Exploring the potential of blockchain for traceability in supply chain: a hybrid simulation approach

Abstract

While the scientific literature on blockchain applications in supply chain management is vast, it is short of empirical evidence due to the novelty of the technology and the inherent complexity of implementing such systems. In situations where empirical evidence is lacking or difficult to gather, modeling and simulation serve as effective tools for capturing the complexities of supply chain networks. This allows for a thorough examination and understanding of these systems, facilitating informed and consistent decision-making. Consequently, potential advantages and risks can be identified prior to their implementation in the real world. However, guidelines to assist scholars and practitioners in creating realistic hybrid simulation models in this context are missing in the literature, which brings great complexity to the modeling process. Thus, the main objective of this work is to propose and test a framework to support the modeling and simulation of supply chain traceability considering blockchain technology. The framework comprises a step-by-step guide that embraces the phases of model design, model development, and output evaluation. In addition, to enhance understanding and adoption, this research incorporates concepts and terminologies from existing and well-established frameworks for both practitioners and scholars, namely SCOR, GTS, and ADACOR. Furthermore, it employs a hybrid modeling approach that combines principles and methods from agent-based modeling and discrete-event simulation paradigms. To accomplish this objective, this work is deployed in three parts. First, to deal with a large publication rate of works related to blockchain in supply chain management, a review of reviews is developed, which is a tertiary study that gathers evidence from literature reviews. Secondly, following the Design Science Research approach, a novel methodological framework is proposed to help build hybrid simulation models of different levels of granularity. Finally, to demonstrate its potential, the proposed methodological framework is applied to a real-scale industrial case in Canada, comprising a live lobster supply chain to identify the potential impacts of a blockchain-based traceability system on the physical supply chain network structure through the lens of network theory, considering single and multi-level supplier evaluation.