Research on significant factors affecting adoption of blockchain technology for enterprise distributed applications based on integrated MCDM FCEM-MULTIMOORA-FG method

Abstract

Blockchain technology-powered applications infuse trust in the system without intermediary entities. Researchers’ interest in blockchain technology has increased dramatically in recent years as a result of this distinguishing feature. However, the adoption of this novel paradigm in enterprise distributed applications is not very encouraging. To adopt a new technology in an industry, managers and technocrats have to do multiple-criteria decision-making (MCDM) in a fuzzy environment. The aim of this study is to propose a system model for the identification and monitoring of significant factors responsible for the slow adoption rate of blockchain technology. In this research, the MULTIMOORA method for group decision-making, a popular MCDM approach, has been further extended by integrating the information entropy weight–fuzzy comprehensive evaluation model (IEW-FCEM) for an uncertain environment. The proposed method of FCEM-MULTIMOORA-FG combines the benefits of four best-in-class ranking methods, namely, the fuzzy ratio system, the fuzzy reference point method, the fuzzy full multiplicative form, and the IEW-FCEM. The idea behind integrating the IEW-FCEM with MULTIMOORA-FG is that information entropy will derive the objective weights of the criteria, thus removing the dependency upon subject matter expert experience only. An empirical study demonstrates the efficacy and practicability of the FCEM-MULTIMOORA-FG method. The simulation results demonstrate that the proposed method is computationally straightforward with better position accuracy than previous algorithms and that its basic idea is logical and understandable, making it easier to apply in a computer system. Additionally, a comparative analysis with five more MCDM methods was executed to validate the results.