Adaptive Utility Ranking Algorithm for Evaluating Blockchain-Enabled Microfinance in Emerging - A New MCDM Perspective

Abstract

Blockchain integration in microfinance is beginning to reshape the scenario of financial inclusion and economic empowerment in emerging markets. To support a strategic decision on adoption, the study introduces the Adaptive Utility Ranking Algorithm (AURA), a newly established Multi-Criteria Decision-Making (MCDM) method to be used in evaluating blockchain-based alternatives relevant to microfinance in Malaysia. AURA stands apart from traditional MCDM techniques in that it has a distance function that is flexible and a normalization scheme that is dynamic by nature, thereby making it capable of offering the decision maker more leverage in terms of adaptability to actual economic conditions. For demonstrating the methodology, a simulated dataset based on eight blockchain-modeled alternatives and six criteria considered important in economic performance was constructed. These criteria were used for sensitivity analysis; the application of comparative evaluation of well-known MCDM methods such as TOPSIS, VIKOR, and COBRA; and robustness checks with the simulation methodology, all of which helped attest to the reliability of AURA. Even though it was based on synthetic data, the study has provided strong conceptual insight into the possibility of financial institutions being able to prioritize options from the technology perspective under complex economic constraints. Portraying AURA as a competitive decision-support tool for technology evaluation in microfinance will certainly make an impact.