User Acceptance Mechanism and Behavioral Prediction in the Digital-Intelligent Communication of Intangible Cultural Heritage: An Integrated Analysis Based on the TAM Model and Artificial Neural Networks

In the context of globalization and digital transformation, the protection and transmission of intangible cultural heritage (ICH) face challenges such as generational discontinuity and communication barriers. How to achieve innovative preservation through digital means has become a key issue for both academia and industry. Drawing on the Technology Acceptance Model (TAM), the Information System Success Model, and the Innovation Diffusion Theory, this study builds a multi-level mediation model to examine how information quality, service quality, and system quality influence users' perceived usefulness, perceived ease of use, and behavioral intention. Using a mixed-method approach combining questionnaire surveys and big data analysis, 4,008 valid samples were collected from multiple countries. An Artificial Neural Network (ANN) model was further applied to improve behavioral prediction and theoretical explanation. Results show that enjoyment, interestingness, and interactivity significantly enhance perceived usefulness, while system compatibility and observability strongly affect perceived ease of use. Perceived ease of use has the greatest impact on behavioral intention. The ANN model also verifies the nonlinear relationships among variables, highlighting the pivotal roles of system quality and user experience. Based on these findings, this study suggests optimization strategies for digital ICH communication, including developing immersive and interactive content, improving cross-platform compatibility, creating trustworthy content frameworks, building intelligent recommendation systems, and promoting cross-cultural innovation.