Risk assessment of relief food delivery delays from a cross-disaster perspective

Yang, M, Qu, SJ, Qu, Z, Dubey, R ORCID: 0000-0002-3913-030X, Zhao, G, Mohsendokht, M, Ji, Y and Yang, Z Risk assessment of relief food delivery delays from a cross-disaster perspective. international Journal of Production Economics. (Accepted)

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Abstract

Delays in relief food delivery critically threaten post-disaster survival, yet existing studies lack a systematic approach to identifying and assessing these risk factors across different disaster contexts. Focusing on floods and storms, this study develops a two-stage risk analysis framework tailored to relief food delivery delay risks across disaster contexts. Using multi-source real-world data and grounded theory, it identifies 24 risk factors, including previously overlooked institutional political risks such as geopolitical conflicts, political considerations, and bureaucratic approval redundancy. Methodologically, this study integrates failure mode and effect analysis (FMEA), a belief-rule-based Bayesian network, and evidential reasoning to assess and prioritise risks, while employing spherical fuzzy set-based social network analysis and the best-worst method to determine expert and risk factor weights. The results show that the key risk factors differ between disaster types: bureaucratic approval redundancy, traffic paralysis, and concentrated warehouse distribution dominate in floods; severe weather, bureaucratic approval redundancy, and communication infrastructure breakdown prevail in storms. This study contributes to delay risk assessment by applying an integrated FMEA–BBN–ER framework to the underexplored context of relief food delivery under floods and storms, while refining its weighting architecture through combined background–SFS–SNA expert weighting and BWM-based risk factor weighting to account for expert and risk factor heterogeneity. It further provides disaster-specific insights by cautiously interpreting how contextual factors, including governance capacity, institutional settings, and cultural value orientations, may help explain these differences and inform targeted mitigation strategies.

Item Type:	Article
Uncontrolled Keywords:	Operations Research
Subjects:	H Social Sciences > HF Commerce > HF5001 Business H Social Sciences > H Social Sciences (General) H Social Sciences > HF Commerce > HF5001 Business > HF5410 Marketing. Distribution of Products
Divisions:	Liverpool Business School
Date of acceptance:	21 August 2026
Date Deposited:	21 Aug 2026 13:58
Last Modified:	21 Aug 2026 13:58
URI:	https://researchonline.ljmu.ac.uk/id/eprint/29180

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