ASSESSING DIGITAL TRANSFORMATION CAPABILITY EVALUATION OF LOGISTICS ENTERPRISES UTILIZING SPHERICAL FUZZY ALTERNATIVE RANKING ORDER METHOD ACCOUNTING FOR TWO-STEP NORMALIZATION APPROACH

Evaluating the Digital Transformation Capability (DTC) of logistics enterprises is crucial for informing policy support and guiding strategic decisions. To address the inherent uncertainties in evaluation process, this study propounds a novel hybrid evaluation framework within a spherical fuzzy (SF) environment. The framework integrates the Symmetry Point of Criterion (SPC), the Stepwise Weight Assessment Ratio Analysis (SWARA) model, and a Regret Theory (RT)-based Alternative Ranking Order Method accounting for two-step normalization (AROMAN). In the following, a new spherical fuzzy score function and Sugeno-Weber operators are introduced to ascertain expert weighting and information fusion. This integrated methodology is empirically applied to assess and rank five logistics enterprises against twelve criteria, successfully identifying the top performer. Comprehensive sensitivity and comparative analyses confirm the proposed evaluation framework's robustness, practicality, and superiority over previous approaches.