@article{article_1691115, title={A Novel Approach to Objective Criterion Weighting: Extended Statistical Variance Procedure (ESVP)}, journal={Gazi Üniversitesi Fen Bilimleri Dergisi Part C: Tasarım ve Teknoloji}, volume={13}, pages={932–954}, year={2025}, DOI={10.29109/gujsc.1691115}, author={Altıntaş, Furkan Fahri}, keywords={Varyans, IVP, ESVP, İçsel Dağılım, Dışsal Dağılım}, abstract={This study proposes the Extended Statistical Variance Procedure (ESVP) method to introduce a new perspective to criterion weighting processes. To address the limitations of the traditional SVP method, which focuses solely on the internal variations of criteria, the proposed method comprehensively examines the contrasts among criteria and their contributions to decision-making processes. In this context, criterion weights are calculated through a mathematical model that integrates the internal distribution of each criterion with the effects of its contrasts with other criteria. The effectiveness of the method has been tested through analyses focusing on sensitivity, reliability, and robustness. When compared to other widely used weighting methods such as ENTROPY, CRITIC, SVP, SD, and MEREC, the ESVP method demonstrated high correlations with these methods and superior performance. The Simulation analyses further validated the stability of the method under varying scenarios, revealing that the variances of criterion weights remained homogeneous. Moreover, the method’s sensitivity to zero and negative values, computational comprehensiveness, and its ability to evaluate contrasts among criteria to strengthen decision-making processes provide distinct advantages over other approaches in the literature. In conclusion, the ESVP method is considered an effective and reliable tool for decision-makers in multi-criteria decision-making problems that require criterion weighting.}, number={3}, publisher={Gazi Üniversitesi}