Robust framework to prioritize blockchain-based supply chain challenges: the fuzzy best-worst approach for multiple criteria decision-making

Abstract

Purpose

This study aims to identify and prioritize the challenges to adopting blockchain in supply chain management and to make its taxonomic model. Moreover, validate whether these challenging factors exist in the real world and, if they exist, then in what percentage.

Design/methodology/approach

This research adopted the fuzzy best-worst method (F-BWM), which integrates fuzzy set theory with the best-worst method to identify and prioritize the prominent challenges of the blockchain-based supply chain by developing a weighted multi-criteria model.

Findings

A total of 20 challenges (CH's) were identified. Lack of storage capacity/scalability and lack of data privacy challenges were found as key challenges. The findings of this study will provide a robust framework of the challenges that will assist academic researchers and industry practitioners in considering the most significant category concerning their working area.

Practical implications

Blockchain provides the best solution for tracing and tracking where RFID has not succeeded. It can improve quality management in a supply chain network by improving standards and speeding up operations. For inventory management, blockchain provides transparency of documentation for both parties within no time.

Originality/value

To the best of the authors' knowledge, no previous research has adopted the fuzzy best-worst method to prioritize the identified challenges of blockchain implementation in the supply chain. Moreover, no study provides a taxonomic model for the challenges of implementing a blockchain-based supply chain.

Citation

Shoaib, M., Zhang, S., Ali, H., Akbar, M.A., Hamza, M. and Rehman, W.U. (2024), "Robust framework to prioritize blockchain-based supply chain challenges: the fuzzy best-worst approach for multiple criteria decision-making", Kybernetes, Vol. 53 No. 10, pp. 3326-3347. https://doi.org/10.1108/K-01-2023-0046