Modeling the key factors leading to post-harvest loss and waste of fruits and vegetables in the agri-fresh produce supply chain

供应链 业务 多元化(营销策略) 生产(经济) 农业 农业科学 农业经济学 环境经济学 运营管理 环境科学 营销 工程类 经济 地理 宏观经济学 考古
作者
Santosh Anand,Mukesh Kumar Barua
出处
期刊:Computers and Electronics in Agriculture [Elsevier BV]
卷期号:198: 106936-106936 被引量:61
标识
DOI:10.1016/j.compag.2022.106936
摘要

Substantial quantities of agri-fresh produce especially fruits and vegetables are lost and wasted at various channels and operational levels in the agri-fresh produce supply chain. This post-harvest loss and waste (PHLW) create an imbalance in demand–supply of fruits and vegetable which hinders the provision of a healthy and nutritious diet for the people. This research article aims to develop a cause-effect model by identifying and analyzing the key factors under five major operational issues (Demand forecasting, Production planning, Transportation, Inventory, and Inefficient harvesting) that leads to post-harvest loss and waste of fruits and vegetables in the agri-fresh produce supply chains (AFPSCs) in developing economies, specifically India. The empirical study evaluates sixteen key factors and is further analyzed by using the fuzzy Decision-Making Trial and Evaluation of Laboratory (F-DEMATEL) technique to understand cause-effect relationships among factors and identify significant causal factors. The results revealed a lack of coordination between production, processing, and fresh market (PHLW6), lack of seasonal demand forecasting for non-producing regions (PHLW1), poor knowledge sharing about demand and supply (PHLW2), insufficient logistics in the catchment area (PHLW10), limited availability of cold chain facility (PHLW16), improper planting and sowing time duration (PHLW5), no change in mindsets for the diversification of crops (PHLW3), and lack of specialized vehicles (PHLW8) are the eight significant causal factors which have high influence to lead the post-harvest loss and waste of fruits and vegetables in the supply chain, that needs special attention. At last, the sensitivity analysis was performed to test the robustness of the result and decrease the biases in the decision-making process. The insights of this outcome will assist in forming policies and making an operational and strategic decision for the reduction of PHLW of fruits and vegetables in the agri-fresh produce supply chain to attain sustainable development goals.
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