An analytical approach for evaluating the impact of blockchain technology on sustainable supply chain performance

Nowadays, distributed ledger technologies (e.g., blockchain technology) can play significant roles in improving supply chain management and sustainability. Blockchain technology can support responsible sourcing and ensure compliance with environmental standards by boosting traceability and transparency in sustainable supply chains. Nevertheless, blockchain technology has not been widely applied in this field due to the lack of familiarity of managers with its intrinsic characteristics. This study investigates the performance improvement, arising from the blockchain implementation, to address the problem of managerial conservatism and this technology adoption. Accordingly, an analytical approach is proposed to identify blockchain technology adoption enablers and analyze their impact on supply chain performance. At first, the main enablers, derived from the literature review, are explored using network theory. The existing causal relationships between enablers are extracted based on a multi-expertise team members' agreement. Then, the fuzzy inference system is employed to determine the weights of relationships between the identified enablers and supply chain performance-related targets. After modeling the extracted causal relationships using the fuzzy cognitive map model, a scenario is defined for each enabler, and its impact on improving supply chain performance is estimated by implementing the hybrid learning algorithm. Finally, the obtained outputs are used to prioritize the blockchain technology adoption enablers using the fuzzy data envelopment analysis model. The result of this study implies that the blockchain technology can have a significant impact on mineral supply chain performance by creating smart contracts and enhancing environmental sustainability, traceability, and transparency.