Document Type : Original Article


1 Assistant Professor, University of Mazandaran.

2 MSc. student, University of Mazandaran.

3 B.A., University of Mazandaran.


In modern business environments, a competitive Supply Chain Management is crucial to business continuity. In this context, Lean, Agile, Resilient and Green (LARG), are advocated as the fundamental paradigm for a competitive Supply Chain as a whole. Various paradigms have emerged in the supply chain from the beginning, from among which there are four paradigms lean, agile, resilient and green that are important in supply chain performance and competitiveness, which are referred to as the LARG supply chain. Each of these paradigms pursues a specific mission and purpose in the supply chain. The choice of best supplier in each supply chain is based on different decision-making criteria, but the weight of each criteria varies according to the supplier's priorities. The purpose of this research is to provide a hybrid model of multi-criteria decision for selecting suppliers in the LARG paradigms of tile and ceramic industry. In this research, in first, supplier selection indicators are identified and then weighted by the Best Worst Method. Subsequently, suppliers are ranked by piecewise linear value function and multi-criteria decision-making technique TODIM. This system can play an important role in improving supply chain performance in effective decision making by managers in the supplier selection process and provide results based to reality.


1. Agarwal, A., Shankar, R., & Tiwari, M. K. (2007). Modeling agility of supply chain. Industrial marketing management, 36(4), 443-457. 2. Alali, F., & Tolga, A. C. (2019). Portfolio allocation with the TODIM method. Expert Systems with Applications, 124, 341-348.
3. Anand, G., & Kodali, R. (2009). Development of a framework for implementation of lean manufacturing systems. International Journal of Management Practice, 4(1), 95-116.
4. Awasthi, A., Chauhan, S.S., Goyal, S.K., (2010). A fuzzy multicriteria approach for evaluating environmental performance of suppliers. Int. J. Prod. Econ., 126, 370e378 5. Azevedo, S. G., Carvalho, H., & Cruz-Machado, V. (2011). 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, 1(1), 7.
6. Balaji, M., Velmurugan, V. & Subashree, C. (2015). TADS: An assessment methodology for agile supply chains. Journal of applied research and technology, 13(5), 504-509.
7. Birgün Barla, S. (2003). A case study of supplier selection for lean supply by using a mathematical model. Logistics Information Management, 16(6), 451-459. 8. Birkie, S. E. (2016). Operational resilience and lean: in search of synergies and trade-offs. Journal of Manufacturing Technology Management, 27(2), 185-207. 9. Blackhurst, J., Dunn, K. S., & Craighead, C. W. (2011). An empirically derived framework of global supply resiliency. Journal of Business Logistics, 32(4), 374-391.
10. Burgess, K., Singh, P. J., & Koroglu, R. (2006). Supply chain management: a structured literature review and implications for future research. International Journal of Operations & Production Management, 26(7), 703-729.
11. Carvalho, H., & Machado, V. C. (2009, November). Lean, agile, resilient and green supply chain: a review. In Proceedings of the Third International Conference on Management Science and Engineering Management (pp. 66-76). 12. Chen, C. T., Lin, C. T., & Huang, S. F. (2006). A fuzzy approach for supplier evaluation and selection in supply chain management. International journal of production economics, 102(2), 289-301.
13. Christopher, M., & Peck, H. (2004). The five principles of supply chain resilience. Logistics Europe, 12(1), 16-21.
14. Christopher, M., & Rutherford, C. (2004). Creating supply chain resilience through agile six sigma. Critical eye, 7(1), 24-28. 15. Duarte, S., & Cruz-Machado, V. (2013). Modelling lean and green: a review from business models. International Journal of Lean Six Sigma, 4(3), 228-250. 16. Espadinha-Cruz, P., Cabral, I., & Grilo, A. (2013, June). 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, p. 255). Courier Corporation.
17. Fan, Z. P., & Liu, Y. (2010). An approach to solve group-decision-making problems with ordinal interval numbers. IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics), 40(5), 1413-1423.
18. Fan, Z. P., Zhang, X., Chen, F. D., & Liu, Y. (2013). Extended TODIM method for hybrid multiple attribute decision making problems. Knowledge-Based Systems, 42, 40-48.
19. Ghazizadeh, M. Nouruzzadeh, F. Raeisi ghorbanabadi. H. (2015). Analysis of LARGe Supply Chain Management using DEMATEL Technique in Saipa Company. Supply Chain Management Quarterly, 48, 12-25 (in Persian) 20. Gomes, L. F. A. M., Rangel, L. A. D., & Maranhão, F. J. C. (2009). Multicriteria analysis of natural gas destination in Brazil: An application of the TODIM method. Mathematical and Computer Modelling, 50(1-2), 92-100.
21. Gunasekaran, A., Patel, C., & Tirtiroglu, E. (2001). Performance measures and metrics in a supply chain environment. International journal of operations & production Management, 21(1/2), 71-87 22. Gupta, H., & Barua, M. K. (2017). Supplier selection among SMEs on the basis of their green innovation ability using BWM and fuzzy TOPSIS. Journal of Cleaner Production, 152, 242-258.
23. Hong, P., Kwon, H. B., & Jungbae Roh, J. (2009). Implementation of strategic green orientation in supply chain: an empirical study of manufacturing firms. European Journal of Innovation Management, 12(4), 512-532.
24. Jafarnezhad, A., Kazemi, A., and Arab, A. (2016). Identification and Prioritization of Supplier’s Resiliency Evaluation Criteria Based on BWM. Industrial management Perspective, 23, 159-186 (In Persian).
25. Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. Econometrica: Journal of the econometric society, 47(2) 363-391.
26. Kainuma, Y., & Tawara, N. (2006). A multiple attribute utility theory approach to lean and green supply chain management. International Journal of Production Economics, 101(1), 99-108.
27. Lee, A. H., Kang, H. Y., Hsu, C. F., & Hung, H. C. (2009). A green supplier selection model for high-tech industry. Expert systems with applications, 36(4), 7917-7927. 28. Li, G. D., Yamaguchi, D., & Nagai, M. (2007). A grey-based decision-making approach to the supplier selection problem. Mathematical and computer modelling, 46(3-4), 573-581.
29. Luo, X., Wu, C., Rosenberg, D., & Barnes, D. (2009). Supplier selection in agile supply chains: An information-processing model and an illustration. Journal of Purchasing and Supply Management, 15(4), 249-262. 30. Maleki, M., & Cruz Machado, V. (2013). Generic Integration of Lean, Agile, Resilient, and Green Practices in Automotive Supply Chain. Review of International Comparative Management/Revista de Management Comparat International, 14(2). 31. Maleki, M., Shevtshenko, E., & Cruz-Machado, V. (2013). Development of supply chain integration model through application of analytic network process and bayesian network. International Journal of Integrated Supply Management, 8(1/2/3), 67-89.
32. Naylor, J. B., Naim, M. M., & Berry, D. (1999). Leagility: integrating the lean and agile manufacturing paradigms in the total supply chain. International Journal of production economics, 62(1), 107-118.
33. Onstein, A. T., Ektesaby, M., Rezaei, J., Tavasszy, L. A., & van Damme, D. A. (2019). Importance of factors driving firms’ decisions on spatial distribution structures. International Journal of Logistics Research and Applications, (In press).
34. Pakdil, F. and Leonard, K.M. (2014). Criteria for a lean organization: Development of a lean assessment tool. International Journal of Production Research, 52(15), 4587-4607. 35. Ponomarov, S. Y., & Holcomb, M. C. (2009). Understanding the concept of supply chain resilience. The international journal of logistics management, 20(1), 124-143. 36. Qin, J., Liu, X., & Pedrycz, W. (2017). An extended TODIM multi-criteria group decision making method for green supplier selection in interval type-2 fuzzy environment. European Journal of Operational Research, 258(2), 626-638.
37. Rahimi, H., Sharifi, M., and Shahriari, M. (2017). Design of Resilience Supply Chain (Case Study: Welfare Organization of Iran). Industrial management Perspective, 27, 127-150 (In Persian). 38. Rajesh, R. (2018). On sustainability, resilience, and the sustainable–resilient supply networks. Sustainable Production and Consumption, 15, 74-88.
39. Rajesh, R., & Ravi, V. (2015). Supplier selection in resilient supply chains: a grey relational analysis approach. Journal of Cleaner Production, 86, 343-359. 40. Rangel, L. A. D., Gomes, L. F. A. M., & Cardoso, F. P. (2011). An application of the TODIM method to the evaluation of broadband internet plans. Pesquisa Operacional, 31(2), 235-249.
41. Ravansetan, K., Aghajani, H., Safaei, A. and Yahyazadefar, M. (2017). Determining and Weighting Resilience Strategies in Iran Khodro Supply Chain. Industrial management Perspective, 25, 145-172 (In Persian). 42. Rezaei, J. (2015). Best-worst multi-criteria decision-making method. Omega, 53, 49-57.
43. Rezaei, J. (2016). Best-worst multi-criteria decision-making method: Some properties and a linear model. Omega, 64, 126-130. 44. Rezaei, J. (2018). Piecewise linear value functions for multi-criteria decision-making. Expert Systems with Applications, 98, 43-56. 45. Rezaei, J., & Fallah Lajimi, H. (2019). Segmenting supplies and suppliers: bringing together the purchasing portfolio matrix and the supplier potential matrix. International Journal of Logistics Research and Applications, 22(4), 419-436. 46. Rezaei, J., Wang, J., & Tavasszy, L. (2015). Linking supplier development to supplier segmentation using Best Worst Method. Expert Systems with Applications, 42(23), 9152-9164.
47. Rosic, H., Bauer, G., & Jammernegg, W. (2009). A framework for economic and environmental sustainability and resilience of supply chains. Rapid modelling for increasing competitiveness, 91-104. 48. Ruiz-Benitez, R., López, C., & Real, J. C. (2017). Environmental benefits of lean, green and resilient supply chain management: The case of the aerospace sector. Journal of Cleaner Production, 167, 850-862. 49. Salimi, N., & Rezaei, J. (2018). Evaluating firms’ R&D performance using best worst method. Evaluation and program planning, 66, 147-155. 50. Shojaei, P., Haeri, S. A. S., & Mohammadi, S. (2018). Airports evaluation and ranking model using Taguchi loss function, best-worst method and VIKOR technique. Journal of Air Transport Management, 68, 4-13.
51. Torabi, S. A., Giahi, R., & Sahebjamnia, N. (2016). An enhanced risk assessment framework for business continuity management systems. Safety science, 89, 201-218.
52. Tseng, M. L. (2011). Green supply chain management with linguistic preferences and incomplete information. Applied Soft Computing, 11(8), 4894-4903. 53. Wang, J., Wang, J. Q., & Zhang, H. Y. (2016). A likelihood-based TODIM approach based on multi-hesitant fuzzy linguistic information for evaluation in logistics outsourcing. Computers & Industrial Engineering, 99, 287-299.
54. Wieland, A., & Wallenburg, C. M. (2013). The influence of relational competencies on supply chain resilience: a relational view." International Journal of Physical Distribution & Logistics Management, 43(4), 300-320.
55. Wyton, P. & Payne, R. (2014). Exploring the development of competence in Lean management through action learning groups: A study of the introduction of Lean to a facilities management function. Action Learning: Research and Practice, 11(1), 42-61.
56. Zhang, Z., & Sharifi, H. (2000). A methodology for achieving agility in manufacturing organisations. International Journal of Operations & Production Management, 20(4), 496-513.