Measuring agri-food supply chain performance: insights from the Peruvian kiwicha industry

Abstract

Purpose: Agri-food firms face many challenges when assessing and managing their performance. The purpose of this research is to determine important factors for an integrated agri-food supply chain performance measurement system. Design/methodology/approach: This research uses the Peruvian kiwicha supply chain as a meaningful context to examine critical factors affecting agri-food supply chain performance. The research uses interpretative structural modelling (ISM) with fuzzy MICMAC methods to suggest a hierarchical performance measurement model. Findings: The resulting kiwicha supply chain performance management model provides insights for managers and academic theory regarding managing competing priorities within the agri-food supply chain. Originality/value: The model developed in this research has been validated by cooperative kiwicha associations based in Puno, Peru, and further refined by experts. Moreover, the results obtained through ISM and fuzzy MICMAC methods could help decision-makers from any agri-food supply chain focus on achieving high operational performance by integrating key performance measurement factors.