Exploring virtual house viewing intentions by integrating the innovation diffusion theory and the unified theory of acceptance and use of technology
Year: 2025
Type: article
Study design: Observational Study
Abstract: This study combined the innovation diffusion theory (IDT) and the unified theory of acceptance and use of technology (UTAUT) to explore the factors influencing user attitudes and behavioral intentions toward virtual reality (VR) house viewing. Data were collected through a questionnaire and empirically analyzed using partial least squares structural equation modeling. The results revealed that the relative advantage of VR viewing had significant, positive, direct, and indirect effects on behavioral intentions. The vividness of VR indirectly and positively influenced behavioral intentions by shaping positive attitudes. The four components of the UTAUT (performance expectancy, effort expectancy, social influence, and facilitating conditions) positively influenced intentions to use VR viewing. These findings demonstrated the suitability of the IDT and UTAUT in house viewing and highlighted the similarities and differences between the influencing factors across contexts. Lastly, this study offers practical recommendations to real estate industry businesses to foster the adoption of VR viewing and promote digital transformation and innovative development in the real estate market. • User attitudes and behavioral intentions toward virtual reality (VR) house viewing. • Data were analyzed using partial least squares structural equation modeling. • The relative advantage of VR viewing had significant, positive, direct and indirect effects on behavioral intentions. • The vividness of VR indirectly and positively influenced behavioral intentions by shaping positive attitudes. • The four components of the UTAUT positively influenced intentions to use VR viewing.
Source: Acta Psychologica
Institutions: Chinese Culture University, National Pingtung University
Language: English
Subfield: Information Systems and Management
Field: Decision Sciences
Domain: Social Sciences
Open Access status: gold
Estimated APC paid: $2,670
OpenAlex ID: W4414898776