Blockchain Service Provider Selection Based on an Integrated BWM-Entropy-TOPSIS Method Under an Intuitionistic Fuzzy Environment
Sen Liu, Yanan Hu, Xiao Zhang, Yanfeng Li, Ling Liu
Abstract
The emergence of blockchain technology has significantly changed the underlying infrastructure of existing information technology and will fundamentally affect the production modes of enterprises. However, because the application of blockchain is still in its infancy, it is difficult for an enterprise to develop a comprehensive assessment of various types of blockchain service providers in the market. Hence, enterprises need scientific decision tools to estimate which blockchain service provider is appropriate. However, few studies have focused on this phenomenon. Therefore, to address this challenge, this investigation proposes a novel integrated multi-attribute group decision-making (MAGDM) method to help enterprises estimate which blockchain vendor is more appropriate by considering more comprehensive influence factors. The proposed method is defined in an intuitionistic fuzzy environment and integrates entropy and the best-worst method (BWM) for comprehensive weighting of decision makers (DMs), subjective criteria and objective criteria in the decision-making process to make the decision results more reliable and reasonable. A numerical example and comparison are provided to illustrate the practicability and usefulness of the method. This study enriches the theory and methodology of blockchain technology and MAGDM analysis.