Development of the Range of Value (ROV) Method Based on Dynamic Weighting for Decision Support Systems
Decision-making in complex environments requires an evaluation framework capable of integrating multiple criteria with different levels of importance and performance. This study proposes Dynamic-ROV, a modified Rank Order Value approach designed to evaluate alternatives through data-driven criterion weighting and utility-based assessment. The proposed procedure consists of decision matrix normalization, standard deviation-based criterion weighting, best and worst utility evaluation, final utility calculation, and ranking. The approach was applied to the selection of nine manager candidates using seven evaluation criteria. Its robustness was assessed through 28 sensitivity scenarios involving positive and negative changes in individual criterion weights, while its ranking consistency was further examined against SAW, MOORA, GRA, and SMART. The results show that Candidate M-02 achieves the highest final utility value of 0.3862 and obtains the first rank, whereas Candidate M-08 records the lowest utility value of 0.1179 and ranks ninth. The sensitivity analysis indicates that the principal ranking structure remains stable across all tested scenarios, with M-02 consistently occupying the first position and M-08 remaining in the last position. Comparative evaluation also demonstrates that Dynamic-ROV produces ranking patterns that are broadly consistent with the established MCDM methods. These findings indicate that Dynamic-ROV provides a reliable and stable framework for multi-criteria evaluation while offering a data-oriented mechanism for determining criterion importance and assessing alternative performance. The proposed approach can therefore serve as an alternative decision-support method for selection problems in organizational settings.
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Copyright (c) 2026 Erlin Windia Ambarsari, Muhammad Waqas Arshad, Gustian Rama Putra, Yuwan Jumaryadi, Febryo Ponco Sulistyo (Author)
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