A quantitative risk assessment methodology and evaluation of food supply chain

Abstract

Purpose

The food supply chain is exposed to severe environmental and social issues with serious economic consequences. The identification and assessment of risk involved in the food supply chain can help to overcome these challenges. In response, the purpose of this paper is to develop a risk assessment framework for a typical food supply chain.

Design/methodology/approach

An integrated methodology of grey analytical hierarchy process and grey technique for order preference by similarity to the ideal solution is proposed for developing a comprehensive risk index. The opinion of the experts is used to illustrate an application of the proposed methodology for the risk assessment of the food supply chain in India.

Findings

Valuable insights and recommendations are drawn from the results, which are helpful to the practitioners working at strategic and tactical levels in the food supply chain for minimising the supply chain disruptions.

Research limitations/implications

The risk quantification for the case organisation is primarily based on inputs collected from the experts working for Indian food supply chain, and so the generalisation of the results is limited to the context of developing countries. However, the generalisability of the proposed risk quantification methodology and key insights developed in the food supply chain will assist practitioners in policy making.

Practical implications

The risk priorities established by this research would enable an implementation of systematic risk mitigation strategies and deployment of necessary resources for leveraging the efficiency of food supply chain.

Originality/value

Specifically, this research has delivered a risk quantification framework and strengthened the inquiry of risk management for the food supply chain.

Citation

Rathore, R., Thakkar, J.J. and Jha, J.K. (2017), "A quantitative risk assessment methodology and evaluation of food supply chain", The International Journal of Logistics Management, Vol. 28 No. 4, pp. 1272-1293. https://doi.org/10.1108/IJLM-08-2016-0198