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Development of a hybrid fresh food supply chain risk assessment model

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  • Dilupa Nakandala
  • Henry Lau
  • Li Zhao

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.

Suggested Citation

  • Dilupa Nakandala & Henry Lau & Li Zhao, 2017. "Development of a hybrid fresh food supply chain risk assessment model," International Journal of Production Research, Taylor & Francis Journals, vol. 55(14), pages 4180-4195, July.
  • Handle: RePEc:taf:tprsxx:v:55:y:2017:i:14:p:4180-4195
    DOI: 10.1080/00207543.2016.1267413
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    Cited by:

    1. Kumar, Anish & Mangla, Sachin Kumar & Kumar, Pradeep & Song, Malin, 2021. "Mitigate risks in perishable food supply chains: Learning from COVID-19," Technological Forecasting and Social Change, Elsevier, vol. 166(C).
    2. Nishat Alam Choudhary & Shalabh Singh & Tobias Schoenherr & M. Ramkumar, 2023. "Risk assessment in supply chains: a state-of-the-art review of methodologies and their applications," Annals of Operations Research, Springer, vol. 322(2), pages 565-607, March.
    3. Guoquan Zhang & Guohao Li & Jing Peng, 2020. "Risk Assessment and Monitoring of Green Logistics for Fresh Produce Based on a Support Vector Machine," Sustainability, MDPI, vol. 12(18), pages 1-20, September.

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