Analysis Model of Urban Rail Transit Service Quality Influencing Variable Factors Based on SEM

Abstract

Objective Aiming to further enhance urban rail transit service with precision, it is essential to quantitatively extract the influencing variable factors of urban rail transit service quality and analyze the intrinsic relationship between these variables. Method Exploratory factor analysis is employed to extract six common influencing factors. SEM (structural equation modeling) is then introduced to construct three confirmatory factor analysis models for the influencing variables. These models are validated using survey data. Result & Conclusion The results indicate that the first-order six-factor uncorrelated model does not fit the actual data. Both the first-order six-factor correlated model and the second-order factor model adequately reflect the relationship between factors, while the later shows a significantly higher goodness of fit，with an average goodness of fit increase by 4.50% in absolute fit index, 0.53% in incremental fit index, and 12.73% in parsimonious fit index. The second-order factor model effectively quantifies the contributions of the six factors to service quality.

Keywords

• urban rail transit
• service quality
• influencing variable
• structural equation model
• goodness of fit