This study addresses a benchmarking challenge in operations management: integrating qualitative and quantitative data for supplier benchmarking in state-owned hydropower enterprises (SOEs). Existing multi-criteria decision-making (MCDM) approaches rely on single-weighting methods and target supplier selection rather than benchmarking, which limits their effectiveness for performance measurement and supplier development.
A five-stage hybrid benchmarking framework integrates the best–worst method (BWM) for expert-driven subjective weighting, the entropy method for objective weighting, game-theoretic combination weighting for optimal synthesis and Fuzzy TOPSIS for supplier ranking under uncertainty. The framework is validated using data from a large Chinese state-owned hydropower enterprise, evaluating eight suppliers across 16 criteria using Delphi consultation.
Quality management is the dominant criterion (BWM weight = 0.4315), followed by delivery and service capability (0.2850) and ESG criteria (0.1988). Game-theoretic combination weighting achieves 100% ranking consistency and exhibits 47.9% greater discrimination power than AHP-TOPSIS. S3 is identified as the benchmark supplier (CC = 0.8523) and S8 as the lowest performer (CC = 0.4688), with a 0.3835 performance gap. The framework enables targeted interventions through supplier stratification.
This study contributes to benchmarking literature by (1) developing a hybrid methodology bridging qualitative and quantitative evaluation through game-theoretic weighting; (2) reframing supplier evaluation as a benchmarking capability – identifying benchmark suppliers, quantifying performance gaps and establishing improvement targets – linked to procurement governance and (3) providing a validated benchmarking tool for procurement in state-owned enterprises, incorporating governance criteria for Chinese SOE reform.
