شناسایی و رتبه بندی مولفه‌های انتخاب تأمین‌کننده تاب‌آور در صنعت فولاد چهارمحال و بختیاری با روش تحلیل تم و رویکرد ترکیبی ( AHP-QUALIFLEX )

نوع مقاله: مقاله پژوهشی

نویسندگان

1 دکترا مدیریت تولید و عملیات، دانشکده پردیس البرز، دانشگاه تهران، تهران، ایران

2 2- دانشجوی دکتری مدیریت دولتی ( مدیریت منابع انسانی)، دانشگاه آزاد اسلامی، واحد سیرجان، سیرجان، ایران

3 دانشجوی دکتری مدیریت صنعتی ( تولید وعملیات)، دانشگاه آزاد اسلامی، واحد قزوین، قزوین، ایران

4 دانشجو دکترا مدیریت دولتی (رفتار سازمانی)، عضو هیات علمی دانشگاه پیام نور

چکیده

محیط آشفته و متغیر امروز موجب پیدایش عدم اطمینان در زنجیره های تأمین شده است. و تامین‌کنندگان با ریسک های زیادی مواجه شده‌اند به همین دلیل انتخاب تامین‌کنندگان تاب‌آور از اهمیت بالایی برخوردار است. بنابراین هدف پژوهش حاضر شناسایی و رتبه بندی مولفه‌های انتخاب تأمین‌کننده تاب‌آور در صنعت فولاد چهارمحال و بختیاری می‌باشد. پژوهش حاضر کاربردی بوده و بصورت آمیخته انجام گرفت. با استفاده از روش نمونه‌گیری هدفمند 10 خبره آشنا به پژوهش تعیین گردید. در بخش کیفی برای کدگذاری و شناسایی عوامل از تحلیل تم استفاده شد. همچنین برای اولویت بندی عوامل در بخش کمی از روش AHP با استفاده از نرم افزار سوپردسیژن استفاده گردید. نتایج حاصل از تحلیل تم نشان داد که عوامل موثر شامل 6 تم کلی چابکی، ایمنی و مسایل زیست محیطی و اجتماعی، انعطاف پذیری، تحویل، کیفیت و تکنولوژی و فناوری اطلاعات می‌باشند. و مولفه چابکی با وزن 221/0 در اولویت اول و مولفه ایمنی و مسایل زیست محیطی و اجتماعی با وزن 104/0 در اولویت آخر قرار دارد. سایر عوامل نیز به ترتیب اثرگذاری شامل انعطاف پذیری، تحویل، کیفیت و تکنولوژی و فناوری اطلاعات می باشند. سپس سه شرکت تأمین‌کننده مواد اولیه برای تولید فولاد با تکنیک QUALIFLEX رتبه بندی گردیدند. با استفاده از نتایج پژوهش مدیران می‌توانند تامین‌کنندگان تاب‌آور مناسب را انتخاب نمایند.

کلیدواژه‌ها


عنوان مقاله [English]

Identification and ranking of resilience supplier selection components in Chaharmahal and Bakhtiari steel industry by theme analysis method and combined approach (AHP-QUALIFLEX)

نویسندگان [English]

  • farhad farhadi 1
  • Alireza mohammadi 2
  • Mostafa Mahmoudabadi 3
  • Mohmmad Mahmoodi Mandani 4
1 Ph.D. of production and operations management, Alborz Campus College, Tehran University, Tehran, Iran
2 - PhD student in Public Management (Human Resource Management), Islamic Azad University, Sirjan Branch, Sirjan, Iran
3 PhD Student Industrial Management(Production and Operations), Islamic Azad University, Qazvin Branch, Qazvin, Iran
4 PhD Student Public Management (Organizational Behavior), Faculty Member of Payame Noor University
چکیده [English]

Today's turbulent and changing environment has created uncertainty in supply chains. And suppliers face many risks, which is why choosing resilient suppliers is so important. Therefore, the aim of this study is to identify and rank the components of resilient supplier selection in Chaharmahal and Bakhtiari steel industry. The present study was applied and was conducted in a mixed manner. In the qualitative section, theme analysis was used to code and identify the factors. AHP method was used to prioritize the factors in a small part using Supersigen software. The results of theme analysis showed that the effective factors include 6 general themes of agility, safety and environmental and social issues, flexibility, delivery, quality and technology and information technology. The agility component with a weight of 0.221 is in the first priority and the component of safety and environmental and social issues with a weight of 0.104 is in the last priority. Other factors influencing flexibility, delivery, quality, and information technology, respectively. Then, three companies supplying raw materials for steel production with QUALIFLEX technique were ranked. Using the research results, managers can select the appropriate resilient suppliers.

کلیدواژه‌ها [English]

  • Resilient Supplier
  • Theme Analysis
  • QUALIFLEX
  • AHP
  1. Adabi Firoozjaei, M, Safaei Ghadiklaei, A. (2017). Selecting the best resilient supply chain with the combined approach of Demetel and Vickor Gray and the technique of the worst case study: selected dairy companies - Mazandaran province, the first national conference on modern management studies in Iran, Karaj, Allameh Khoei Higher Education Institute and Meraj Higher Education Institute.
  2. Arampantzi, C, Minis, I, Dikas, G. (2018). A strategic model for exact supply chain network design and its application to a global manufacturer. International Journal of Production Research, 57 (5), 1–27.
  3. Awasthi, A, Govindan, K, & Gold, S. (2018). Multi-tier sustainable global supplier selection using a fuzzy AHP-VIKOR based approach. International Journal of Production Economics, 195, 106-117.‏
  4. Adeinat, H, Ventura, J. A, (2015). Determining the retailer’s replenishment pol- icy considering multiple capacitated suppliers and price-sensitive demand. Eu- ropean Journal of Operational Research, 247 (1), 83–92.
  5. Azadnia, A. H, Saman, M, Wong, K. Y. (2015). Sustainable supplier selection and order lot-sizing: An integrated multi-objective decision-making process. In- ternational Journal of Production Research, 53 (2), 383–408.
  6. Amid, A, Ghodsypour, S. H, O´Brien, C. (2006). Fuzzy multiobjective linear model for supplier selection in a supply chain. Internathona Journal of Production Economics, 104, 394-407.
  7. Boran, F. E, Genç, S, Kurt, M, Akay, D. (2009). A multi-criteria intuitionistic fuzzy group decision making for supplier selection with TOPSIS method. Expert Systems with Applications, 36(8), 11363-11368.
  8. Bodaghi, G, Jolai, F, & Rabbani, M. (2018). An integrated weighted fuzzy multi-ob- jective model for supplier selection and order scheduling in a supply chain. In- ternational Journal of Production Research, 56 (10), 3590–3614.
  9. Chai, J, & Ngai, E. W. (2019). Decision-making techniques in supplier selection: Recent accomplishments and what lies ahead. Expert Systems with Applications, 112903.‏
  10. Chen, W, Lei, L, Wang, Z, Teng, M, & Liu, J. (2018). Coordinating supplier selec- tion and project scheduling in resource-constrained construction supply chains. International Journal of Production Research, 56, 1–15.
  11. Kar, A. K. (2014). Revisiting the supplier selection problem: An integrated approach for group decision support. Expert Systems with Applications, 41 (6), 2762–2771.
  12. Chai, J, & Ngai, E. W. (2019). Decision-making techniques in supplier selection: Recent accomplishments and what lies ahead. Expert Systems with Applications, 112903.‏
 

  1. Hasan, M. M, Jiang, D, Ullah, A. S, Noor-E-Alam, M. (2020). Resilient supplier selection in logistics 4.0 with heterogeneous information. Expert Systems with Applications, 139, 112799.‏
  2. Lee, J, Cho, H, Kim, Y. S. (2014). Assessing business impacts of agility criterion and order allocation strategy in multi-criteria supplier selection. Expert Systems with Applications, In Press
  3. Liang, Y, Qin, J, Martínez, L, Liu, J. (2020). A heterogeneous QUALIFLEX method with criteria interaction for multi-criteria group decision making. Information Sciences, 512, 1481-1502.‏
  4. Karsak, E. E, & Dursun, M. (2015). An integrated fuzzy MCDM approach for supplier evaluation and selection. Computers & Industrial Engineering, 82, 82-93.
  5. Kabgani, M, Shah Bandarzadeh, H, (2019), Quantitative Analysis of Supplier Selection Criteria in Resilient Supply Chain Using Multi-Criteria Decision Making Techniques, Business Research, 23 (90), 115-140.
  6. Kumar, A, Pal, A, Vohra, A, Gupta, S, Manchanda, S, & Dash, M. K. (2018). Construction of capital procurement decision making model to optimize supplier selection using Fuzzy Delphi and AHP-DEMATEL. Benchmarking: An International Journal, 25(5), 1528-1547.
  7. Jafarnejad Chaghoshi, A, Kazemi, A, Arab, A, (2016), Identifying and prioritizing suppliers' resilience assessment indicators based on the best-worst method, Industrial Management Perspective, 23, 159-186.
  8. Govindan, K, Shankar, M, & Kannan, D. (2016). Supplier selection based on corpo- rate social responsibility practices. International Journal of Production Economics, 200, 353–379 .
  9. ‏Govindan. K., Kadzi ´nski. M, Sivakumar, R. (2017). Application of a novel PROMETHEE-based method for construction of a group compromise ranking to prior- itization of green suppliers in food supply chain, Omega 71 (2017) 129–145.
  10. Liou, J. J. H, Chuang, Y. C, & Tzeng, G. H. (2014). A fuzzy integral-based model for supplier evaluation and improvement. Information Sciences, 266, 199-217.
  11. Pramanik, D, Mondal, S. C, & Haldar, A. (2020). Resilient supplier selection to mitigate uncertainty: soft-computing approach. Journal of Modelling in Management.
  12. Purohit, A. K, Choudhary, D, & Shankar, R. (2016). Inventory lot-sizing with sup- plier selection under non-stationary stochastic demand. International Journal of Production Research, 54 (8), 2459–2469.
  13. Sahebjamnia, N. (2020). Resilient supplier selection and order allocation under uncertainty. Scientia Iranica, 27(1), 411-426.‏
  14. Sarkis, J, & Dhavale, D. G. (2015). Supplier selection for sustainable operations: A triple-bottom-line approach using a Bayesian framework. International Journal of Production Economics, 166, 177–191.
  15.  Morente-Molinera, J. A, Wu, X, Morfeq, A, Al-Hmouz, R, Morente-Molinera, J. A, Wu, X, Morfeq, A, Al-Hmouz, R, & Herrera-Viedma, E. (2020). A novel multi-criteria group decision-making method for heterogeneous and dynamic contexts using multi-granular fuzzy linguistic modelling and consensus measures. Information Fusion, 53, 240-250.‏
  16. Negahban, A, & Dehghanimohammadabadi, M. (2018). Optimizing the supply chain configuration and production-sales policies for new products over multiple planning horizons. International Journal of Production Economics, 196, 150–162.
  17. Valipour Parkoohi, S, Safaei Qadiklaei, A, Madhoshi, M. (2017). Explain the causal relationships of effective factors in choosing a resilient supplier. Journal of Executive Management, 9 (18), 89-110.
  18. Zhang, X, tance-based comparison method for multiple criteria decision analysis. Expert Systems with Applications, 42 (2), 873–884.
  19. You, X. Y, You, J. X, Liu, H. C, Zhen, L. (2015). Group multi-criteria supplier selection using an extended VIKOR method with interval 2-tuple linguistic information. Expert Systems with Applications, 42(4), 1906-1916.