Development of a hybrid fresh food supply chain risk assessment model. Issue 14 (18th July 2017)

• Record Type: Journal Article
• Authors: Nakandala, Dilupa; Lau, Henry; Zhao, Li
• Is Part Of: International journal of production research. Volume 55:Issue 14(2017)
• Page Start: 4180
• Page End: 4195
• Publication Date: 2017-07-18
• Subjects: supply chain risk management -- fuzzy logic -- risk analysis -- fresh food supply chain -- risk assessment; Factory management -- Periodicals; 658.57
• DOI: 10.1080/00207543.2016.1267413
• Languages: English
• ISSNs: 0020-7543

Abstract

Abstract : Supply chain managers and scholars recognise the importance of managing supply chain risk, especially in fresh food supply chain due to the perishable nature and short life cycle of products. Supply chain risk management consists of supply chain risk assessment, risk evaluation and formulation and implementation of effective risk response strategies. The commonly adopted qualitative methods such as risk assessment matrix to determine the level of risk have limitations. This paper proposes a hybrid model comprising both fuzzy logic (FL) and hierarchical holographic modelling (HHM) techniques where risk is first identified by the HHM method and then assessed using both qualitative risk assessment model (named risk filtering, ranking and management Framework) and fuzzy-based risk assessment method (named FL approach). The risk assessment results by the two different approaches are compared, and the overall risk level of each risk is calculated using the Root Mean Square calculation before identifying response strategies. This novel approach takes advantage of the benefits of both techniques and offsets their drawbacks in certain aspects. A case study in a fresh food supply chain company has been conducted in order to validate the proposed integrated approach on the feasibility of its functionality in a real environment.