Virtual reality (VR) technology in tourism and hospitality has been discussed during this decade with increasing research interest. It has been described as the environment created by a computer that can be either a simulation of the real world or an imaginative one. Visitors can enhance their travel experience by adopting ICT throughout the whole process of their trip. Thus, innovations from advanced technology play a significant part in ICT. According to Law et al. (2014), advanced technology has become one of the crucial factors to influence the tourism and hospitality industry. VR technology plays a significant part in the innovation of museums by employing advance technology for visitor interactions with exhibition material (Trunfio et al., 2022). For example, VR technology can redefine the virtual environment in museums, which can alter their positioning of attraction image (Trunfio et al., 2022). The research objectives of this study are to explore visitors’ experience with VR technology in museums and to understand the relationship between variables from extended UTAUT and attitude towards VR technology experience.  Using the quantitative partial least squares–structural equation modelling (PLS–SEM) method to analyse the conceptual framework, this research can identify significant factors influencing visitors’ VR experience in museums. A sample size of 781 respondents from Macau Science Museum and museums in mainland China are involved. Quantitative PLS–SEM analysis is performed to determine the influences of extended UTAUT variables on visitors’ attitude towards VR technology experience, VR technology attraction image and intention to revisit and recommend museums with VR technology. This research can help destination marketers understand which dimensions are the most influential to visitors’ behavioural intention. For instance, to enhance museums’ image, museum practitioners can meet visitor expectation and provide visitor enjoyment, reliable network connection and human technical support. Further studies can demonstrate the moderating relationship among gender, age group that between the independent variables and dependent variable ‘behavioural intention’ in this research.