Document Type : Original Article


1 Professor, Tehran University.

2 Associate Professor, Tehran University.

3 Ph.D Student, Alborz Campous of Tehran University.


Nowadays, companies are seeking to find suitable supply chain paradigms to gain better performance and improve their competitiveness. Because competition between supply chains has been replaced by competition between companies. Among different paradigms in supply chain management, integrating lean, agile and resilient paradigms are considered as a new idea to gain better performance and competitiveness. The main purpose of this paper is to determine the importance practices of lean, agile and resilient that top managers should focus on them to improve their supply chain's performance. To this end, interpretive structural modeling (ISM) approach is used to analyze relationships among lean, agile and resilient practices and supply chain performance measures. This approach classifies variables according to their driving or dependence power. As the results shows, the practice "supplier relationship" is with strong driving power and also, performance measure "cash-to-cash cycle" is with weak driving power and strong dependence power. It means that, this measure is strongly influenced by the other variables but does not affect them.


1. Agarwal, A., Shankar, R., & Tiwari, M. (2007). Modeling agility of supply chain. Industrial Marketing Management36(4), 443-457.
2. Anand, G., & Kodali, R. (2008). A conceptual framework for lean supply chain and its implementation. Int J Value Chain Manage, 2, 313–357.
3. Andersson, P., Aronsson, H., & Storhagen, NG. (1989). Measuring Logistics Performance. Eng Costs Prod Econ17, 253–262.
4. Azevedo, S., Carvalho, H., Cruz-Machado, V., & Grilo, F. (2010) The influence of agile and resilient practices on supply chain performance: an innovative conceptual model proposal. In: Innovative process optimization methods in logistics: emerging trends, concepts and technologies. Erich Schmidt Verlag GmbH & Co. KG, Hamburg, Germany, 265–281.
5. Azevedo, S., Carvalho, H., & Cruz-Machado, V. (2013). Using interpretive structural modeling to identify and rank performance measures: an application in the automotive supply chain. Baltic J Manage8(2), 208–230.
6. Beamon, BM. (1999). Measuring supply chain performance. Int J Oper Prod Manage19(3), 275–292.
7. Bolan˜os, R., Fontela, E., Nenclares, A., & Pastor, P. (2005).Using interpretive structural modelling in strategic decision-making groups. Manage Decis 43(6), 877–895.
8. Cabral, I, Grilo, A., & Cruz-Machado, V. (2012). A decision-making model for Lean, Agile, Resilient and Green supply chain management. Int J Prod Res50(17), 4830–4845.
9. Carvalho, H., Azevedo, S., & Cruz-Machado., V. (2010). Supply chain performance management: lean and green paradigms. Int J Bus Perform Supply Chain Model 2(3/4), 151–179.
10. Carvalho, H., Duarte, S., & Cruz-Machado, V. (2011). Lean, agile, resilient and green: divergences and synergies. Int J Lean Six Sigma2(2), 151–179.
11. Carvalho, H., Maleki, M., & Cruz-Machado, V. (2012).The links between supply chain disturbances and resilience strategies. Int J Agile Syst Manage5(3), 203–234.
12. Carvalho, H., Azevedo, S., & Cruz-Machado, V. (2014). Trade-offs among lean, agile, resilient and green paradigms in supply chain management: a case study approach. In: Xu J, Fry JA, Lev B, Hajiyev A (eds) Proceedings of the seventh international conference on management science and engineering management. Springer Berlin, 953–968.
13. Chan, F. (2003).Performance measurement in a supply chain”, International Journal of Advanced Manufacturing Technology21(7), 534-48.
14. Charan, P., Shankar, R., Baisya, R. (2008). Analysis of interactions among the variables of supply chain performance measurement system implementation. Bus Process Manage J14(4), 512–529.
15. Christopher, M., & Towill, D. (2002).The supply chain strategy conundrum: to be lean or agile or to be lean and agile?. International Journal of Logistics, 5(3), 299-309.
16. Christopher, M., & Peck, H. (2004). Building the resilient supply chain. Int J Logist Manage, 15(2), 1–14.
17. Cumbo, D., Kline, D., & Bumgardner, M. M. (2006). Benchmarking performance measurement and lean manufacturing in the rough mill. Forest Products Journal, 56(6), 25-30.
18. Duarte, S., Carvalho, H., & Cruz-Machado, V. (2010). Exploring relationships between supply chain performance measures. The Fourth International Conference on Management Science and Engineering Management, Chungli, Taiwan, 3-7.
19. Farris, T., & Hutchison, P. (2002).Cash-to-cash: the new supply chain management metric, International Journal of Physical Distribution & Logistics Management32(3/4), 288-98.
20. Ghalayini, A., & Noble, J. (1996).The changing basis of performance measurement. Int J Operat Prod Manage, 16(8), 63–80.
21. Glickman, T., & White, S. (2006).Security, visibility and resilience: the keys to mitigating supply chain vulnerabilities. Int J Logist Syst Manage2, 107–119.
22. Goldsby, T. J., Griffis, S. E., & Roath, A. S. (2006). Modeling lean, agile, and leagile supply chain strategies. Journal of Business Logistics27(1), 57-80.
23. Gunasekaran, A., Patel, C., & Tirtiroglu, E. (2001). Performance measures and metrics in a supply chain environment. Int J Operat Prod Manage21(1/2), 71–87.
24. Holweg, M. (2007). The genealogy of lean production. Journal of Operations Management, 25(3), 420-437.
25. Lambert, D. & Pohlen, L. (2001). Supply chain metrics, The International Journal of Logistics Management12 (1), 1-19.
26. Lin, C., Chiu, H., & Chu, P. (2006). Agility index in the supply chain. International Journal of Production Economics100(2), 285-299.
27. Naylor, B., Naim, M., & Berry, D. (1999). Leagility: integrating the lean and agile manufacturing paradigms in the total supply chain. Int J Prod Econ62(1–2), 107–118.
28. Schroer, B. (2004).Simulation as a tool in understanding the concepts of lean manufacturing, Simulation80(3), 171-175.
29. Tang, C. (2006). Robust strategies for mitigating supply chain disruptions. Int J Logist Res Appl9(1), 33–45.
30. Zobel, C. (2011).Representing perceived tradeoffs in defining disaster resilience. Decis Support Syst50(2), 394–403.
31. Zsidisin, G., Ragatz, G., & Melnyk, S. (2005). The dark side of supply chain management. Supply Chain Manage Rev, 9(2), 46–52.