Abstract

PurposeThe usefulness of technology for managing projects in the construction industry is indisputable. The potential utility of immersive technologies (ImTs), including virtual and augmented reality, has recently received significant attention. However, the construction industry, especially in developing countries, lags on the implementation of technology generally and ImTs specifically. Forecasting the potential successful ImTs acceptance at the individual level is essential to strategic planning. The study's objective was to develop and test a conceptual model of factors influencing ImTs acceptance at the individual level in the construction industry.Design/methodology/approachA survey of construction management-level professionals in South Africa was undertaken. The study extended two complementary models, the technology acceptance model (TAM) and the theory of planned behavior (TPB), to analyze behavior towards technology acceptance using structural equation modelling.FindingsResults indicated that attitude significantly influenced the intention to use ImTs and perceived usefulness (PU) positively and significantly predicted the intention to use and usage attitude (UA). Further, the effects of perceived enjoyment (PEn) on UA, and social norms (SNs) and perceived behavioral control (PBC) on intention to use were positive and significant. Perceived ease of use (PEU) had negative and non-significant effects on intention to use and UA. By explaining 82% of the variance, the study established that the proposed model successfully evaluates how management-level professionals in the construction industry accept ImTs.Practical implicationsThe study provides valuable insight into the acceptance of ImTs from the perspective of management-level stakeholders in the South African construction industry. It offers fundamental direction to create a general theory on integrating ImTs in construction.Originality/valueThis study systematically surveyed the intention to accept ImTs in the South African construction industry using an extension of the TAM and TPB models.

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