Measuring Consumer Behavioural Intention to Accept Technology: Towards Autonomous Vehicles Technology Acceptance Model (AVTAM)

Seuwou, Patrice; Chrysoulas, Christos; Banissi, Ebad; Ubakanma, George

Abstract

The work presented in the paper aims at exploring information technology acceptance in the context of Autonomous Vehicles (AV) with the objectives of identifying and testing the constructs that will influence future AVs acceptance. Most models of technology acceptance focus on barriers of successful information technology implementation in organisations and technologies that have already been deployed. There is only a small number of studies conducted on emerging and disruptive technologies such as AV. We address this issue by deriving context-related determinants from an extensive literature analysis and further describing a technology acceptance modeling process to provide an explanation for drivers’ and factors influencing people behavioural intention to accept AV technology. Based on our evaluation we take the determinants self-efficacy, perceived safety, trust, anxiety and legal regulation into consideration. The outcome and main contribution of this paper is the proposal of a theoretical AV technology acceptance model (AVTAM). This study concluded that the performance of these AV technologies, their safety on the road and consumer’s trust for the AV manufacturers will play a very important role for mass AV adoption.

• Presentation Conference Type: Conference Paper (Published)
• Conference Name: WorldCIST: World Conference on Information Systems and Technologies
• Start Date: Apr 7, 2020
• End Date: Apr 10, 2020
• Acceptance Date: Jan 7, 2020
• Online Publication Date: May 18, 2020
• Publication Date: 2020
• Deposit Date: May 21, 2020
• Publicly Available Date: May 19, 2021
• Publisher: Springer
• Pages: 507-516
• Series Title: Advances in Intelligent Systems and Computing
• Series Number: 1159
• Series ISSN: 2194-5357
• Book Title: Trends and Innovations in Information Systems and Technologies: Volume 1
• ISBN: 9783030456870
• DOI: https://doi.org/10.1007/978-3-030-45688-7_51
• Public URL: http://researchrepository.napier.ac.uk/Output/2664342