Measuring agri-food supply chain performance: insights from the Peruvian kiwicha industry
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Issue Date
2022-04-26
Metadata
Show full item recordPublisher
Emerald Group Holdings Ltd.Journal
BenchmarkingDOI
10.1108/BIJ-10-2020-0544Abstract
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.Type
info:eu-repo/semantics/articleRights
info:eu-repo/semantics/openAccessAttribution-NonCommercial-ShareAlike 4.0 International
Language
engISSN
14635771ae974a485f413a2113503eed53cd6c53
10.1108/BIJ-10-2020-0544
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- Creative Commons