Document Type : Research Paper


1 Assistant Professor, Department of Industrial Management, Allameh Tabatabai University, Tehran, Iran

2 Master's student in Industrial Management, Allameh Tabatabai University, Tehran, Iran


In today's markets that industries have faced different risks and disruptions, selecting the appropriate and resilient supplier has become a strategic factor for the success and sustainability of organizations in a turbulent and competitive business environment and has attracted much attention from researchers and practitioners. The natural stone industry is one of the most important industries in Iran. Hence, this study aims to identify and rank the evaluation criteria of resiliency in a real case study of natural stone industry. Gathering the criteria was done based on the previous related literature and in order to confirm the identified criteria, a survey of 10 stone industry experts was conducted using the fuzzy Delphi method. Consequently, 20 criteria was approved. In order to rank the approved criteria, the best-worst method (BWM) was used. The results showed that flexibility, velocity and financial performance are the most important suppliers' resiliency evaluation criteria in the stone industry, respectively.


Main Subjects

جعفرنژاد چقوشی، ا.، کاظمی، ع.، عرب، ع. (1395). شناسایی و اولویت بندی شاخص های ارزیابی تاب‌آوری تأمین‌کنندگان برپایه روش بهترین-بدترین. چشم انداز مدیریت صنعتی. 159-186.تهران، ایران.
 فرهادی، ف.، محمدی، ع.، محمودآبادی، م.، محمودی ماندنی، م.، محمد. (1399). شناسایی و رتبه‌بندی مؤلفه‌های انتخاب تأمین‌کننده تاب‌آور در صنعت فولاد چهارمحال و بختیاری با روش تحلیلتم و رویکرد ترکیبی (AHP-QUALIFLEX). فصلنامه مدیریت صنعتی، 15(53)، 1-13.
Afrasiabi, A., Tavana, M., & Di Caprio, D. (2022). An extended hybrid fuzzy multi-criteria decision model for sustainable and resilient supplier selection. Environmental Science and Pollution Research, 1-24.
Ates, A., & Bititci, U. (2011). Change process: A key enabler for building resilient SMEs. International Journal of Production Research, 49(18), 5601–5618.
Bakhtiari Tavana, A., Rabieh, M., Pishvaee, M. S., & Esmaeili, M. (2021). A Stochastic Mathematical Programming Approach to Resilient Supplier Selection and Order Allocation Problem: A Case Study in Iran Khodro Supply Chain. Scientia Iranica.
Barroso, A. P., Machado, V. H., Carvalho, H., & Cruz Machado, V. (2015). Quantifying the supply chain resilience. In H. Tozan, & A. Erturk (Eds.), Applications of contemporary management approaches in supply chains. ISBN: 978-953-51-2045-2.
Brandon-Jones, E., Squire, B., Autry, C. W., & Petersen, K. (2014). A contingent resource-based perspective of supply chain resilience and robustness. Journal of Supply Chain Management, 50(3), 55–73.
Cabral, I., Grilo, A., & Cruz-Machado, V. (2012). A decision-making model for lean, agile, resilient and green supply chain management. International Journal of Production Research, 50(17), 4830-4845.
Centobelli, P., Cerchione, R., & Ertz, M. (2020). Managing supply chain resilience to pursue business and environmental strategies. Business Strategy and the Environment, 29(3), 1215-1246.
Christopher, M., & Peck, H. (2004). Building the resilient supply chain.
Davoudabadi, R., Mousavi, S. M., & Sharifi, E. (2020). An integrated weighting and ranking model based on entropy, DEA and PCA considering two aggregation approaches for resilient supplier selection problem. Journal of Computational Science, 40, 101074.
Falasca, M., Zobel, C. W., & Cook, D. (2008, May). A decision support framework to assess supply chain resilience. In Proceedings of the 5th International ISCRAM Conference (pp. 596–605).
Fiksel, J. (2015). Resilient by design: Creating businesses that adapt and flourish in a changing world. USA: Island Press.
Ganguly, A., Chatterjee, D., & Rao, H. (2018). The role of resiliency in managing supply chains disruptions In Supply chain risk management (pp. 237-251). Springer.
Han, Y., Chong, W. K., & Li, D. (2020). A systematic literature review of the capabilities and performance metrics of supply chain resilience. International Journal of Production Research, 58(15), 4541-4566.
Ivanov, D. (2017). Simulation-based single vs. dual sourcing analysis in the supply chain with consideration of capacity disruptions, big data and demand patterns. International Journal of Integrated Supply Management, 11(1), 24-43.
Keliji, P., Abadi, B., & Abedini, M. (2018). Investigating readiness in the Iranian steel industry through six sigma combined with fuzzy delphi and fuzzy DANP. Decision Science Letters, 7(4), 465-480.
Khalili, S. M., Jolai, F., & Torabi, S. A. (2017). Integrated production–distribution planning in two-echelon systems: a resilience view. International Journal of Production Research, 55(4), 1040-1064.
Kim, Y., Chen, Y. S., & Linderman, K. (2015). Supply network disruption and resilience: A network structural perspective. Journal of Operations Management, 33–34, 43–59.
Leong, W. Y., Wong, K. Y., & Wong, W. P. (2022). A New Integrated Multi-Criteria Decision-Making Model for Resilient Supplier Selection. Applied System Innovation, 5(1), 8.
Mabrouk, N. (2021). Green supplier selection using fuzzy Delphi method for developing sustainable supply chain. Decision Science Letters, 10(1), 63-70.
Mohammed, A., Harris, I., Soroka, A., Naim, M. M., & Ramjaun, T. (2018). Evaluating Green and Resilient Supplier Performance: AHP-Fuzzy Topsis Decision-Making Approach. ICORES,
Mosayebi, A., Ghorbani, S., & Masoomi, B. (2020). Applying fuzzy delphi and best-worst method for identifying and prioritizing key factors affecting on university-industry collaboration. Decision Science Letters, 9(1), 107-118.
Nasrollahi, M., Fathi, M. R., Sobhani, S. M., Khosravi, A., & Noorbakhsh, A. (2021). Modeling resilient supplier selection criteria in desalination supply chain based on fuzzy DEMATEL and ISM. International Journal of Management Science and Engineering Management, 16(4), 264-278.
Ocampo, L., Ebisa, J. A., Ombe, J., & Geen Escoto, M. (2018). Sustainable ecotourism indicators with fuzzy Delphi method – A Philippine perspective. Ecological Indicators, 93, 874-888.
Özfirat, M. K., Özkan, E., Kahraman, B., Şengün, B., & Yetkin, M. E. (2017). Integration of risk matrix and event tree analysis: a natural stone plant case. Sādhanā, 42(10), 1741-1749.
Padilla-Rivera, A., do Carmo, B. B. T., Arcese, G., & Merveille, N. (2021). Social circular economy indicators: Selection through fuzzy delphi method. Sustainable Production and Consumption, 26, 101-110.
Piprani, A. Z., Jaafar, N. I., & Ali, S. M. (2020). Prioritizing resilient capability factors of dealing with supply chain disruptions: an analytical hierarchy process (AHP) application in the textile industry Benchmarking: An International Journal.
Pramanik, D., Mondal, S. C., & Haldar, A. (2020). Resilient supplier selection to mitigate uncertainty: soft-computing approach. Journal of Modelling in Management, 15(4), 1339-1361.
Ralston, P., & Blackhurst, J. (2020). Industry 4.0 and resilience in the supply chain: a driver of capability enhancement or capability loss? International Journal of Production Research, 58(16), 5006-5019.
Rezaei, J. (2015). Best-worst multi-criteria decision-making method. Omega, 53, 49-57.
Rezaei, J. (2016). Best-worst multi-criteria decision-making method: Some properties and a linear model. Omega, 64, 126-130.
Sahebjamnia, N. (2020). Resilient supplier selection and order allocation under uncertainty. Scientia Iranica, 27(1), 411-426.
afarnezhad Chaghooshi, A., Kazemi, A., & Arab, A. (2016). Identification and Prioritization of Supplier’s Resiliency Evaluation Criteria Based on BWM. Journal of Industrial Management Perspective, 6(Issue 3, Autumn 2016), 159-186.
 Farhadi, F., Mohammadi, A., Mahmoudabadi, M., Mahmoudi Mandani, M. (1399). Identifying and ranking the components of resilient supplier selection in Chaharmahal and Bakhtiari steel industry by theme analysis method and combined approach (AHP-QUALIFLEX). Industrial Management 53. 1-13.