Modeling volunteers’ participation in public cultural services: A motivation–behavior–performance framework using SEM and ANN

Volunteers constitute a vital force in advancing the socialization of public cultural services. This study examines the relationships among motivation, behavior, and performance in volunteers’ participation in public cultural services from an integrated perspective, with the aim of promoting more effective engagement. Drawing on self-determination theory and social support theory, a conceptual model of motivation, behavior, and performance was developed and tested using second-order Partial Least Squares Structural Equation Modeling (PLS-SEM) based on questionnaire data collected from 290 volunteers engaged in public cultural service in China. The results indicate that introjected, identified, and integrated regulation each exert positive effects on specific types of support behaviors, while informational and emotional support significantly enhance volunteer service performance. In addition, the importance rankings derived from the artificial neural network (ANN) analysis were consistent with the structural equation modeling path results, supporting the robustness of the findings. Finally, practical recommendations are proposed to help managers enhance volunteer engagement and improve service effectiveness.