A Hybrid Statistical–MCDM Framework for Integrated Risk Prioritization and Sustainability Assessment in Construction Supply Chains: Bridging Local Data with Global Theory
Keywords:
Sustainable Construction, Construction Project Management, Sustainable Supply Chain Management, Analytic Network Process, Risk PrioritizationAbstract
This study aimed to develop and empirically validate a hybrid statistical–multi-criteria decision-making (MCDM) framework for identifying, prioritizing, and managing sustainability-related risks and strategic interventions in construction supply chains within the context of the Qeshm Free Trade Zone. A practical descriptive–inferential research design was employed using a structured Delphi survey administered to 33 experts, including project managers, engineers, contractors, consultants, and supply chain professionals involved in major construction projects in Qeshm. Following expert consensus, a questionnaire measuring economic, social, environmental, and structural risks, as well as key supply chain success drivers, was developed and validated. Reliability was confirmed through Cronbach’s alpha coefficients. One-sample t-tests were conducted to determine statistically significant risk factors. The Analytic Network Process (ANP) was applied to prioritize critical supply chain drivers and capture interdependencies among criteria, while the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) was used to rank sustainability-oriented management strategies based on multiple performance criteria. The results revealed that economic risks, including supplier financial challenges, material price volatility, exchange-rate fluctuations, transportation costs, and delay-related expenses, were statistically significant. Environmental risks, such as pollution, resource depletion, non-renewable resource usage, and environmental compliance issues, also demonstrated significant effects. ANP results indicated that Material Supply Management was the most influential driver (weight = 0.553), followed by Design and Engineering Management (0.294), Manufacturing and Production Management (0.094), and Workforce Supply and Safety Management (0.059). At the sub-criterion level, provision of high-quality domestic building materials (0.304) and optimal foundation design (0.215) received the highest priorities. TOPSIS analysis identified sustainable supply chain management software (0.8962) and sustainable material selection (0.8664) as the most effective strategic interventions. The integration of statistical analysis, ANP, and TOPSIS provides a robust decision-support framework for sustainable construction supply chain management. The findings demonstrate that economic volatility, environmental pressures, material quality, and engineering effectiveness are dominant determinants of sustainable performance.
References
Ada, E., Sezer, M. D., & Khaleel, R. (2023). Towards the Smart Sustainable and Circular Food Supply Chains through Digital Technologies. International Journal of Mathematical, Engineering and Management Sciences, 8(3), 022. https://doi.org/10.33889/ijmems.2023.8.3.022
Adem, A., Çolak, A., & Dağdeviren, M. (2018). An Integrated Model Using SWOT Analysis and Hesitant Fuzzy Linguistic Term Set for Evaluation Occupational Safety Risks in Life Cycle of Wind Turbine. Safety Science, 106, 184-190. https://doi.org/10.1016/j.ssci.2018.02.033
Alamdari, A. M., Jabarzadeh, Y., Adams, B., Samson, D., & Khanmohammadi, S. (2023). An Analytic Network Process Model to Prioritize Supply Chain Risks in Green Residential Megaprojects. Operations Management Research, 16(1), 141-163. https://doi.org/10.1007/s12063-022-00288-2
Alshehri, S. M. A., Jun, W. X., Shah, S. A. A., & Solangi, Y. A. (2022). Analysis of Core Risk Factors and Potential Policy Options for Sustainable Supply Chain: An MCDM Analysis of Saudi Arabia's Manufacturing Industry. Environmental Science and Pollution Research, 29(17), 25360-25390. https://doi.org/10.1007/s11356-021-17558-4
Altekar, R. V. (2023). Supply Chain Management: Concepts and Cases. PHI Learning Pvt. Ltd.
Attia, E. A., & Uddin, M. S. (2024). Hybrid Assessment for Strengthening Supply Chain Resilience and Sustainability: A Comprehensive Analysis. Sustainability, 16(10), 4010. https://doi.org/10.3390/su16104010
Boadu, E. F., Sunindijo, R. Y., Wang, C. C., & Frimpong, S. (2022). Client-Led Promotion of Health and Safety through the Procurement Process on Public Construction Projects in Developing Countries. Safety Science, 147, 105605. https://doi.org/10.1016/j.ssci.2021.105605
Brusset, X., & Teller, C. (2017). Supply Chain Capabilities, Risks, and Resilience. International Journal of Production Economics, 184, 59-68. https://doi.org/10.1016/j.ijpe.2016.09.008
Chakraborty, S. (2022). TOPSIS and Modified TOPSIS: A Comparative Analysis. Decision Analytics Journal, 2, 100021. https://doi.org/10.1016/j.dajour.2021.100021
Chen, C., & Tang, L. (2019). BIM-Based Integrated Management Workflow Design for Schedule and Cost Planning of Building Fabric Maintenance. Automation in Construction, 107, 102944. https://doi.org/10.1016/j.autcon.2019.102944
Ciardiello, F., & Genovese, A. (2023). A Comparison between TOPSIS and SAW Methods. Annals of Operations Research, 325(2), 967-994. https://doi.org/10.1007/s10479-023-05339-w
Fang, C., Marle, F., Xie, M., & Zio, E. (2013). An Integrated Framework for Risk Response Planning under Resource Constraints in Large Engineering Projects. Ieee Transactions on Engineering Management, 60(3), 627-639. https://doi.org/10.1109/TEM.2013.2242078
Fernie, J. (2023). Relationships in the Supply Chain. In Logistics and Retail Management: Insights into Current Practice and Trends from Leading Experts (pp. 23-46). CRC Press.
Hanaysha, J. R., & Alzoubi, H. M. (2022). Investigating the Impact of Benefits and Challenges of IoT Adoption on Supply Chain Performance and Organizational Performance: An Empirical Study in Malaysia. Uncertain Supply Chain Management, 10(2), 537-550. https://doi.org/10.5267/j.uscm.2021.11.005
Hasaniyan Pourfereidani, A., Feili, A., Nikmanesh, M., & Sorooshian, S. (2025). An Analysis of Success in Supply Chain Management for Construction Projects: Fuzzy Inference System Application. Journal of Soft Computing in Civil Engineering, 9(2), 167-195. https://doi.org/10.22115/scce.2024.416971.1721
Hugos, M. H. (2024). Essentials of Supply Chain Management. John Wiley & Sons.
Hussein, M., Eltoukhy, A. E., Karam, A., Shaban, I. A., & Zayed, T. (2021). Modelling in Off-Site Construction Supply Chain Management: A Review and Future Directions for Sustainable Modular Integrated Construction. Journal of Cleaner Production, 310, 127503. https://doi.org/10.1016/j.jclepro.2021.127503
Ika, L. A., & Pinto, J. K. (2022). The Re-Meaning of Project Success: Updating and Recalibrating for a Modern Project Management. International Journal of Project Management, 40(7), 835-848. https://doi.org/10.1016/j.ijproman.2022.08.001
Jamalnia, A., Gong, Y., Govindan, K., Bourlakis, M., & Mangla, S. K. (2023). A Decision Support System for Selection and Risk Management of Sustainability Governance Approaches in Multi-Tier Supply Chain. International Journal of Production Economics, 264, 108960. https://doi.org/10.1016/j.ijpe.2023.108960
Johnsson, F., Karlsson, I., Rootzén, J., Ahlbäck, A., & Gustavsson, M. (2020). The Framing of a Sustainable Development Goals Assessment in Decarbonizing the Construction Industry: Avoiding Greenwashing. Renewable and Sustainable Energy Reviews, 131, 110029. https://doi.org/10.1016/j.rser.2020.110029
Lepistö, K., Saunila, M., & Ukko, J. (2024). Enhancing Customer Satisfaction, Personnel Satisfaction and Company Reputation with Total Quality Management: Combining Traditional and New Views. Benchmarking, 31(1), 75-97. https://doi.org/10.1108/BIJ-12-2021-0749
Ma, G., Wu, Z., Jia, J., & Shang, S. (2021). Safety Risk Factors Comprehensive Analysis for Construction Project: Combined Cascading Effect and Machine Learning Approach. Safety Science, 143, 105410. https://doi.org/10.1016/j.ssci.2021.105410
Mohandes, S. R., Abdelmageed, S., Hem, S., Yoo, J. S., Abhayajeewa, T., & Zayed, T. (2022). Occupational Health and Safety in Modular Integrated Construction Projects: The Case of Crane Operations. Journal of Cleaner Production, 342, 130950. https://doi.org/10.1016/j.jclepro.2022.130950
Mossalam, A., & Arafa, M. (2017). Using Artificial Neural Networks (ANN) in Projects Monitoring Dashboards' Formulation. HBRC Journal, 14(3), 385-392. https://doi.org/10.1016/j.hbrcj.2017.11.002
Munier, N., & Hontoria, E. (2021). Shortcomings of the AHP Method. In Uses and Limitations of the AHP Method: A Non-Mathematical and Rational Analysis (pp. 41-90). Springer International Publishing. https://doi.org/10.1007/978-3-030-60392-2
Natalia, C., Surbakti, I. P., & Oktavia, C. W. (2020). Integrated ANP and TOPSIS Method for Supplier Performance Assessment. Jurnal Teknik Industri, 21(1), 34-45. https://doi.org/10.22219/JTIUMM.Vol21.No1.34-45
Patel-Jena, R. K., & Dwivedi, Y. (2023). Prioritizing the Barriers to Tourism Growth in Rural India: An Integrated Multi-Criteria Decision Making (MCDM) Approach. Journal of Tourism Futures, 9(3), 393-416. https://doi.org/10.1108/JTF-10-2020-0171
Qazi, A., Shamayleh, A., El-Sayegh, S., & Formaneck, S. (2021). Prioritizing Risks in Sustainable Construction Projects Using a Risk Matrix-Based Monte Carlo Simulation Approach. Sustainable Cities and Society, 65, 102576. https://doi.org/10.1016/j.scs.2020.102576
Shiliang, S., Min, J., Yong, L., & Runqui, L. (2012). Risk Assessment on Falling from Height Based on AHP-Fuzzy. Procedia Engineering,
Shou, Y., Kang, M., & Park, Y. W. (2022). A Systematic Literature Review of Supply Chain Integration. In Supply Chain Integration for Sustainable Advantages (pp. 15-40). Springer. https://doi.org/10.1007/978-981-16-9332-8_2
Tiira, K., & Lohi, H. (2014). Reliability and Validity of a Questionnaire Survey in Canine Anxiety Research. Applied Animal Behaviour Science, 155, 82-92. https://doi.org/10.1016/j.applanim.2014.03.007
Torp, O., Belay, A. M., Thodesen, C., & Klakegg, O. J. (2016). Cost Development over Time at Construction Planning Phase: Empirical Evidence from Norwegian Construction Projects. Procedia Engineering, 145, 1177-1184. https://doi.org/10.1016/j.proeng.2016.04.152
Wuni, I. Y., & Shen, G. Q. (2020). Critical Success Factors for Modular Integrated Construction Projects: A Review. Building Research & Information, 48(7), 763-784. https://doi.org/10.1080/09613218.2019.1669009
Zanjani, M. E., Najafi, A., Naghilou, A., & Mohammadi, N. (2021). Identification and Assessment of Critical Risks of Sustainable Supply Chain in the Iranian Lead and Zinc Industry. International Journal of Industrial Engineering & Production Research, 32(3), 1-22. http://ijiepr.iust.ac.ir/article-1-1149-en.html
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Mahyar Amin Forghani (Author); Sohail Dadkhah; Mohsen Dadras (Author)
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
