Civil and Project journal

Quantitative assessment of supply chain risk on project activities in project-driven supply chains under uncertainty

10.22034/cpj.2026.601387.1472
Volume 8, Issue 11 - Serial Number 93
January 2027
Pages 59-81
Civil and Project journal

Document Type : Research Article

Authors

farid farpour 1
Hamid Reza Sobhi 2

1 Department of Architecture, Faculty of Art and Architecture, Islamic Azad University - South Tehran Branch, Tehran, Iran

2 Department of Project and Construction Management, Islamic Azad University, South Tehran Branch, Tehran, Iran

Abstract
Project-driven organizations have given rise to project-driven supply chains due to their focus on their core and greater dependence on their contractors and suppliers. For this reason, the study and evaluation of project-driven supply chains has become an interesting topic in recent years. In this regard, in this study, two methods are presented for the two parts of the supply chain and project management in the project-driven supply chain. First, a combined method including CoCoSo methods and the best-worst method is presented to evaluate the resilience of suppliers in the supply chain environment. Then, this index is used to quantify the risk of suppliers on project activities. This is done using fuzzy alpha-cut. The proposed method for evaluating suppliers and the developed critical path method is developed in a fuzzy environment to deal with uncertainty. After applying alpha-cut to the time of project activities and quantifying the supply chain risk on them, the fuzzy critical path method is presented to determine the critical path and the criticality of activities. But in the fuzzy critical path, to determine the floats of activities, negative numbers are generated, which is unacceptable, in this regard, a new fuzzy subtraction method for the critical path is presented to prevent the generation of negative numbers. The proposed method is applied to a case study to demonstrate its effectiveness. Then, sensitivity analysis is performed on the weight of resilience criteria, which indicates the stability of the proposed results. Also, comparative consistency shows the consistency of the results of the proposed method.

Keywords

Risk quantification
project-driven supply chain
fuzzy CoCoSo method
Fuzzy best-worst method
Fuzzy critical path method
Subjects
Alimohammadlou, M., & Khoshsepehr, Z. (2025). Green-resilient supplier selection: a hesitant fuzzy multi-criteria decision-making model: M. Alimohammadlou, Z. Khoshsepehr. Environment, development and sustainability, 27(9), 22107-22143.
Alizdeh, S., & Saeidi, S. (2020). Fuzzy project scheduling with critical path including risk and resource constraints using linear programming. International Journal of Advanced Intelligence Paradigms, 16(1), 4-17.
Arora, A., Swarnakar, V., Singh, M., & Gaur, R. (2026). Strategic prioritization of sustainable Lean-Green initiatives in the farming industry using an integrated BWM-Fuzzy TOPSIS framework. The TQM Journal, 1-27.
Chanas, S., & Zieliński, P. (2001). Critical path analysis in the network with fuzzy activity times. Fuzzy sets and systems, 122(2), 195-204.
Dorfeshan, Y., Jolai, F., & Mousavi, S. M. (2023). A multi-criteria decision-making model for analyzing a project-driven supply chain under interval type-2 fuzzy sets. Applied Soft Computing, 148, 110902.
Ecer, F. (2024). A state-of-the-art review of the BWM method and future research agenda. Technological and Economic Development of Economy, 30(4), 1165-1204.
Gan, J., Zhong, S., Liu, S., & Yang, D. (2019). Resilient Supplier Selection Based on Fuzzy BWM and GMo‐RTOPSIS under Supply Chain Environment. Discrete Dynamics in Nature and Society, 2019(1), 2456260.
Hailiang, Z., Khokhar, M., Islam, T., & Sharma, A. (2023). A model for green-resilient supplier selection: fuzzy best–worst multi-criteria decision-making method and its applications. Environmental Science and Pollution Research, 30(18), 54035-54058.
Jafari, M., & Khanachah, S. N. (2024). Integrated knowledge management in the supply chain: assessment of knowledge adoption solutions through a comprehensive CoCoSo method under uncertainty. Journal of Industrial Information Integration, 39, 100581.
Kampalasiri, C., Pitiruek, K., & Sureeyatanapas, P. (2026). An enhanced TOPSIS method for resilient supplier selection under data uncertainty. International journal of management science and engineering management, 21(1), 36-51.
Moslem, S. (2025). Evaluating commuters' travel mode choice using the Z-number extension of Parsimonious Best Worst Method. Applied Soft Computing, 173, 112918.
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.
Rasoanaivo, R. G., Yazdani, M., Zaraté, P., & Fateh, A. (2024). Combined Compromise for Ideal Solution (CoCoFISo): a multi-criteria decision-making based on the CoCoSo method algorithm. Expert Systems with Applications, 251, 124079.
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.
Shishodia, A., Sharma, R., MR, P., & Mathiyazhagan, K. (2024). Analyzing drivers of sustainable project‐driven supply chains: A fuzzy Delphi methodology–grey relational analysis approach. Business Strategy and the Environment, 33(3), 1626-1646.
Shishodia, A., Verma, P., & Dixit, V. (2019). Supplier evaluation for resilient project driven supply chain. Computers & Industrial Engineering, 129, 465-478.
Shishodia, A., Verma, P., & Jain, K. (2022). Supplier resilience assessment in project-driven supply chains. Production Planning & Control, 33(9-10), 875-893.
Taghizadeh, A., Karaminezhad, K., Fakhri, N., Moghaddami, B., & Charkhian, D. (2025). Assessing innovation strategies in the digital economy through artificial intelligence-based criteria using CoCoSo method. Journal of Intelligent Decision Making and Granular Computing, 1(1), 237-255.
Tajally, A., Babakhani, B., Jeyzanibrahimzade, E., Parvin, M., & Irani, S. (2025). Sustainable supplier selection and order allocation problem considering the agility and resilience dimensions: a novel multi-stage data-driven decision-making approach. International journal of systems science: Operations & logistics, 12(1), 2458756.
Trivedi, P., Shah, J., Čep, R., Abualigah, L., & Kalita, K. (2024). A hybrid best-worst method (BWM)–technique for order of preference by similarity to ideal solution (TOPSIS) approach for prioritizing road safety improvements. IEEe Access.
Wang, T. K., Zhang, Q., Chong, H. Y., & Wang, X. (2017). Integrated supplier selection framework in a resilient construction supply chain: An approach via analytic hierarchy process (AHP) and grey relational analysis (GRA). Sustainability, 9(2), 289.
Yazdani, M., Zarate, P., Kazimieras Zavadskas, E., & Turskis, Z. (2019). A combined compromise solution (CoCoSo) method for multi-criteria decision-making problems. Management decision, 57(9), 2501-2519.
Zammori, F. A., Braglia, M., & Frosolini, M. (2009). A fuzzy multi-criteria approach for critical path definition. International Journal of Project Management, 27(3), 278-291.
  • Receive Date 07 August 2026
  • Revise Date 08 September 2026
  • Accept Date 10 September 2026
  • First Publish Date 10 September 2026
  • Publish Date 21 January 2027

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