An adaptive and extensible framework to enhance end to end trustworthiness of traceability data
Oratile Leteane, Yirsaw Ayalew · 2022
In recent years, many traceability systems have been developed. These systems can capture traceability data from the first link to the last link of a supply chain, which makes the traceability of a product from the consumer to its origin possible. However, current traceability systems are less effective in providing traceability data that can be trusted. This research proposes a framework that leverages blockchain smart contracts and a trust model to improve traceability data's trustworthiness. The framework's use of multi-set trust metrics makes it adaptable to all supply chain links. Furthermore, the framework's extensibility feature is enhanced through the use of metric developers who continuously assess supply chain trust needs and avail relevant trust metric packages to address the needs. This makes the proposed traceability solution more relevant and effective even when trust requirements change. We demonstrate the applicability of the framework using the Botswana beef supply chain case study.