A multi-dimensional evaluation model for power enterprise procurement performance based on fuzzy analytic hierarchy process and TOPSIS integration

基于模糊层次分析法和TOPSIS方法的电力企业采购绩效多维评价模型

阅读:1

Abstract

Power enterprises face unique procurement challenges, including grid reliability requirements, regulatory complexities, and long-term asset investment considerations that existing evaluation methods inadequately address. Traditional approaches suffer from three critical limitations: inability to handle linguistic uncertainty (consistency ratios often exceeding 0.15), failure to integrate power-specific criteria simultaneously, and lack of systematic frameworks for aggregating conflicting stakeholder objectives. This study develops a comprehensive multi-dimensional evaluation model by integrating Fuzzy Analytic Hierarchy Process (FAHP) and TOPSIS methodologies specifically tailored for power enterprise contexts. The proposed framework achieves 23% improved consistency ratios compared to traditional AHP methods while systematically addressing uncertainty in expert judgments. The model constructs a hierarchical evaluation system encompassing four primary dimensions: cost-benefit performance, quality management, supplier relationship management, and risk control. FAHP handles subjective expert judgments and linguistic uncertainties in weight determination, while TOPSIS provides robust ranking capabilities through distance-based proximity measures. Empirical validation through a large regional power enterprise case study demonstrates model effectiveness. Results show a comprehensive closeness coefficient of 0.6651, positioning the enterprise at the 73rd industry percentile with strengths in quality management and improvement opportunities in supplier relationship development. Multi-dimensional sensitivity analysis across five uncertainty sources confirms model robustness, with coefficient variations within ± 5.7% and 96.3% ranking stability. Cross-validation with three peer enterprises (closeness coefficients ranging 0.5834-0.7245) demonstrates 91.3% performance gap identification accuracy. The integrated framework provides enhanced analytical capabilities for strategic procurement decision-making and continuous improvement initiatives in power enterprises.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。