Knowledge-Driven Evaluation of Enterprise Service Capabilities

With the rapid evolution of smart logistics supply chains, collaborative management has become increasingly vital. To address the limitations of inaccurate enterprise service capability evaluation in this context, an improved Entropy Weight Method–Technique for Order Preference by Similarity to Ideal Solution (EWM-TOPSIS) is proposed. Using a case enterprise, a quantitative service capability evaluation model was developed based on supply chain collaboration. Comparative analysis shows the improved EWM-TOPSIS achieved a fitting coefficient of 0.977 and accuracy of 96.78%, with mean square error of 1.472 and root mean square error of 0.061—outperforming other methods. The evaluation was applied to a company, followed by improvement strategies, which were validated by its leadership. Results demonstrate that the improved EWM-TOPSIS enhances accuracy and practical value in enterprise service capability assessment. The proposed model and strategies provide a quantitative and theoretical basis for advancing supply chain service capability research.