No abstract

Blockchain is one of the innovative and disruptive technologies that has a wide range of applications in multiple industries beyond cryptocurrency. The widespread adoption of blockchain technology in various industries has shown its potential to solve challenging business problems, as well as the possibility to create new business models which can increase a firm's competitiveness. Due to the novelty of the technology, whereby many companies are still exploring potential use cases, and considering the complexity of blockchain technology, which may require huge changes to a company's existing systems and processes, it is important for companies to carefully evaluate suitable use cases and determine if blockchain technology is the best solution for their specific needs. This research aims to provide an evaluation framework that determines the important dimensions of blockchain suitability assessment by identifying the key determinants of suitable use cases in a business context. In this paper, a novel approach that utilizes both qualitative (Delphi method) and quantitative (fuzzy set theory) methods has been proposed to objectively account for the uncertainty associated with data collection and the vagueness of subjective judgments. This work started by scanning available literature to identify major suitability dimensions and collected a range of criteria, indicators, and factors that had been previously identified for related purposes. Expert opinions were then gathered using a questionnaire to rank the importance and relevance of these elements to suitability decisions. Subsequently, the data were analyzed and we proceeded to integrate multi-criteria group decision-making (MCGDM) and intuitionistic fuzzy set (IFS) theory. The findings demonstrated a high level of agreement among experts, with the model being extremely sensitive to variances in expert assessments. Furthermore, the results helped to refine and select the most relevant suitability determinants under three important dimensions: functional suitability of the use case, organizational applicability, and ecosystem readiness.