Smart building retrofitting acceptance model (SBRAM): a new angle of optimizing smart retrofitting of aged residential buildings

As society and techniques develop rapidly, people raise higher requirements for urban buildings where they live and work. Urban buildings should not only provide suitable space for kinds of activities, but also ensure occupants’ security and health, respond to the changing environments, and provide a better living environment for occupants. In order to improve age residential buildings, smart building retrofitting solutions are widely adopted, such as automatic control of indoor environment, activity detection, health monitoring, smart energy optimization, and other solutions based on IoT, digital twin, computer vision, and other techniques. Even lots of smart building retrofitting solutions have been proposed and applied, whether these new solutions can be accepted by occupants well is seldom concerned. For instance, occupants may not utilize all designed functions and learn the usage of smart techniques easily. A typical technology acceptance model (TAM) has been proposed to explain the interaction between end-users and techniques, but may not be suitable for smart building retrofitting, which is based on new intelligent techniques especially for buildings. This study develops a newsmart building retrofitting acceptance model (SBRAM) for smart building retrofitting by involving different occupant groups and diverse techniques. An experiment and survey are designed and conducted to verify the SBRAM model by partial least squares structural equation modeling (PLS-SEM). This study comes up with a new angle to review smart building retrofitting solutions besides the accuracy of the technique itself, guiding the approach to retrofitting smart buildings by concerning more about occupant-technique interactions.