Examining the Factors Influencing Autonomous Vehicle Use and its Impact on Environmental Sustainability in UAE using a Hybrid SEM-ANN Approach
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Date
2024-05
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The British University in Dubai (BUiD)
Abstract
Over the past few years, the evolution of transportation towards autonomous vehicles has attracted substantial interest, signifying a transformative shift in the realm of mobility. Nevertheless, AVs adoption is a complex process, influenced by cutting-edge technological advancements, societal acceptance, regulatory frameworks, and potential environmental impacts, all of which are critical in shaping their integration into modern transportation systems. To address the gap in the existing research of this domain, a comprehensive systematic review was conducted, focusing on AVs adoption through the lens of various information system (IS) models and theoretical frameworks. The systematic review analysed empirical studies published in the timeframe from January 2013 to January 2023, focusing on AVs adoption. Out of 3,532 articles, 71 were shortlisted for in-depth analysis according to specific inclusion criteria. In addition, this study constructs a novel theoretical model based on the integration of the Protection Motivation Theory (PMT), the Behavioural Reasoning Theory (BRT), and the updated IS success model variables to investigate the factors influencing AVs adoption and its impact on environmental sustainability. Subsequently, the proposed model was validated using data obtained from an online survey involving 495 individuals in the UAE, who either own or have had experience using AVs. The proposed model underwent empirical validation by applying a hybrid Structural Equation Modelling-Artificial Neural Network (SEM-ANN). The results of hypothesis testing provided strong support for the majority of the hypotheses derived from the proposed model (i.e., out of 12 hypotheses, 9 were supported).
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Keywords
autonomous vehicles, information system, Protection Motivation Theory (PMT), Behavioural Reasoning Theory (BRT), Structural Equation Modelling (SEM), Artificial Neural Network (ANN)