The impact of customer perceived value on relationship quality -- An empirical study of Home Inns based on SEM, SVM and SHAP value

This study examines the impact of customer perceived value on relationship quality using Ru Jia hotel customers in China. Using a mixed-method approach combining Structural Equation Modeling (SEM), Support Vector Machine (SVM), and SHAP value analysis, the results of the study indicate that customer perceived value (including price, quality, affective, and social dimensions) significantly improves relationship quality (satisfaction, trust, and commitment).SVM and SHAP analyses further indicate that affective value is the most critical driver of satisfaction, trust, and commitment. This research advocates prioritizing emotional engagement (e.g., personalized experiences) and social value (e.g., community building) to strengthen customer relationships. Future research should explore cross-industry applications, integrate dynamic models, and address cultural or technological influences to deepen actionable insights.