PurposeThis paper aims to examine the current technology acceptance model (TAM) in the field of mixed reality and digital twin (MRDT) and identify key factors affecting users' intentions to use MRDT. The factors are used as a set of key metrics for proposing a predictive model for virtual, augmented and mixed reality (MR) acceptance by users. This model is called the extended TAM for MRDT adoption in the architecture, engineering, construction and operations (AECO) industry.Design/methodology/approachAn interpretivist philosophical lens was adopted to conduct an inductive systematic and bibliographical analysis of secondary data contained within published journal articles that focused upon MRDT acceptance modelling. The preferred reporting items for systematic reviews and meta-analyses (PRISMA) approach to meta-analysis were adopted to ensure all key investigations were included in the final database set. Quantity indicators such as path coefficients, factor ranking, Cronbach’s alpha (a) and chi-square (b) test, coupled with content analysis, were used for examining the database constructed. The database included journal papers from 2010 to 2020.FindingsThe extant literature revealed that the most commonly used constructs of the MRDT–TAM included: subjective norm; social influence; perceived ease of use (PEOU); perceived security; perceived enjoyment; satisfaction; perceived usefulness (PU); attitude; and behavioural intention (BI). Using these identified constructs, the general extended TAM for MRDT in the AECO industry is developed. Other important factors such as “perceived immersion” could be added to the obtained model.Research limitations/implicationsThe decision to utilise a new technology is difficult and high risk in the construction project context, due to the complexity of MRDT technologies and dynamic construction environment. The outcome of the decision may affect employee performance, project productivity and on-site safety. The extended acceptance model offers a set of factors that assist managers or practitioners in making effective decisions for utilising any type of MRDT technology.Practical implicationsSeveral constraints are apparent due to the limited investigation of MRDT evaluation matrices and empirical studies. For example, the research only covers technologies which have been reported in the literature, relating to virtual reality (VR), augmented reality (AR), MR, DT and sensors, so newer technologies may not be included. Moreover, the review process could span a longer time period and thus embrace a fuller spectrum of technology development in these different areas.Originality/valueThe research provides a theoretical model for measuring and evaluating MRDT acceptance at the individual level in the AECO context and signposts future research related to MRDT adoption in the AECO industry, as well as providing managerial guidance for progressive AECO professionals who seek to expand their use of MRDT in the Fourth Industrial Revolution (4IR). A set of key factors affecting MRDT acceptance is identified which will help innovators to improve their technology to achieve a wider acceptance.

While Virtual Reality (VR) technology has experienced a recent growth in interest and offers immense potential in a number of domains, there is still insufficient information on the acceptance and adoption of this technology among individual users. The purpose of this chapter is to examine the acceptance and adaptation of people using VR technology in the construction industry and to identify factors that prevent VR technology from being adopted more widely in the construction industry. Semi-structured interviews were conducted to approach this research problem among 15 students and academic staff members at two universities. The results of this research indicate that VR technology is acceptable to people who work in the construction industry. However, there are barriers to further adoption of VR technology, namely high VR hardware and software requirements, low affordability, and low accessibility. This research also proposes several resolutions to these barriers, including preparing facilities by construction industries and universities, providing software and hardware requirements for VR technologies, and decreasing the price of VR devices. The results of this research are of immense value to suppliers and companies affiliated with this technology. Further research is required to demonstrate the functionality of VR technology in the construction industry.

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Augmented Reality (AR) is increasingly influential in education. AR technology allows users to learn and practice in a simulated environment that enables repetition, correction, and failure without risk. The present study evaluated users’ attitudes towards using AR for learning complex tasks. The users are asked to interact with an AR Piling (ARP) application that shows various steps of a construction process. A set of selected practitioners and students used the application, and the evaluation involved various participants of different genders and backgrounds. A questionnaire was designed and data was collected through an online survey based on the Technology Acceptance Model (TAM). The model is modified considering education practices and adjusted to an AR app for learning purposes. The novelty of the model lies in various constructs such as technical quality, social influence, perceived immersion, learning, and perceived enjoyment. 200 responses were obtained and used for evaluating the proposed model. The attitude toward using AR and the perceived usefulness of AR were the two factors that determined the participants’ behavioral intention to use ARP. Respondents showed a high level of acceptance for AR. In education and higher learning contexts, the findings of this study contribute to a deeper understanding of how AR is accepted in complex learning environments. The study allows us to extend the TAM by examining how AR technology can be applied to teaching in universities and unpack the ways in which gender influences learning through AR application.

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