Systematic assessment of food traceability information loss: A case study of the Bangladesh export shrimp supply chain

Traceability information systems in food supply chains (FSCs) can suffer from information loss, and this can cause food safety crises and economic downturns around the world. Information loss happens as a result of inefficiencies in material and information flows caused by the vulnerabilities associated with either the internal traceability systems of individual FSC operators and/or external traceability systems between them. A structured comprehensive approach to identify and analyse these vulnerabilities in an entire FSC encompassing both of its internal and external traceability systems is still absent in the literature. This paper develops a systematic information loss assessment technique, modifying and integrating Failure mode effect and criticality analysis (FMECA) and a traceability modelling tool, Material and information flow modelling technique (MIFMT). To demonstrate the proposed method, the study uses data derived from a primary case study on Bangladesh export shrimp supply chain comprising a farm, a depot and a processor. Providing standardised visualisation and quantitative information loss evaluation, the proposed method offers a systematic approach for analysing vulnerabilities in the food traceability system. The results of this approach are used to make specific reengineering suggestions to improve the existing shrimp traceability system in Bangladesh. The proposed method could be applied widely in various FSCs to support systematic reengineering e.g. blockchain and IoT implementation in existing traceability systems.

Automated summary

Traceability information systems in food supply chains can suffer from information loss, resulting in food safety crises and economic downturns. A comprehensive approach to identify and analyze vulnerabilities in these systems is still lacking. This paper proposes a systematic information loss assessment technique, offering a systematic approach for analyzing vulnerabilities in the food traceability system.