Research on Multidimensional Factors Impacting Willingness of Intelligent Customer Service Systems

In recent years, the advent of artificial intelligence and machine learning has led to a proliferation of intelligent customer service systems (ICSS). However, the extent to which users are willing to utilize these systems exhibits variability, which is influenced by a multitude of factors, including technology acceptance, user experience, and perceived trust. This study proposes a comprehensive model that integrates the Technology Acceptance Model (TAM), the Service Quality Model (SERVQUAL), and the Trust-Commitment Theory to explore the factors influencing users' willingness to use intelligent customer service systems. Structural equation modeling (SEM) was employed to examine the interrelationships between the variables, including perceived usefulness, ease of use, trust, customer satisfaction, and system performance. The data were collected via user questionnaires, and the model was validated using confirmatory factor analysis (CFA) to ensure its robustness. The findings indicate that user trust, service quality, and perceived efficiency are key factors influencing user willingness to use.