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A model ISM-MICMAC for managing risk in agri-food supply chain: An investigation from the Andean region of Peru

  • Edgar Ramos
  • , Timothy J. Pettit
  • , Mamun Habib
  • , Melissa Chavez
  • National University, San Diego
  • Independent University, Bangladesh
  • Universidad Nacional de Ingeniería, Peru

Research output: Contribution to journal › Article › peer-review

27 Scopus citations

Abstract

During recent years, supply chain risks have gained importance in the food supply chain. This study presents a methodology to analyse the risk in the agri-food supply chain belonging to the Andean region in Peru. It utilises the interpretive structural modelling (ISM) with matrice d' impacts croises multiplication appliqué an classement (cross-impact matrix multiplication applied to classification, abbreviated as MICMAC) to identify and understand relationships between risk types. Based on the empirical data collected from the food industry experts, ten risk factors were identified as relevant. Finally, the identified risks were classified using ISM-MICMAC methodology. The research findings demonstrated that natural disaster, environmental, and legal risks were the most substantial. The findings highlight that selected methods are capable of recognising the most substantial risks that are most critical to assess, manage with adequate mitigation actions from the practitioners in the agri-food industry.

Original languageEnglish
Pages (from-to)62-85
Number of pages24
JournalInternational Journal of Value Chain Management
Volume12
Issue number1
DOIs
StatePublished - 2021

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 2 - Zero Hunger
    SDG 2 Zero Hunger

Keywords

  • Agri-food supply chain
  • ISM
  • Interpretive structural modelling
  • MICMAC
  • Matrice d' impacts croises multiplication appliqué an classement
  • Peru
  • Risk management
  • Supply chain

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