Sustainability risk assessment of blockchain adoption in sustainable supply chain: An integrated method. (September 2022)

• Record Type: Journal Article
• Authors: Zhang, Fang; Song, Wenyan
• Is Part Of: Computers & industrial engineering. Volume 171(2022)
• Publication Date: 2022-09
• Subjects: Sustainability risk assessment -- Blockchain technology -- Sustainable supply chain -- Variable precision rough set -- Best-Worst Method; Engineering -- Data processing -- Periodicals; Industrial engineering -- Periodicals; 620.00285
• DOI: 10.1016/j.cie.2022.108378
• Languages: English
• ISSNs: 0360-8352

Abstract

Highlights: A new method for risk analysis of blockchain-based sustainable SCM is proposed. A new topic of risk factors in adopting blockchain technology in SSCM is tackled. The method considers severity, occurrence, detection and response of risk factors. The method flexibly handles vague information with variable precision rough set theory. Abstract: Blockchain technology improves the transparency and traceability of sustainable supply chain management (SSCM). The merits of introducing blockchain technology are fully discussed. However, the potential sustainability risks of introducing blockchain technology to SSCM, such as excessive energy consumption and additional operating training costs, are less considered. This paper aims to ascertain and evaluate the sustainability risk factors of applying blockchain technology to SSCM. Based on the triple bottom line, the risk factors are grouped into three categories, i.e., environmental risk factors, economic risk factors, and social risk factors. This paper proposes a comprehensive risk evaluation framework for adopting blockchain to SSCM considering severity (S), occurrence (O), detection (D), and response(R) of risk factors. Then, a new risk analysis method is developed. The proposed new approach integrates the strength of Best-Worst Method (BWM) in reducing the decision makers' burden of pairwise comparisons of risk criteria importance, and the merit of rough Combined Compromise Solution method (CoCoSo) in flexibly handling incomplete and vague information without much priori information, which makes the results of risk analysis more accurate. The results demonstrate that increased training costs, and resource waste due to repeated audits and certifications are the two most prominent risk factors. These findings give practitioners managerial insights on blockchain technology application in SSCM.