Determinants of Digital Museum Visit Intention: An Integrated TAM–TPB Model
Abstract
Against the backdrop of the digital transformation of cultural heritage institutions, mobile Internet and cloud computing technologies have gradually made digital museums an important alternative to physical visits. To deeply explore the underlying behavioral motivations of tourists choosing mobile digital museums, this study integrates the Technology Acceptance Model (TAM) with the Theory of Planned Behavior (TPB), taking the Palace Museum in Beijing as a specific context, and constructs a contextualized direct effect model that includes four core antecedent variables: convenience, technological familiarity, social influence, and cost. Based on the verified 552 research data, we conducted an empirical test of the conceptual path using the structural equation model. The key findings indicate: (1) Social influence is the most crucial factor driving tourists’ visit intention (β= 0.327), highlighting the core role of group identification and social sharing in cultural consumption; (2) Cost (β= 0.263), technology familiarity (β= 0.260), and convenience (β= 0.259) also have a significant positive impact on the visit intention. This research helps to alleviate the limitations of a single theoretical framework when explaining complex cultural consumption decisions, and provides valuable management insights for large cultural heritage institutions to optimize their cloud computing architectures and mobile platform designs, and enhance cultural accessibility.
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References
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