A framework for modeling and simulating blockchain-based supply chain traceability systems

Abstract

Traceability improves supply chain operations transparency, benefiting the overall performance and the end customer perception. Blockchain technology is a promising alternative to create robust traceability systems, as it promotes trust and supports information sharing based on data immutability. Despite the hype surrounding blockchain technology and the vast literature in the field, the effectiveness and efficiency of blockchain-based supply chain traceability systems remain uncertain across multiple industry sectors, due to the lack of empirical evidence. Considering its characteristics, simulation is a valuable tool to evaluate the performance of supply chain management processes and technology alternatives. However, a structured guide to support the building process of simulation models regarding blockchain in the supply chain is still missing, making it hard for modelers to create realistic simulation models. Thus, this work proposes a novel methodological framework with guidelines to develop HS models regarding supply chain traceability capable of integrating the main blockchain concepts for managerial purposes. Scenarios with different granularity levels may be designed through the combination of both discrete-event and agent-based simulation paradigms. The proposed approach integrates concepts and terminologies from foundational references, including the Supply Chain Operations Reference (SCOR) model and the Global Traceability Standard (GTS). In addition, it is anchored on the ADACOR holonic architecture for the agentification process. Following the Design Science Research methodology, a proof-of-concept application is presented, based on a real-scale industrial case of a lobster supply chain from Canada. Results obtained reflect the framework's versatility to assist the development of a hybrid simulation model, as traceability is explored through the perspectives of time to react, item separation, temporal screening, and blockchain participation rate.