Leveraging sustainable housing through artificial intelligence enabled dynamic capability, technological self efficacy, digital twin adoption and data driven culture in Netherlands

Drawing on dynamic capability theory, social cognitive theory, and socio-technical system theory, this research examines the mediating roles of technological self-efficacy and digital twin adoption in the relationship between AI-enabled dynamic capability and sustainable housing in the Dutch housing sector. Furthermore, this study examines the moderating effect of data-driven culture on the relationships among AI-enabled dynamic capability, technological self-efficacy, and digital twin adoption. The structured, closed-ended questionnaire was distributed to the senior manager of housing projects using a time-lagged, three-wave (T1, T2, T3) research approach, in which data were collected on AI-enabled dynamic capability and data-driven culture at T1. After 4 weeks, data were collected on technological self-efficacy and digital twin adoption. Similarly, at T3 (after 4 weeks), data collection on sustainable housing was conducted. The final number of complete questionnaires was 246, which was utilised for the final analysis. Partial least squares structural equation modelling was employed for data analysis and hypothesis testing. The results reveal a significant and positive effect of AI-enabled dynamic capability on sustainable housing. Furthermore, the mediating roles of technological self-efficacy and digital twin adoption in the relationship between AI-enabled dynamic capability and sustainable housing are also established. In addition, a data-driven culture moderates the relationships among AI-enabled dynamic capability, technological self-efficacy, and digital twins in the Dutch housing sector.