A Review of the Application of MCDM Methods in Business Analytics

Multi-Criteria Decision-Making (MCDM) techniques have become quite important in solving complex business decision-making problems that involve numerous conflicting criteria and uncertainty. This review provides a full discussion of theoretical backgrounds, methodological development, and practical implementation of MCDM within the framework of business analytics in marketing, finance and supply chain management, operations, human resource management, and strategic management. Classical methods such as AHP, ANP, TOPSIS, VIKOR, DEMATEL, COPRAS, Entropy, WASPAS, and MOORA have proved to be effective in prioritization, performance evaluation, and risk assessment. Hybrid structures that combine fuzzy logic, DEMATEL, ANP, and AI-based predictive analytics are additionally used to gain robustness, interpretability, and real-time decision support. The analysis identifies major methodological trends, gaps in the research, and uncharted areas and offers a systematic roadmap on which future research can be directed. These results emphasize the strategic importance of MCDM as a decision-support facilitator that incorporates ordered multi-criteria reasoning with data-driven evaluations that encourage transparency, resilience, and sustainability of managerial choices.