Modeling the drivers of post-harvest losses - MCDM approach

Post-harvest losses (PHL) in India are significant and cause massive economic deficit. The reduction of PHL can help achieve sustainability in balancing economic, social, and environmental dimensions. The objective of this research article is to identify the crucial causal factors of PHL in the fruits and vegetables (F&V) supply chain in the Indian context. From the exhaustive literature review and expert opinions, sixteen causal factors were identified, and the analytic hierarchy process (AHP) was applied to ascertain the relative importance of these factors on a comparative basis. The developed model highlighted the most critical factors that should be prioritized for progressive PHL reduction. The top three significant causal factors are lack of linkages between institution, industry, and Government (F8) with an intensity of 0.164313, climate and weather conditions (F15) with a magnitude of 0.103817, and lack of linkages in the marketing channel, from farm gate to the market because of small land sizing fanners (F9) with a value of 0.101895. In future studies, for improving the accuracy and reliability of the developed model, other Multi-Criteria Decision Making (MCDM) tools may be employed along with the AHP. Also, for validation purpose, the Structural Equation Modeling (SEM) methodology, which is a statistical approach, may be applied. The proposed model is intended to guide various supply chain members and decision-makers for reducing PHL and improving the performance of the F&V supply chain