The Evaluation Method of Electric Scooter Design Solutions

Abstract

To tackle the challenges of uncertainty and subjectivity in evaluating electric scooter modeling schemes, this study introduces an innovative decision-making framework that integrates the Social Network Analysis-Group Decision Making (SNA-GDM) model with the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method. Initially, a comprehensive evaluation index system is established, followed by the determination of index weights to facilitate the selection of the optimal scheme. Analysis of practical cases demonstrates the proposed approach's ability to overcome the inherent limitations of traditional evaluation techniques. The validation of the optimal electric scooter modeling scheme provides valuable insights for future research, development, and design endeavors in this field. The integrated evaluation method, which combines SNA, GDM, and TOPSIS, exhibits significant advantages and practical applicability. By addressing the drawbacks of the conventional TOPSIS method, such as data sensitivity and subjectivity, and enhancing the objectivity and accuracy of the expert group evaluation through the introduction of the SNA-GDM model and consensus adjustment mechanism, this method represents a substantial improvement in the evaluation of electric scooter modeling schemes.