Evaluating Disruption Risk to Foster Resilience in Humanitarian Supply Chain:  An Integrated SV-PSI and EDAS Model

Authors

  • Agung Sutrisno Universitas Sam Ratulangi Indonesia
  • Christian Spreafico University of Bergamo Italy
  • Muhammad Dwisnanto Putro Universitas Sam Ratulangi Indonesia
  • Ade Yusupa Universitas Sam Ratulangi Indonesia
  • Amir Tjolleng Bina Nusantara University Indonesia
  • Kenji Lokaputra Bina Nusantara University Indonesia

DOI:

https://doi.org/10.26877/asset.v8i4.3345

Keywords:

Humanitarian Supply Chain, Risk Assessment, FMEA, Resilience, EDAS

Abstract

The evaluation of the risks in humanitarian supply chain operations is crucial to prevent losses due to disasters. However, many quantitative studies in the literature are aimed at the profit-oriented supply chain, while those in the field are based on the subjective preferences of decision-makers, making risk prioritization less accurate. To fill this gap, this study presents a theoretically improved approach for this purpose by integrating statistical variance, preference selection index (PSI), and EDAS methods into humanitarian supply chain FMEA to prioritize risks. To demonstrate the applicability of the model, numerical calculations and sensitivity tests were conducted using secondary data. The test results indicate that the dimension of risk detection capability is an important dimension for proactive risk prevention. Furthermore, communication in humanitarian disaster response supply chain operations is a very important enabler for the resilience of the humanitarian supply chain. In the future, inclusion of the influence of relationships between decision criteria and between risk factors is recommended as a direction for further research from this study.

Author Biographies

  • Agung Sutrisno, Universitas Sam Ratulangi

    Industrial Engineering Department, Faculty of Engineering, Universitas Sam Ratulangi, Kampus Bahu, Manado 95115, North Sulawesi, Indonesia

  • Christian Spreafico, University of Bergamo

    Department of Management Information and Production Engineering, University of Bergamo, Viale Marconi 5, 24044, Dalmine, Bergamo, Italy

  • Muhammad Dwisnanto Putro, Universitas Sam Ratulangi

    Informatics Engineering Department, Faculty of Engineering, Universitas Sam Ratulangi, Kampus Bahu, Manado 95115, North Sulawesi, Indonesia

  • Ade Yusupa, Universitas Sam Ratulangi

    Informatics Engineering Department, Faculty of Engineering, Universitas Sam Ratulangi, Kampus Bahu, Manado 95115, North Sulawesi, Indonesia

  • Amir Tjolleng, Bina Nusantara University

    Industrial Engineering Department, Faculty of Engineering, Bina Nusantara University, Jakarta 11480, Indonesia

  • Kenji Lokaputra, Bina Nusantara University

    Industrial Engineering Department, Faculty of Engineering, Bina Nusantara University, Jakarta 11480, Indonesia

References

[1] Eckhardt D, Leiras A, Thomé A M T. Systematic literature review of methodologies for assessing the costs of disasters. International Journal of Disaster Risk Reduction 2019; 33:398–416. https://doi.org/10.1016/j.ijdrr.2018.10.010.

[2] Zhang J, Wang Z, Ren F. Optimization of humanitarian relief supply chain reliability: a case study of the Ya’an earthquake. Annals of Operation Research 2019;283:1551–72. https://doi.org/10.1007/s10479-018-03127-5.

[3] Köstepen ZN, Selim H. Literature Review on Humanitarian Logistics in Disaster Management: A Risk-Oriented Approach. Sustainability 2025;17:9773. https://doi.org/10.3390/su17219773.

[4] Kundu T, Sheu J-B, Kuo H-T. Emergency logistics management—Review and propositions for future research. Transportation Research Part E: Logistics and Transportation Review 2022;164:102789. https://doi.org/10.1016/j.tre.2022.102789.

[5] Arier T N, Roechmoljati R, Nugraha I. Waste Analysis in The Production Process Urea Fertilizer Using The Lean Six Sigma Method and Recommendations for Improving Failure Mode Effect Analysis (FMEA) at PT. Damai Sejahtera. Advance Sustainable Science Engineering and Technology 2024;6: 0240303-01. https://doi.org/10.26877/asset.v6i3.579

[6] Widotomo G. Improving Analysis of Risk-Based Maintenance Management Strategies Through Reliability Centered Maintenance. Case Study: Coal Crushing Plant. Central Kalimantan. Indonesia. Advance Sustainable Science, Engineering and Technology 2023;6:0240109. https://doi.org/10.26877/asset.v6i1.17529.

[7] Huang J, You J-X, Liu H-C, Song M-S. Failure mode and effect analysis improvement: A systematic literature review and future research agenda. Reliability Engineering and System Safety 2020;199:106885. https://doi.org/10.1016/j.ress.2020.106885.

[8] Nain A, Jain D, Trivedi A. Multi-criteria decision-making methods: application in humanitarian operations. Benchmarking: An International Journal 2024;31:2090–128. https://doi.org/10.1108/BIJ-11-2022-0673.

[9] Pournader M, Kach A, Talluri S (Sri). A Review of the Existing and Emerging Topics in the Supply Chain Risk Management Literature. Decision Sciences 2020; 51:867–919. https://doi.org/10.1111/deci.12470.

[10] Wu Z, Liu W, Nie W. Literature review and prospect of the development and application of FMEA in manufacturing industry. The International Journal of Advanced Manufacturing Technology 2021;112:1409–36. https://doi.org/10.1007/s00170-020-06425-0.

[11] Chakhrit A, Benharkat NEH, Guetarni IHM, Guedri A, Chennoufi M. A literature review of risk assessment approaches in failure mode and effects analysis. International Journal of Quality & Reliability Management 2025;42:2415–54. https://doi.org/10.1108/IJQRM-01-2025-0042.

[12] Minguito G, Banluta J. Risk management in humanitarian supply chain based on FMEA and grey relational analysis. Socioeconomics Planning Sciences 2023; 87:101551. https://doi.org/10.1016/j.seps.2023.101551.

[13] Chukwuka OJ, Ren J, Wang J, Paraskevadakis D. A comprehensive research on analyzing risk factors in emergency supply chains. Journal of Humanitarian Logistics and Supply Chain Management 2023;13:249–92. https://doi.org/10.1108/JHLSCM-10-2022-0108.

[14] Nguyen P-H, Nguyen L-AT. A Spherical Fuzzy Sets Approach to Humanitarian Logistics: Typhoon Yagi and Vietnam’s Disaster Risk Response, 2025, p. 572–9. https://doi.org/10.1007/978-3-031-98304-7_63.

[15] Wen T-C, Chung H-Y, Chang K-H, Li Z-S. A flexible risk assessment approach integrating subjective and objective weights under uncertainty. Engineering Application of Artificial Intelligent 2021;103:104310. https://doi.org/10.1016/j.engappai.2021.104310.

[16] Tay HL, Banomyong R, Varadejsatitwong P, Julagasigorn P. Mitigating Risks in the Disaster Management Cycle. Advances in Civil Engineering 2022;2022. https://doi.org/10.1155/2022/7454760.

[17] Hassan F ul, Nguyen T, Le T, Le C. Automated prioritization of construction project requirements using machine learning and fuzzy Failure Mode and Effects Analysis (FMEA). Autom Constr 2023;154:105013. https://doi.org/10.1016/j.autcon.2023.105013.

[18] Spreafico C, Sutrisno A. Artificial Intelligence Assisted Social Failure Mode and Effect Analysis (FMEA) for Sustainable Product Design. Sustainability 2023;15:8678. https://doi.org/10.3390/su15118678.

[19] Wang Z, Du H, Tao L, Javed SA. Risk assessment in machine learning enhanced failure mode and effects analysis. Data Technologies and Applications 2024;58:95–112. https://doi.org/10.1108/DTA-06-2022-0232.

[20] Peddi S, Lanka K, Gopal P. Modified FMEA using machine learning for food supply chain. Mater Today Proc 2023. https://doi.org/10.1016/j.matpr.2023.04.353.

[21] Chang K-H. Integrating Subjective–Objective Weights Consideration and a Combined Compromise Solution Method for Handling Supplier Selection Issues. Systems 2023; 11:74. https://doi.org/10.3390/systems11020074.

[22] Akram M, Ullah I, Allahviranloo T, Shahriari M. An integrated weighted multi-criteria decision-making method using Z -number and its application in failure modes and effect analysis. Journal of Industrial Information Integration 2025;45:100805. https://doi.org/10.1016/j.jii.2025.100805.

[23] Chakhrit A, Guedri A, Chennoufi M. An integrated multi-criteria decision-making approach for the risk assessment in the automotive parts industry. International Journal of System Assurance Engineering and Management 2025; 16:765–84. https://doi.org/10.1007/s13198-024-02662-8.

[24] Sheshe F. An investigation into supply chain risk factors and their impact on performance of humanitarian pharmaceutical supply chain in Sub-Sahara Africa - A case study of the supply chain system for UNICEF Tanzania. Doctoral Thesis. Northumbria University, 2018.

[25] Kashav V, Garg CP. Fortifying humanitarian supply chains: evaluating sustainability enablers for strengthened resilience of humanitarian supply chains during calamities and pandemics. Journal of Humanitarian Logistics and Supply Chain Management 2025; 15:294–308. https://doi.org/10.1108/JHLSCM-04-2024-0050.

[26] Mohammed A, Al-Baqami A, Alshibani A, Hadidi LA, Ghaithan A, Al-Abbas A. An integrated gray relational analysis – FMEA approach for risk assessment of petrochemical projects during the design stage. Journal of Modelling in Management 2025:1–27. https://doi.org/10.1108/JM2-04-2025-0167.

[27] Khan AU, Ali Y. Analytical hierarchy process (ahp) and analytic network process methods and their applications: a twenty-year review from 2000-2019. International Journal of the Analytic Hierarchy Process 2020;12. https://doi.org/10.13033/ijahp.v12i3.822.

[28] Jin G, Meng Q, Feng W. Optimization of Logistics System with Fuzzy FMEA-AHP Methodology. Processes 2022;10:1973. https://doi.org/10.3390/pr10101973.

[29] Spreafico C, Russo D, Rizzi C. A state-of-the-art review of FMEA/FMECA including patents. Comput Sci Rev 2017;25:19–28. https://doi.org/10.1016/j.cosrev.2017.05.002.

[30] Zavadkas ED, Ghorabae MK, Deveci M, Antuceviciene J. Reviews on developments and appications of edas. Newsletter 14 of EWG ORSDCE 2023.

[31] Ranjan R, Rajak S, Chatterjee P, Kadry S. Evaluation Based on Distance from Average Solution (EDAS) Method. Bibliometric Analyses in Data‐Driven Decision‐Making, Wiley; 2025, p. 223–55. https://doi.org/10.1002/9781394302581.ch8.

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Published

2026-08-29

Issue

Vol. 8 No. 4 (2026): August-October

Section

Articles

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