Data Normalization in RAWEC Method: Limitations and Remedies

Abstract

Multi-Criteria Decision Making (MCDM) methods play a significant role in evaluating and comparing options based on various criteria, helping optimize decisions in complex situations. They enhance transparency and fairness in the decision-making process while minimizing risks and optimizing decision performance. Ranking of Alternatives with Weights of Criterion (RAWEC) is a MCDM method recently proposed in early 2024. Its advantage lies in the minimal steps required for implementation. Simultaneously employing two data normalization approaches is also a distinctive feature of RAWEC compared to most other MCDM methods. However, if there is at least one zero element in the decision matrix, the normalization method using available data in RAWEC cannot be utilized. This study aims to address these limitations. Investigating the suitability of data normalization methods when combined with the RAWEC method has been conducted in various scenarios. The results of this study have addressed the limitations of the RAWEC method. Specifically, an alternative normalization method has been identified as suitable to replace the normalization method using available data in RAWEC when there is at least one zero element in the decision matrix.