IJE TRANSACTIONS C: Aspects Vol. 32, No. 3 (March 2019) 413-423   

PDF URL: http://www.ije.ir/Vol32/No3/C/9-3032.pdf  
downloaded Downloaded: 35   viewed Viewed: 214

Z. Akbarzadeh, A. H. Safaei Ghadikolaei, M. Madhoushi and H. Aghajani
( Received: January 02, 2018 – Accepted in Revised Form: July 26, 2018 )

Abstract    In recent years, taking advantage of LARG supply chain (SC) paradigm, a combination of four paradigms (clean, agile, resilience and green) has been increasingly employed. For capturing the advantages of LARG in SC, companies needed to recognize proper practices and implement them with appropriate planning and infrastructure. However, one of its deficiencies is lack of proper method in the prioritization of the LARG paradigms and practices as well as explanation of their relationship. Hence, the main contribution of this paper is to present a comprehensive approach to deal with inherent vagueness and uncertainty of the human decision process using fuzzy set theory, it aims to provide a quantitative basis via a hybrid fuzzy multi-criteria decision making (FMCDM) model that will make easy data collection and shall decrease the calculation. This model combines fuzzy decision making trial and evaluation laboratory (DEMATEL) with fuzzy analytical network process (ANP), i.e. FDANP, to determine the global weights of paradigms and practices and develop their impact relation map. Finally, the implementation of practice was prioritized by using interpretative structural model (ISM). It should be noted that, to measure the efficiency of this method, Iranian dairy industries as a case study was considered. With the help of obtained results, it can be determined the most and the least important practices and paradigms and prioritization of their implementation.


Keywords    LARG Supply Chain; LARG Practices; FDANP Technique; ISM; Dairy Industries



طی سال¬های اخیر، بکارگیری پارادایم زنجیره تأمین لارج (ترکیبی از چهار پارادایم ناب، چابک، تاب¬آور و سبز) به¬طور فزاینده¬ی در حال افزایش است. جهت بهره¬برداری از مزایای پارادایم لارج در زنجیره تأمین، ابتدا باید اقدامات مناسب شناسایی شوند و با برنامه¬ریزی صحیح بستر لازم برای جاری ساختن آنها فراهم گردد. با این حال، یکی از نقاط ضعف این حوزه فقدان روشی مناسب برای اولویت¬بندی اقدامات و پاردایم¬های لارج و تبیین روابط بین آنها است. در همین راستا، پژوهش حاضر درصدد است یک رویکرد جامع بر مبنای مدل تصمیم¬گیری چند معیاره فازی ارائه دهد بطوریکه ضمن مقابله با ابهام و عدم اطمینان موجود در فرآیند تصمیم¬گیری، جمع¬آوری داده را تسهیل کرده و حجم محاسبات را کاهش دهد. با استفاده از این مدل کمی، که ترکیبی از تکیک‌های دیمتل فازی و فرآیند تحلیل شبکه فازی یا به اختصار FDANP است درجه اهمیت اقدامات و پارادایم¬های زنجیره تأمین لارج تعیین و روابط علی بین آنها را ترسیم می¬شود.در نهایت با استفاده از روش مدل ساختاری تفسیری اولویت اجرای هر یک از اقدامات تعیین خواهد شد. همچنین به‌منظور سنجش بهتر کارایی رویکرد پیشنهادی، صنایع لبنی ایران به¬عنوان مطالعه موردی بررسی گردید. با توجه به نتایج مدل، بااهمیت ترین و کم‌اهمیت ¬ترین پارادایم و اقدامات و نیز اولویت اجرای آنها تعیین شد.


1. Fard, A. M. F., Gholian-Jouybari, F., Paydar, M. M., & Hajiaghaei-Keshteli, M., “A Bi-Objective Stochastic Closed-loop Supply Chain Network Design Problem Considering Downside Risk”, Industrial Engineering and Management System, Vol. 16, (2017), 342-362.
2. Nourmohamadi Shalke, P., Paydar, M. M., & Hajiaghaei-Keshteli, M., “Sustainable supplier selection and order allocation through quantity discounts”, International Journal of Management Science and Engineering Management, (2017), 2-13.
3. Sahraeian, R., Bashiri, M., & Moghadam, A. T., “Capacitated multimodal structure of a green supply chain network considering multiple objectives”, International Journal of Engineering-Transactions C: Aspects, Vol. 26, No. 9, (2013), 963-974.
4. Moubed, M., & Mehrjerdi Zare, Y., “A hybrid dynamic programming for inventory routing problem in collaborative reverse supply chains”, International Journal of Engineering, Transactions A: Basics, Vol. 29, No. 10, (2016), 1412-1420.
5. Fard, A. M. F., & Hajaghaei-Keshteli, M., “A tri-level location-allocation model for forward/reverse supply chain”, Applied Soft Computing, Vol. 62, (2018), 328-346.
6. Azevedo, S. G., Carvalho, H., & Machado, V. C. “The influence of LARG supply chain management practices on manufacturing supply chain performance”, In Proceedings of International Conference on Economics, Business and Marketing Management, (2011), 1-6.
7. Azevedo, S. G., Carvalho, H., & Machado, V. C., “A proposal of LARG supply chain management practices and a performance measurement system”,International Journal of e-Education, e-Business, e-Management and e-Learning, Vol. 1, (2011), 7-14.
8. Azevedo, S., Carvalho, H., & Cruz-Machado, V., “Proposal of a conceptual model to analyse the influence of LARG practices on manufacturing supply chain performance”, Journal of Modern Accounting & Auditing, Vol. 8, (2012), 174-184.
9. Cabral, I., Espadinha-Cruz, P., Grilo, A., Puga-Leal, R., & Cruz-:Machado, V., “Decision-Making Models for Interoperable Lean, Agile, Resilient and Green Supply Chains”, In Proceedings of the International Symposium on the Analytic Hierarchy Process, (2011), 1-6.
10. Cabral, I., Grilo, A., Leal, R. P., & Machado, V. C., “Modeling Lean, Agile, Resilient, and Green Supply Chain Management”, Information Technology Interfaces (ITI), Proceedings of the ITI 2011 33rd International Conference on IEEE, (2011), 365-370.
11. Carvalho, H., Duarte, S., & Cruz Machado, V., “Lean, agile, resilient and green: divergencies and synergies”, International Journal of Lean Six Sigma, Vol. 2, (2011), 151-179.
12. Maleki, M., Shevtshenko, E. & Machado, V. C., “Development of Supply Chain Integration model through application of Analytic Network Process and Bayesian Network”, International Journal of Integrated Supply Management, Vol. 8, (2013),67-89.
13. Maleki, M., & Machado, V. C., “Generic integration of lean, agile, resilient, and green practices in automotive supply chain”, Revista de Management Comparat International, Vol. 14, (2013), 237-248.
14. Carvalho, H., Azevedo, S. & Cruz-Machado, V., “Trade-offs among lean, agile, resilient and green paradigms in supply chain management: a case study approach”, In Proceedings of the Seventh International Conference on Management Science and Engineering Management, (2014), 953-968.
15. Cruz, E. P., Cabral, I., & Grilo, A., “LARG Interoperable Supply Chains: from Cooperation Analysis to Design”, In Intelligent Decision Technologies: Proceedings of the 5th KES International Conference on Intelligent Decision Technologies, Vol. 255, (2013), 255.
16. Cruz, E. P., Cabral, I., Grilo, A., & Cruz-Machado, V., “Information model for LARGeSCM interoperable practices”, In Information Technology Interfaces (ITI), Proceedings of the ITI 34th International Conference on IEEE, (2012a), 23-28.
17. Cruz, E. P., Grilo, A., & Cruz-Machado, V., “Fuzzy evaluation model to assess interoperability in LARG Supply Chains”, In Fuzzy Systems and Knowledge Discovery (FSKD), 9th International Conference on IEEE, (2012b), 75-79.
18. Santos, J. P. P. D. “A simulation model for Lean, Agile, Resilient and Green Supply Chain Management: practices and interoperability assessment”, Doctoral dissertation, Faculdade de Ciências e Tecnologia, (2013).
19. Donk, P. V. D., Akkerman, R., & Van der Vaart, T., “Opportunities and realities of supply chain integration: the case of food manufacturers”, British Food Journal, Vol. 110, (2008), 218-235.
20. Gölcük, İ., & Baykasoğlu, A. “An analysis of DEMATEL approaches for criteria interaction handling within ANP” Expert Systems with Applications, Vol. 46, (2016). 346-366.
21. Ghadikolaei, A. H. S., Akbarzadeh, Z., Ahmadi, A., & Geshniani, Y. V., “Applying hybrid FMADM model for analysing SWOT strategies at the Iranian industrial engines manufacturing firm (a case study)”, International Journal of Productivity and Quality Management, Vol. 20, (2017), 462-487.
22. Beikkhakhian, Y., Javanmardi, M., Karbasian, M. & Khayambashi, B., “The application of ISM model in evaluating agile supplier's selection criteria and ranking suppliers using fuzzy TOPSIS-AHP methods”, Expert Systems with Applications, Vol. 42, no. 15-16 (2015), 6224-6236.
23. Kannan, G., Pokharel, S., & Sasi Kumar, P., “A hybrid approach using ISM and fuzzy TOPSIS for the selection of reverse logistics provider. Resources”, Conservation and Recycling, Vol. 54, (2009), 28–36.  
24. Attri, R., Dev, N., & Sharma, V., “Interpretive structural modeling (ISM) approach: an overview”, Research Journal of Management Sciences, 2319, (2013), 1171.
25. Pfohl, H. C., Gallus, P., & Thomas, D.,“Interpretive structural modeling of supply chain risks”, International Journal of Physical Distribution & Logistics Management, Vol. 41, No. 9, (2011). 839-859.
26. Cheraghalipour, A., Paydar, M. M., & Hajiaghaei-Keshteli, M., “An integrated approach for collection center selection in reverse logistics”, International Journal of Engineering, Transactions A: Basics, Vol. 30, (2017), 1005-1016.
27. Carvalho, Helena; Cruz Machado, V, “Lean, agile, resilient and green supply chain: a review”, Proceedings of the Third International Conference on Management Science and Engineering Management, Thailand, (2009), 3–14.
28. Cabral, I., Grilo, A., & Cruz-Machado, V., “A decision-making model for lean, agile, resilient and green supply chain management”, International Journal of Production Research, Vol. 50, (2012), 4830-4845.
29. Maleki, M., da Cruz, P. E., Valente, R. P., & Machado, V. C., “Supply Chain Integration Methodology: LARGe Supply Chain”, Encontro Nacional de Engenharia e Gestão Industrial, (2011), 57-66.
30. Jassbi, A., Jassbi, J., Akhavan, P., Chu, M. T., & Piri, M., “An empirical investigation for alignment of communities of practice with organization using fuzzy Delphi panel”, VINE, Vol. 45, (2015), 322-343.
31. Liou, J. J., Yen, L., & Tzeng, G. H., “Building an effective safety management system for airlines”, Journal of Air Transport Management, Vol. 14, (2008), 20-26. 
32. Dalalah, D., Hayajneh, M., & Batieha, F., “A fuzzy multi-criteria decision making model for supplier selection”, Expert systems with applications, Vol. 38, (2011), 8384-8391.
33. Büyüközkan, G., Kayakutlu, G., & Karakadılar, İ. S., “Assessment of lean manufacturing effect on business performance using Bayesian Belief Networks”, Expert Systems with Applications, Vol. 42, No. 19, (2015), 6539-6551.
34. Netland, T. H., Schloetzer, J. D., & Ferdows, K, “Implementing corporate lean programs: the effect of management control practices”, Journal of Operations Management, Vol. 36, (2015), 90-102.
35. Sharma, V., Dixit, A. R., & Qadri, M. A., “Impact of lean practices on performance measures in context to Indian machine tool industry”, Journal of Manufacturing Technology Management, Vol. 26, No. 8, (2015), 1218-1242.
36. Birkie, S. E., “Operational resilience and lean: In search of synergies and tradeoffs”, International Journal of Manufacturing Technology and Management (IJMTM), Vol. 27, No. 2, (2016), 185-207.
37. Nawanir, G., Nawanir, G., Lim, K. T., Lim, K. T., Othman, S. N., & Othman, S. N., “Lean manufacturing practices in Indonesian manufacturing firms: Are there business performance effects?”, International Journal of Lean Six Sigma, Vol. 7, No. 2, (2016), 149-170.
38. Mehralian, G., Zarenezhad, F., & Rajabzadeh Ghatari, A., “Developing a model for an agile supply chain in pharmaceutical industry”, International Journal of Pharmaceutical and Healthcare Marketing, Vol. 9, No. 1, (2015), 74-91.
39. Tse, Y. K., Zhang, M., Akhtar, P., & MacBryde, J., “Embracing supply chain agility: an investigation in the electronics industry”, Supply Chain Management: An International Journal, Vol. 21, No. 1, (2016), 140-156.
40. Durrani, U. K., Pita, Z., & Richardson, J., “Coexistence of agile and SCM practices: an exploratory study of Australian agile software development organizations”, Journal of Systems and Information Technology, Vol. 16, No. 1, (2014),  20-39.
41. Francis, R., & Bekera, B, “A metric and frameworks for resilience analysis of engineered and infrastructure systems”, Reliability Engineering & System Safety, Vol. 121, (2014), 90-103.
42. Hoejmose, S. U., Grosvold, J., & Millington, A., “The effect of institutional pressure on cooperative and coercive ‘green’supply chain practices”, Journal of Purchasing and Supply Management, Vol. 20, No. 4, (2014), 215-224.
43. Govindan, K., Khodaverdi, R., & Vafadarnikjoo, A., “Intuitionist fuzzy based DEMATEL method for developing green practices and performances in a green supply chain”, Expert Systems with Applications, Vol. 42, No. 20, (2015), 7207-7220.
44. rishnamurthy, R. and Yauch, C.A., “Leagile manufacturing: a proposed corporate infrastructure”, International Journal of Operations and Production Management, Vol. 27, (2007), 588-604.
45. Wan, H.D., “Measuring Leanness of Manufacturing Systems and Identifying Leanness Target by Considering Agility”, PhD Thesis, The Virginia Polytechnic Institute and State University, (2006). 

Download PDF 

International Journal of Engineering
E-mail: office@ije.ir
Web Site: http://www.ije.ir