Digital rebirth: how task-technology fit drive immersion and user engagement in intangible cultural heritage VR

With the growing adoption of virtual reality (VR) technologies in Intangible Cultural Heritage (ICH) dissemination. This study integrates the Task–Technology Fit (TTF) model and the Hedonic-Motivation System Adoption Model (HMSAM) to propose a holistic framework for analyzing immersion (IM) and behavioral intention (BI) in VR-ICH experiences. Data from the VR Dunhuang cultural experience involving 387 participants were analyzed using a hybrid methodology combining Partial Least Squares Structural Equation Modeling (PLS-SEM) and Artificial Neural Networks (ANN). The results demonstrate that both task characteristics and technology characteristics significantly influence hedonic motivation through perceived ease of use, with joy and control emerging as the strongest predictors of IM and BI. These findings underscore the interplay between task design, technology integration, and emotional engagement, offering theoretical and practical guidance for designing immersive and sustainable VR heritage experiences that enhance public participation and support the sustainable transmission of cultural heritage.