Modeling the Causes of Post-harvest Loss in the Agri-Food Supply Chain to Achieve Sustainable Development Goals: An ISM Approach

In emerging economies like India, wastage along the Agri-Food chain is a huge challenge. Thus, it becomes imperative to analyze the causes of post-harvest losses. This study aims to identify the causes of wastage in Agri-Food, as well as the interaction among the causes. The driving and dependence power of every cause of wastage, as well as their level of importance, has been analyzed. Interpretive structural modeling (ISM) has been utilized for obtaining driving and dependence power and establishing the interrelationship among causes. Matrix cross multiplication and classification (MICMAC) has been applied for clustering the causes into four groups. Thirteen causes of Agri-Food wastage in the Indian context have been analyzed by applying ISM and MICMAC. The study shows that poor logistics infrastructure, large numbers of intermediates, and lack of innovative technology are the most influential causes for PHL in Indian Agri-Food supply chain. Reducing wastage in the Agri-Food supply chain in emerging economies countries like India may get big boosts in their economy as well as to achieve sustainable development goals (like zero hunger, sustainable cities, etc.). Food wastage is linked with a huge amount of environmental emission so reducing wastage will help in achieving SDG like livable land, sustainable cities, zero hunger, etc. This work may be utilized by supply chain practitioners, decision-makers, and policymakers in reduction of Agri-Food wastage.