Earticle

초록

영어

Modern businesses increasingly depend on large and continuously growing volumes of data to inform strategic decision-making. However, the rapid pace of data generation presents significant challenges for traditional analytical methods to remain timely and effective. This has led to a growing need for AI-based Decision Support System (AI-DSS) to assist business management processes. The effectiveness of an AI-DSS extends beyond its technical capabilities; it also depends on alignment with business goals, ease of use, and its support for ethical and responsible decision-making. This paper evaluates and compares AI-DSS tools within business contexts using Multi-Criteria Decision-Making (MCDM) frameworks. They have been reliably used in selecting systems tailored to given priorities. The proposed MCDM framework considers key evaluation dimensions, including technical performance, strategic compatibility, usability, cost-effectiveness and other factors. By integrating these factors, the study offers a systematic approach to help organizations make more informed and context-sensitive decisions when selecting AI-DSS tools.

목차

Abstract
Introduction
Literature review
Methodology
3.1 Phase I: FAHP-Based Criteria Weighting
3.2 Phase II: Ranking AIDSS Tools Using TOPSIS
Results
4.1 Fuzzy AHP Results for Criteria Weighting
4.2 TOPSIS Results for AIDSS Tools Ranking
Conclusion
References

저자

• Yusupova Fotima Javlon kizi [ Interdisciplinary Program of Digital Future Convergence, Chonnam National University ]
• Park, So Ra [ Collage of Business Administration, Chonnam National University ]

참고문헌