of green initiatives in an emerging economy. International Journal of Operations & Production Management.33(6), 656-688
  15. Islam, M. S., Tseng, M. L., Karia, N., & Lee, C. H. (2018). Assessing green supply chain practices in Bangladesh using fuzzy importance and performance approach. Resources, Conservation and Recycling, 131, 134-145.
  16. Jenkin, T. A., Webster, J., & McShane, L. (2011). An agenda for ‘Green’information technology and systems research. Information and Organization, 21(1), 17-40.
  17. Kusi-Sarpong, S., Sarkis, J., & Wang, X. (2016). Assessing green supply chain practices in the Ghanaian mining industry: A framework and evaluation. International Journal of Production Economics, 181, 325-341.
  18. Laari, S., Töyli, J., Solakivi, T., & Ojala, L. (2016). Firm performance and customer-driven green supply chain management. Journal of cleaner production, 112, 1960-1970.
  19. Lee, V. H., Ooi, K. B., Chong, A. Y. L., & Seow, C. (2014). Creating technological innovation via green supply chain management: An empirical analysis. Expert Systems with Applications, 41(16), 6983-6994.
  20. Li, S., Ngniatedema, T., & Chen, F. (2017). Understanding the impact of green initiatives and green performance on financial performance in the US. Business Strategy and the Environment, 26(6), 776-790.
  21. Mardani, A., Kannan, D., Hooker, R. E., Ozkul, S., Alrasheedi, M., & Tirkolaee, E. B. (2020). Evaluation of green and sustainable supply chain management using structural equation modelling: A systematic review of the state of the art literature and recommendations for future research. Journal of Cleaner Production, 249, 119383.
  22. Min, H., & Galle, W. P. (2001). Green purchasing practices of US firms. International Journal of Operations & Production Management, 21, 1222-1238.
  23. Mortazavi, S., & Seif Barghy, M. (2018). Two-objective modeling of location-allocation problem in a green supply chain considering transportation system and CO2 emission. Journal of Industrial Management Perspective, 8(1), 163-185. (In Persian)
  24. Radfar, A., & Mohammaditabar, D. (2019). Bi-Objective Optimization of Vendor Managed Inventory Problem in a Mult Echelon Green Supply Chain. Journal of Industrial Management Perspective, 9(3), 109-134. (In Persian)
  25. Rao, P., & Holt, D. (2005). Do green supply chains lead to competitiveness and economic performance?. International journal of operations & production management, 25(9), 898-916.
  26. Rostamzadeh, R., Govindan, K., Esmaeili, A., & Sabaghi, M. (2015). Application of fuzzy VIKOR for evaluation of green supply chain management practices. Ecological Indicators, 49, 188-203.
  27. Sari, K. (2017). A novel multi-criteria decision framework for evaluating green supply chain management practices. Computers & Industrial Engineering, 105, 338-347.
  28. Sari, K., & Suslu, M. (2018). A modeling approach for evaluating green performance of a hotel supply chain. Technological Forecasting and Social Change, 137, 53-60.
  29. Sarkis, J. (2003). A strategic decision framework for green supply chain management. Journal of cleaner production, 11(4), 397-409.
  30. Sharma, V. K., Chandna, P., & Bhardwaj, A. (2017). Green supply chain management related performance indicators in agro industry: A review. Journal of Cleaner Production, 141, 1194-1208.
  31. Shen, L., Olfat, L., Govindan, K., Khodaverdi, R., & Diabat, A. (2013). A fuzzy multi criteria approach for evaluating green supplier's performance in green supply chain with linguistic preferences. Resources, Conservation and Recycling, 74, 170-179.
  32. Tan, Q., & Sousa, C. M. (2015). Leveraging marketing capabilities into competitive advantage and export performance. International Marketing Review, 32(1), 78-102.
  33. Tseng, M. L., & Chiu, A. S. (2013). Evaluating firm's green supply chain management in linguistic preferences. Journal of cleaner production, 40, 22-31.
  34. Tseng, M.L., Lim, K. M., Wong, W.P. (2015). Sustainable supply chain management: a closed-loop network approach. Industrial Management & Data System, 115(3), 436 – 461.
  35. Uygun, Ö., & Dede, A. (2016). Performance evaluation of green supply chain management using integrated fuzzy multi-criteria decision making techniques. Computers & Industrial Engineering, 102, 502-511.
  36. Vachon, S., & Klassen, R. D. (2008). Environmental management and manufacturing performance: The role of collaboration in the supply chain. International journal of production economics, 111(2), 299-315.
  37. Vahabzadeh, A. H., Asiaei, A., & Zailani, S. (2015). Green decision-making model in reverse logistics using FUZZY-VIKOR method. Resources, Conservation and Recycling, 103, 125-138.
  38. Walker, H., & Jones, N. (2012). Sustainable supply chain management across the UK private sector. Supply Chain Management, 17(1), 15-28.
  39. Wang, H. F., & Gupta, S. M. (2011). Green supply chain management: Product life cycle approach. McGraw Hill Professional.
  40. Watson, R. T., Boudreau, M. C., Chen, A., & Huber, M. H. (2008). Green IS: Building sustainable business practices. In R. T. Watson (Ed.), Information Systems. Athens, GA, USA: Global Text Project.
  41. Wouters, M., Anderson, J. C., Narus, J. A., & Wynstra, F. (2009). Improving sourcing decisions in NPD projects: Monetary quantification of points of difference. Journal of Operations Management, 27(1), 64-77.
  42. Wu, K. J., Liao, C. J., Tseng, M. L., & Chiu, A. S. (2015). Exploring decisive factors in green supply chain practices under uncertainty. International Journal of Production Economics, 159, 147-157.
  43. Zhou, L., Naim, M. M., & Disney, S. M. (2017). The impact of product returns and remanufacturing uncertainties on the dynamic performance of a multi-echelon closed-loop supply chain. International Journal of Production Economics, 183, 487-502.