Hybrid Multi-Criteria Decision Making Methods: Combination of Preference Selection Index Method with Faire Un Choix Adèquat, Root Assessment Method, and Proximity Indexed Value
Received: 11 October 2024 | Revised: 30 October 2024 | Accepted: 9 November 2024 | Online: 25 November 2024
Corresponding author: Nguyen Trong Mai
Abstract
This study presents an investigation into the hybridization of Multiple Criteria Decision Making (MCDM) methods. The Preference Selection Index (PSI) method is used in two distinct ways: first, for its traditional purpose of ranking alternatives, and second, to calculate criteria weights. These criteria weights are utilized to rank the alternatives provided by other MCDM methods, including the Faire Un Choix Adéquat (FUCA), Root Assessment Method (RAM), and Proximity Indexed Value (PIV), resulting in the creation of three hybrid models: FUCA-PSI, RAM-PSI, and PIV-PSI. The effectiveness of these hybrid approaches is tested by ranking 20 Vietnamese cities based on their digital transformation efforts. The results demonstrate that the hybrid approaches produce a highly correlated ranking, as evidenced by the Spearman rank correlation coefficient found among these methods, with the lowest being 0.8571. Both the PSI method and the three hybrid models identified the same top alternative, confirming the reliability and accuracy of the rankings.
Keywords:
hybrid models, MCDM methods, PSI, FUCA, RAM, PIV, digital transformationDownloads
References
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