Abstract

This study explores the impact of interactive behaviour, relationship quality, and the external environment on the quality of urban public services, as well as their mechanisms of action. Correlation analysis (CA) was used to assess the relationships between variables, while a structural equation modelling (SEM) analysed the complex links among interactive behaviour, relationship quality, public service quality, and the external environment. Additionally, principal component analysis (PCA) and K-Means clustering techniques were applied to reveal intrinsic relationships between variables. The findings indicate that interactive behaviour indirectly enhances public service quality by improving relationship quality, with the external environment playing a significant moderating role in this process. The model fit indices (CFI, RMSEA, chi-square statistics) confirmed the model’s interpretability and consistency with the data. The innovation of this study lies in the integration of PCA and K-Means clustering into the SEM model, providing a more comprehensive framework for analysing variable relationships. This research offers a theoretical foundation and practical guidance for policymakers seeking to optimize public service management strategies, government departments aiming to strengthen cooperation, and scholars working to deepen related research.