The resilience evaluation model for supply chain with integrated DEMATEL, ANP and Gray theory approach (Case study: Isfahan mobarakeh steel Co.)

Document Type : Applied Article

Authors

1 University of Imam Hossein (PBUH)

2 , Faculty of Management and Strategic Planning, Imam Hossein Compressive University

3 Phd. Student, Industrial Engineering Department, Imam Hossein Compressive University, Tehran, Iran.

Abstract

By the rapid advancement of technology and the creation of global markets, competition, turbulence and environmental uncertainty have been enhanced. In the same vein, competition between companies has replaced the competition between the chains. Chaos and uncertainty have adverse effects on the supply chain and can lead to reduced corporate profitability and competitive advantage. In this situation, the selection of suppliers who can withstand more uncertainty and resilience and deliver the goods and services at the time specified by the customer is considered necessary for the organization. The purpose of this research is to evaluate the resilience of the supply chain in Mobarakeh Steel Co., Isfahan. To this end, the theoretical framework has first emerged from a comprehensive literature review and research on the resilience of the supply chain. With the help of this framework, the resiliency criteria of the supply chain were extracted and, according to experts, the criteria were confirmed. Then, using the DEMATEL method, the relationships between the indices and sub-indices were determined and using the ANP method, the importance of each of the criteria was determined. Among the criteria, the sub-criteria of agility, addiction, and risk management culture have the highest weight. At the end, they have been ranked by the Grey ARAS of the suppliers of Mobarakeh Steel Co. in terms of the degree of viability, and the supplier of Behran is considered at the highest rating.

Keywords

References

[1] Bouzon, M., Govindan, K., Rodriguez, C. M. T., & Campos, L. M. (2016). Identification and analysis of reverse logistics barriers using fuzzy Delphi method and AHP. Resources, Conservation and Recycling.
[2] Chen I. (2016), “A combined MCDM model based on DEMATEL and ANP for the selection of airline service quality improvement criteria: A study based on the Taiwanese airline industry”, Journal of Air Transport Management, no. 57, pp.7-18.
[3] Chiang, C., Kocabasoglu-Hillmer, C. and Suresh, N. (2012), “An empirical investigation of the impact of strategic sourcing and flexibility on firm’s supply chain agility”, International Journal of Operations & Production Management, Vol. 32 No. 1, pp. 49-78.
[4] Christopher, M., & Peck, H. (2004). Building the resilient supply chain. The international journal of logistics management, 15(2), 1-14.
[4] Christopher, M., Mena, C., Khan, O., & Yurt, O. (2011). Approaches to managing global sourcing risk. Supply Chain Management: An International Journal, 16(2), 67-81.
[5] Fu, X. Zhu, Q. & Sarkis, J. (2012). “Evaluating green supplier development programs at a telecommunications systems provider”. International Journal of Production Economics, 140(1), 357-367.
[6] Hohenstein, N. O., Feisel, E., Hartmann, E., & Giunipero, L. (2015). Research on the phenomenon of supply chain resilience: a systematic review and paths for further investigation. International Journal of Physical Distribution & Logistics Management, 45(1/2), 90-117.
[7] Jüttner, U., & Maklan, S. (2011). Supply chain resilience in the global financial crisis: an empirical study. Supply Chain Management: An International Journal, 16(4), 246-259.
[8] KHoshsepehr Z, Ghasemi A.R, Maleki M.H (2016). Providing a framework for the assessment of Antifragility with a hybrid approach AHP and Grey-COPRA (Case Study: Industrial Group Golriz Qom), Tehran Uni, 19-20. (in persian)
[9] Mansory F, Abbasnejad T, Askarpor H.R. (2017), Designing an agile supply chain network in terms of demand dependence on price, Modern Researches in Decision Making, 179-206.
[10] Parsaei M, Nili Ahmadabadi, M. (2017), Prioritizing Maintenance Strategies with a Combination Approach DEMATEL-ANP-COPRAS in Auto Parts Manufacturing Industry Case Study: Milad Company of Qom, Modern Researches in Decision Making, 32-33. (in persian)
[11]Pettit, T. J., Fiksel, J., & Croxton, K. L. (2010). Ensuring supply chain resilience: development of a conceptual framework. Journal of Business Logistics, 31(1), 1-21.
[12] Ponomarov, S. Y., & Holcomb, M. C. (2009). Understanding the concept of supply chain resilience. The International Journal of Logistics Management, 20(1), 124-143.
[13] Rahimian M.M, Rajabzadeh Ghatari A. (2017), Measuring Supply Chain Resilience using Complex Adaptive Systems approach; Case Study: Iranian Pharmaceutical Industry, Modern Researches in Decision Making, 158-159. (in persian)
[14] Rajesh, R., & Ravi, V. (2015). Supplier selection in resilient supply chains: a grey relational analysis approach. Journal of Cleaner Production, 86, 343-359.
[15] Roberta Pereira, C., Christopher, M., & Lago Da Silva, A. (2014). Achieving supply chain resilience: the role of procurement. Supply Chain Management: an international journal, 19(5/6), 626-642.
[16] Sahu, A. K., Datta, S., & Mahapatra, S. S. (2016). Evaluation and selection of resilient suppliers in fuzzy environment: exploration of fuzzy-VIKOR.Benchmarking: An International Journal, 23(3).
[17] Sheffi, Y. (2005). Building a resilient supply chain. Harvard Business Review, 1-4.
[18] Soni, U., Jain, V., & Kumar, S. (2014). Measuring supply chain resilience using a deterministic modeling approach. Computers & Industrial Engineering, 74, 11-25.
[19] Tang, Christopher S. (2006) "Robust strategies for mitigating supply chain disruptions" International Journal of Logistics: Research and Applications 9(1),33-45.
[20] Tukamuhabwa, B. R., Stevenson, M., Busby, J., & Zorzini, M. (2015). Supply chain resilience: definition, review and theoretical foundations for further study. International Journal of Production Research, 53(18), 5592-5623.
[21] Turskis, Z. & Zavadskas, E. K. (2010). A novel method for multiple criteria analysis: grey       additive ratio assessment (ARAS-G) method. Informatica,21(4), 597-610.
[22] Turskis, Z. Zavadskas, E. K. & Kutut, V. (2013). A model based on ARAS-G and AHP methods for multiple criteria prioritizing of heritage value.International Journal of Information Technology & Decision Making, 12(01), 45-73.
[23] Wieland, Andreas, and Carl Marcus Wallenburg. (2013), "The influence of relational competencies on supply chain resilience: a relational view". International [24] Journal of Physical Distribution & Logistics Management 43(4),300-320.
Yang, Y., & Xu, X. (2015). Post-disaster grain supply chain resilience with government aid. Transportation research part E: logistics and transportation review, 76, 139-159.
Supply Chain Management
Volume 21, Issue 65
June 2020
Pages 60-72

Files

History

  • Receive Date: 20 February 2020
  • Revise Date: 05 April 2020
  • Accept Date: 13 April 2020
  • Publish Date: 19 May 2020

Share

How to cite

Statistics