A profit maximization approach for organic short food supply chains

Abstract

Demand for organic food is rapidly increasing. This is despite several constraints in the process of producing organic foods. Producers should aim to maximize their profit by catering to the rising demand of this niche market. Manufacturing cost per unit is comparatively higher in the organic chain compared to the conventional chain. Hence, producers must make critical decisions when supplying their products to different markets. A Python-based Linear Programming optimization model tested using Google optimization Tools has been developed to identify the optimum delivery volume that should be supplied to each market which has been identified in this empirical study. The designed model aims to maximize profits by minimizing unsold products and postharvest waste. The developed model can guide producers who operate in the organic perishable supply chain to gain market benefits in short food supply chains. There is a lack of research on sustainability aspects in agricultural coordination and applications in supply network performance. Therefore, this study fills this gap by addressing the issue of postharvest waste in the distribution process of organic vegetables and fruits. The model can be extended into other product variants to validate the model’s applicability under different market scenarios.