A novel group BWM approach to evaluate the implementation criteria of blockchain technology in the automotive industry supply chain

Abstract

The use of blockchain technology leads to improved operations and supply chain (SC) integration. Moreover, identifying and evaluating the blockchain technology application criteria in the logistics system is a Multi-Criteria Decision-Making (MCDM) challenge that requires taking into account the perspectives of experts with varying degrees of SC expertise. The purpose of this paper is to propose a novel group decision-making method based on the best-worst method (BWM) to evaluate the criteria of implementing blockchain technology in the SC. The proposed approach provides a mechanism whereby opinions of decision-makers (DMs) are aggregated in nine steps, first. Then, weights of criteria are determined using BWM individual decision-making models. Moreover, two individual decision-making methods called nonlinear goal programming based BWM II (NGPBWM II) and linear goal programming based BWM II (LGPBWM II) are extended in this study, which can be adopted in both individual and group decision-making problems. The NGPBWM II and LGPBWM II methods can be used for both individual and group decision-making. This study proposes a novel group decision-making framework. The framework has fewer constraints than previous group BWM models and can consider different best (worst) criteria by different DMs. The effectiveness of the proposed methodology is investigated employing eight numerical examples. The results reveal the high accuracy of the NGPBWM II in all eight examples. Therefore, a combination of the proposed group decision-making method and NGPBWM II is applied in a real case to evaluate the application criteria of the blockchain technology in the automotive industry SC, which was a new application for using blockchain technology in SC.