Hierarchical Causal Mapping and Prioritisation of Post-Harvest Fish Losses Risk in Aquaculture Supply Chain Using an Integrated FDM-Fdematel

Post-Harvest Fish Losses (PHFL) remain a significant constraint in the aquaculture supply chain, where rapid quality deterioration can reduce the value and availability of food, especially in tropical contexts such as Indonesia. Prior PHFL research is dominated by capture-fisheries studies and primarily descriptive evidence, leaving aquaculture-specific, multi-echelon causal mechanisms, particularly those related to processing capabilities and supporting infrastructure, that are not sufficiently prioritized. This study develops a causal mapping and prioritization framework for PHFL risk factors for a sustainable aquaculture supply chain using an integrated Fuzzy Delphi Method (FDM) and Fuzzy Decision -Making Trial and Evaluation Laboratory (FDEMATEL) approach. Judgments from 23 experts representing four echelons (farmers, intermediaries, processors, retailers/consumers) were elicited to screen and structure risks under uncertainty. FDM retained 17 key risk factors from 30 candidates. FDEMATEL then produced a prioritized causal structure, in which inadequate harvesting techniques and equipment (RF17), limited cold-chain availability (RF21), and inadequate handling techniques and equipment (RF18) emerge as the strongest causal drivers, shaping downstream outcomes related to safety, storage, and market performance. Theoretically, the study contributes a two-level (hierarchical) causal architecture (aspect and risk-factor levels) that moves beyond determinant lists to explain propagation pathways. Managerially, this provides evidence-based priorities for interventions in initial handling capabilities, cold chain continuity, and IT coordination/integration to guide investment and policy decisions for reducing PHFL in the aquaculture supply chain in Indonesia.