Identifying and ranking suppliers' resilience evaluation indicators in the construction paint industry using the best-worst method

Subject Areas : Industrial Management

Mahdi Jahani ¹ , Mohammad Barzegar ² , Masoumeh Messi Bidgoli ³

1 - Department of Industrial Engineering and Management, Faculty of Industrial Engineering and Management, Shahrood University of Technology, Shahrood, Iran;
2 - Department of Industrial Engineering, Faculty of Industrial Engineering and Management, Shahrood University of Technology, Shahrood, Iran
3 - Industrial Engineering Group, Golpayegan College of Engineering, Isfahan University of Technology, Golpayegan, 87717-67498, Iran.

Received: 2025-06-02 Accepted : 2025-12-13 Published : 2025-11-15

Keywords: Best-worst method, Construction paint industry, Fuzzy Delphi approach, Multi-criteria decision-making, Resiliency of suppliers.,

Abstract :

In today’s turbulent business environment, industries face numerous risks and challenges. Selecting appropriate and resilient suppliers can ensure business continuity in the face of disruptions, enhance competitive advantage, and increase customer satisfaction. In this context, supplier resilience is of particular importance in the paint manufacturing industry. Due to exchange rate fluctuations and sanctions-related restrictions, this industry encounters significant difficulties in sourcing raw materials. Given the critical nature of the issue, the present study aims to identify and rank the resilience indicators of the architectural paint industry in Iran. In the first phase, relevant indicators were extracted from previous research. To validate the identified indicators, a fuzzy Delphi questionnaire was administered to 10 experts in the paint industry. Out of 23 identified indicators, 17 were ultimately confirmed. In the second phase, a questionnaire based on the Best-Worst Method (BWM) was designed to rank the confirmed indicators. This questionnaire was distributed among the same 10 experts, and the collected responses were used to perform the final ranking. The findings of the study revealed that the most important supplier resilience indicators in the architectural paint industry include customer service and satisfaction level, agility, and inventory management practices, in descending order of significance.

References:

Anjali.S., Priyanka,. V., Karuna,J., (2022). Supplier resilience assessment in project-driven supply chains Volume 33, 2022 - Issue 9-10: Supply Chain Management in Construction and Engineer-to-order Industries. DOI: 10.1108/TQM-07-2020-0160. ISSN: 17542731
Bowen,F., Siegler, J., (2024). The role of visibility in supply chain resiliency: Applying the Nexus supplier index to unveil hidden critical suppliers in deep supply networks: Decision Support Systems. Volume 176, January 2024, 114063.
Chang.Y., Wilkinso,. S., Seville, E., Potangaroa , R.,(2010). Resourcing for a resilient post‐disaster reconstruction environment. International Journal of Disaster Resilience in the Built Environment. ISSN: 1759-5908. Article publication date: 26 February 2010
Chen.X., Xi,. Z., Jing,P., Authors,A., (2017). A Unified Framework for Evaluating Supply Chain Reliability and Resilience. IEEE Transactions on Reliability ( Volume: 66, Issue: 4, December 2017).
Ganguly, A., Chatterjee, D., & Rao, H. (2018). The role of resiliency in managing supply chain disruptions In Supply chain risk management (pp. 237-251). Springer.
Hajian Heydari, Mojtabi., Mirza Alian, Maedeh., Identification and ranking of suppliers' resilience evaluation criteria in the natural building stone industry, . (2022). 20th year, No. 56 Summer, 0410 pp. 001 to 041 jims.atu.ac.ir DOI : 10.22054/JIMS.2022.66299.2767 Industrial Management Studies Quarterly.
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
Ishikaw,A., Amagasa,M., Shiga,T., Tomizawa,G., Tatsuta,R., Mieno,H.,(1993). The max-min Delphi method and fuzzy Delphi method via fuzzy integration, Volume 55, Issue 3, 10 May 1993, Pages 241-253. https://doi.org/10.1016/0165-0114(93)90251-C
Jafaranjad Chagoshi, Ahmad. Kazemi, great. Arab, Alireza. (2016). Identifying and prioritizing suppliers' resilience evaluation indicators based on the best-worst method. Industrial management perspective. -159-186. Tehran, Iran.
. 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
. 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
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
. Pham, C.P., Nguyen, P.T. and Phan, P.T. (2022). Application of the Grey System Theory in Construction Management: A Case Study of Construction Paint Supplier Evaluation and Selection Criteria. Engineering, Technology & Applied Science Research. 12, 5 (Oct. 2022), 9087–9091. DOI:https://doi.org/10.48084/etasr.5145
. Rahimi, A., Karimi Gharsaki, M. H., Amirreza. Z.,(2022) Presentation of a framework for choosing a lean, agile and resilient supplier in the food industry supply chain with a combined approach of multi-criteria decision-making and rough numbers (case study: Atka organization), management studies Industrial, 22nd year, number, 27 Bahar, 3041, pp. 373 to 323 jims.atu.ac.ir DOI: 10.22054/jims.2024.76548.2885
Rahnamay Bonab, S., Haseli, G., Rajabzadeh, H., Jafarzadeh Ghoushchi, S. ., Hajiaghaei-Keshteli, M., & Tomaskova, H. . (2023). Sustainable resilient supplier selection for IoT implementation based on the integrated BWM and TRUST under spherical fuzzy sets. Decision Making: Applications in Management and Engineering, 6(1), 153–185. https://doi.org/10.31181/dmame12012023b
Rajesh, R., Ravi, V., (2015). Supplier selection in resilient supply chains: a grey relational analysis approach: Journal of Cleaner Production. Volume 86, 1 January 2015, Pages 343-359. https://doi.org/10.1016/j.jclepro.2014.08.054
. Rezaei, J. (2015). Best-worst multi-criteria decision-making method: Some properties and a linear model. Omega.
Rostami, Saber, 1402, Presenting a new supplier resilience assessment framework to improve supply chain resilience: a case study, 14th International Conference on Recent Advances in Industrial Engineering and Management, https://civilica.com/doc/ 1701755
Shishodia.A., Verma,. P., Dixit,V., (2019). Supplier evaluation for resilient project-driven supply chain Computers & Industrial Engineering Volume 129, March 2019, Pages 465- 47.https://doi.org/10.1016/j.cie.2019.02.006
Sonar.H., Gunasekaran,. A., Agrawal,S., Roy,M., (2022). Role of lean, agile, resilient, green, and sustainable paradigm in supplier selection. Cleaner Logistics and Supply Chain Volume 4, July 2022, 100059. https://doi.org/10.1016/j.clscn.2022.100059
. Soni, U., Jain, V., & Kumar, S. (2014). Measuring supply chain resilience using a deterministic modeling approach. Computers & Industrial Engineering, 74, 11-25
.