Artificial Intelligence Service Usage Satisfaction from User Perspective: An Integrated Model

Based on the Technology Readiness (TR), Technology Acceptance Model (TAM) and Human-Computer Relationship Quality Theory, this study constructs an integrated model for exploring the satisfaction with AI services and its influencing factors from the user's perspective. A total of 296 valid samples were collected through questionnaires, and the data were analyzed using descriptive statistics and Pearson's correlation coefficient. The results show that the quality of human-computer relationship and perceived ease of use have the most significant impact on user satisfaction. Perceived usefulness and optimism and innovation in technology readiness also have a certain impact on satisfaction, while discomfort and insecurity in technology readiness have a relatively smaller impact on user satisfaction with AI service. Relevant suggestions to improve AI service satisfaction are proposed. This study enriches previous research perspectives that focus on technical performance evaluation, and provides a reference for optimizing and improving artificial intelligence services and enhancing user satisfaction.