Work

A Fuzzy Failure Mode and Effects Analysis with Cumulative Prospect Theory for Reverse Cold Chain Risk Assessment

Year: 2026

Type: article

Abstract: The cold supply chain (CSC) reverse logistics segment remains underexplored in the risk assessment literature. Existing frameworks apply traditional failure mode and effects analysis (FMEA) with a three-criterion structure (severity, occurrence, detectability), which inadequately captures the time-sensitive and cost-intensive risk environment of CSC reverse logistics. This study proposes an integrated framework combining hazard analysis and critical control points (HACCP)-based node partitioning, an extended five-criterion FMEA incorporating timeliness and economic cost, triangular interval-valued fuzzy number (TIVFN) aggregation via the Aczél–Alsina operator, and cumulative prospect theory (CPT) to prioritize risk modes. Applied to a food-sector reverse CSC, 16 failure modes were identified across six HACCP-based process nodes. Severity and economic cost jointly account for 47.5% of total criterion weight. Monitoring and data management (node P6) consistently emerge as the dominant risk cluster, with data completeness (FM14), sensor accuracy (FM15), and early-warning functionality (FM16) occupying the top three positions across all weight scenarios. Relative to conventional models and the extended RPN, the TIVFN-CPT model assigns FM16 a substantially higher priority, demonstrating that CPT captures asymmetric, loss-averse risk perception that conventional methods fail to encode. Sensitivity analysis across five weight scenarios confirms the structural robustness of the rankings. By extending FMEA to a five-criterion behavioral framework and introducing TIVFNs as an uncertainty-preserving linguistic scale, this study indicates that information quality constitutes a risk factor of comparable priority to physical temperature maintenance, supporting a tiered resource allocation strategy that prioritizes investment at node P6 and targeted upgrades at nodes P1 and P4.

Source: Processes

DOI: 10.3390/pr14182880

Authors: Hsiang-Yue Chen, Xin-Yi Xu, Kai-Ying Chen, James J. H. Liou

Institution: National Taipei University of Technology

Language: English

Topic: Multi-Criteria Decision Making

Subfield: Management Science and Operations Research

Field: Decision Sciences

Domain: Social Sciences

SDG: Responsible consumption and production

Open Access status: gold

Estimated APC paid: $2,896