Accès libre

Understanding the adoption of autonomous vehicles in Thailand: an extended TAM approach

À propos de cet article

Citez

Akbari, M., Rezvani, A., Shahriari, E., Zúñiga, M. Á., & Pouladian, H. (2020). Acceptance of 5 G technology: Mediation role of Trust and Concentration. Journal of Engineering and Technology Management, 57, 101585. doi: 10.1016/j.jengtecman.2020.101585 Search in Google Scholar

Alhashmi, S. F., Salloum, S. A., & Abdallah, S. (2019). Critical success factors for implementing artificial intelligence (AI) projects in Dubai Government United Arab Emirates (UAE) health sector: applying the extended technology acceptance model (TAM). International Conference on Advanced Intelligent Systems and Informatics. Search in Google Scholar

Alhashmi, S. F., Salloum, S. A., & Mhamdi, C. (2019). Implementing artificial intelligence in the United Arab Emirates healthcare sector: an extended technology acceptance model. International Journal of Information Technology and Language Studies, 3(3), 27-42. Search in Google Scholar

Alraja, M. N. (2016). Government acceptance from the individual employees’ perspective. Polish Journal of Management Studies, 14(2), 18-27. doi: 10.17512/pjms.2016.14.2.02 Search in Google Scholar

Al-Sharafi, M. A., Arshah, R. A., Herzallah, F. A., & Alajmi, Q. (2017). The effect of perceived ease of use and usefulness on customers intention to use online banking services: the mediating role of perceived trust. International Journal of Innovative Computing, 7(1), 9-14. Search in Google Scholar

Alzamel, S. (2021). The Moderating Role of Resource Accessibility to the Theory of Planned Behaviour Components: A Study of E-Entrepreneurship Intention among Saudi Women. Polish Journal of Management Studies, 24(1), 30-44. doi: 10.17512/pjms.2021.24.1.02 Search in Google Scholar

Amin, M., Rezaei, S., & Abolghasemi, M. (2014). User satisfaction with mobile websites: the impact of perceived usefulness (PU), perceived ease of use (PEOU) and trust. Nankai Business Review International, 5(3), 258-274. Search in Google Scholar

Bagozzi, R. P., & Yi, Y. (1988). On the evaluation of structural equation models. Journal of the Academy of Marketing Science, 16(1), 74-94. Search in Google Scholar

Bezai, N. E., Medjdoub, B., Al-Habaibeh, A., Chalal, M. L., & Fadli, F. (2021). Future cities and autonomous vehicles: analysis of the barriers to full adoption. Energy and Built Environment, 2(1), 65-81. doi: 10.1016/j.enbenv.2020.05.002 Search in Google Scholar

Bharadwaj, S., & Deka, S. (2021). Behavioural intention towards investment in cryptocurrency: an integration of Rogers’ diffusion of innovation theory and the technology acceptance model. Forum Scientiae Oeconomia, 9(4), 137-159. Search in Google Scholar

Carr, N. K. (2019). As the Role of the Driver Changes with Autonomous Vehicle Technology, so, Too, Must the Law Change. Mary’s Law Journal, 51(4), 817-843. Search in Google Scholar

Chailungka, P., Preittigun, A., & Ramjan, S. (2021). Public Policy Design for Artificial Intelligence Adoption: A Case Study of Autonomous Vehicle in Thailand. 11th National Conference of Southern College of Technology Research., Southern College of Technology, Nakorn Sri Thammarat. Search in Google Scholar

Chang, H. S., Lee, S. C., & Ji, Y. G. (2016). Wearable device adoption model with TAM and TTF. International Journal of Mobile Communications, 14(5), 518-537. doi: 10.1504/IJMC.2016.078726 Search in Google Scholar

Chao, C.-M. (2019). Factors Determining the Behavioral Intention to Use Mobile Learning: An Application and Extension of the UTAUT Model. Frontiers in Psychology, 10, 1652. doi: 10.3389/fpsyg.2019.01652 Search in Google Scholar

Chong, B., Yang, Z., & Wong, M. (2003). Asymmetrical impact of trustworthiness attributes on trust, perceived value and purchase intention: a conceptual framework for cross-cultural study on consumer perception of online auction. 5th International Conference on Electronic Commerce. Search in Google Scholar

Chung, J. E., Park, N., Wang, H., Fulk, J., & McLaughlin, M. (2010). Age differences in perceptions of online community participation among non-users: An extension of the Technology Acceptance Model. Computers in Human Behavior, 26(6), 1674-1684. doi: 10.1016/j.chb.2010.06.016 Search in Google Scholar

Coeckelbergh, M., Pop, C., Simut, R., Peca, A., Pintea, S., David, D., & Vanderborght, B. (2016). A survey of expectations about the role of robots in robot-assisted therapy for children with ASD: ethical acceptability, trust, sociability, appearance, and attachment. Science and Engineering Ethics, 22(1), 47-65. Search in Google Scholar

Creswell, J. W., & Creswell, J. D. (2017). Research design: Qualitative, quantitative, and mixed methods approaches. Sage. Search in Google Scholar

Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340. doi: 10.2307/249008 Search in Google Scholar

Diop, E. B., Zhao, S., Song, S., & Van Duy, T. (2020). Modelling travellers’ route switching behaviour in response to variable message signs using the technology acceptance model. Transport, 35(5), 533-547. Search in Google Scholar

Ejdys, J. (2018). Building technology trust in ICT application at a University. International Journal of Emerging Market, 13(5), 980-997. doi: 10.1108/IJoEM-07-2017-0234 Search in Google Scholar

Ejdys, J. (2020). Trust-Based Determinants of Future Intention to Use Technology. Foresight and STI Governance, 14(1), 60-68. doi: 10.17323/2500-2597.2020.1.60.68 Search in Google Scholar

Ejdys, J., & Halicka, K. (2018). Sustainable adaptation of new technology – the case of humanoids used for the care of older adults. Sustainability, 10(10), 3770. doi: 10.3390/su10103770 Search in Google Scholar

Felzmann, H., Villaronga, E. F., Lutz, C., & Tamò-Larrieux, A. (2019). Transparency you can trust: Transparency requirements for artificial intelligence between legal norms and contextual concerns. Big Data & Society, 6(1). doi: 10.1177/2053951719860542 Search in Google Scholar

Gempton, N., Skalistis, S., Furness, J., Shaikh, S., & Petrovic, D. (2013). Autonomous control in military logistics vehicles: Trust and safety analysis. International Conference on Engineering Psychology and Cognitive Ergonomics. Search in Google Scholar

Gerbing, D. W., & Anderson, J. C. (1992). Monte Carlo evaluations of goodness of fit indices for structural equation models. Sociological Methods & Research, 21(2), 132-160. Search in Google Scholar

Gill, T. (2020). Blame it on the self-driving car: how autonomous vehicles can alter consumer morality. Journal of Consumer Research, 47(2), 272-291. doi: 10.1093/jcr/ucaa018 Search in Google Scholar

Hadi, S. H., Permanasari, A. E., Hartanto, R., Sakkinah, I. S., Sholihin, M., Sari, R. C., & Haniffa, R. (2021). Developing augmented reality-based learning media and users’ intention to use it for teaching accounting ethics. Education and Information Technologies. doi: 10.1007/s10639-021-10531-1 Search in Google Scholar

Hair, J. F. (2010). Multivariate data analysis: a global perspective (7th ed. ed.). Pearson/Prentice-Hall. Search in Google Scholar

Hernandez-Ortega, B. (2011). The role of post-use trust in the acceptance of a technology: Drivers and consequences. Technovation, 31(10-11), 523-538. Search in Google Scholar

Hinkin, T. R. (2005). Scale Development Principles and Practices. In R. A. Swanson, & E. F. Holton III (Eds.), Research in Organizations: Foundations and Methods of Inquiry (pp. 161-179). San Francisco, CA: Berrett-Koehler Publishers. Search in Google Scholar

Hu, L. T., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6(1), 1-55. Search in Google Scholar

Hutchins, N., Kirkendoll, Z., & Hook, L. (2017). Social impacts of ethical artifical intelligence and autonomous system design. 2017 IEEE International Systems Engineering Symposium (ISSE). Search in Google Scholar

Jamšek, S., & Culiberg, B. (2020). Introducing a three-tier sustainability framework to examine bike-sharing system use: An extension of the technology acceptance model. International Journal of Consumer Studies, 44(2), 140-150. Search in Google Scholar

Kangwansil, K., & Leelasantitham, A. (2020). Factors Affecting the Acceptance of Technology Adoption Model in Digital Painting on Tablet of Media Arts Students. 59th Annual Conference of the Society of Instrument and Control Engineers of Japan (SICE). Search in Google Scholar

Kaushik, A. K., Agrawal, A. K., & Rahman, Z. (2015). Tourist behaviour towards self-service hotel technology adoption: Trust and subjective norm as key antecedents. Tourism Management Perspectives, 16, 278-289. doi: 10.1016/j.tmp.2015.09.002 Search in Google Scholar

Kim, S. (2018). Chapter Two - Blockchain for a Trust Network Among Intelligent Vehicles. In P. Raj & G. C. Deka (Eds.), Advances in Computers (pp. 43-68). Elsevier. doi: 10.1016/bs.adcom.2018.03.010 Search in Google Scholar

Księżak, P., & Wojtczak, S. (2020). AI versus robot: in search of a domain for the new European civil law. Law, Innovation and Technology, 12(2), 297-317. Search in Google Scholar

Lee, C., & Wan, G. (2010). Including subjective norm and technology trust in the technology acceptance model: a case of e-ticketing in China. ACM SIGMIS Database: The DATABASE for Advances in Information Systems, 41(4), 40-51. Search in Google Scholar

Lee, L., & Charles, V. (2021). The impact of consumers’ perceptions regarding the ethics of online retailers and promotional strategy on their repurchase intention. International Journal of Information Management, 57, 102264. doi: 10.1016/j.ijinfomgt.2020.102264 Search in Google Scholar

Lee, W., Xiong, L., & Hu, C. (2012). The effect of Facebook users’ arousal and valence on intention to go to the festival: Applying an extension of the technology acceptance model. International Journal of Hospitality Management, 31(3), 819-827. Search in Google Scholar

Liao, C., Liu, C.-C., & Chen, K. (2011). Examining the impact of privacy, trust and risk perceptions beyond monetary transactions: An integrated model. Electronic Commerce Research and Applications, 10(6), 702-715. doi: 10.1016/j.elerap.2011.07.003 Search in Google Scholar

Liu, A.-C., & Chou, T.-Y. (2020). An integrated technology acceptance model to approach the behavioral intention of smart home appliance. International Journal of Organizational Innovation, 13(2), 95-118. Search in Google Scholar

Ljungholm, D. P. (2020). Regulating Autonomous Vehicles in a Smart Urban Transport System: Safety, Security, and Privacy Issues. Contemporary Readings in Law and Social Justice, 12(2), 9-15. Search in Google Scholar

Lu, J., Yu, C. S., Liu, C., & Yao, J. E. (2003). Technology acceptance model for wireless Internet. Internet Research, 3(13), 206-222. Search in Google Scholar

Luarn, P., & Juo, W.-J. (2010). The role of trust in technology within the TAM in the context of NFC mobile payment. Journal of Information and Optimization Sciences, 31(4), 875-896. Search in Google Scholar

Lui, H. K., & Jamieson, R. (2003). TriTAM: a model for integrating trust and risk perceptions in business-to-consumer electronic commerce. 16th Bled Electronic Commerce Conference, Slovenia. Search in Google Scholar

Man, S. S., Xiong, W., Chang, F., & Chan, A. H. S. (2020). Critical factors influencing acceptance of automated vehicles by hong kong drivers. IEEE Access, 8, 109845-109856. Search in Google Scholar

Manfreda, A., Ljubi, K., & Groznik, A. (2021). Autonomous vehicles in the smart city era: An empirical study of adoption factors important for millennials. International Journal of Information Management, 58, 102050. doi: 10.1016/j.ijinfomgt.2019.102050 Search in Google Scholar

McKnight, D. H., Liu, P., & Pentland, B. T. (2020). Trust Change in Information Technology Products. Journal of Management Information Systems, 37(4), 1015-1046. Search in Google Scholar

Mousa, A. H., Mousa, S. H., Aljshamee, M., & Nasir, I. S. (2021). Determinants of customer acceptance of e-banking in Iraq using technology acceptance model. Telkomnika, 19(2), 421-431. Search in Google Scholar

Nadeem, W., & Al-Imamy, S. (2020). Do ethics drive value co-creation on digital sharing economy platforms? Journal of Retailing and Consumer Services, 55, 102095. Search in Google Scholar

Nasri, W., & Charfeddine, L. (2012). Factors affecting the adoption of Internet banking in Tunisia: An integration theory of acceptance model and theory of planned behavior. The Journal of High Technology Management Research, 23(1), 1-14. Search in Google Scholar

Nelson, A. (2020). Smart transportation systems: Sustainable mobilities, autonomous vehicle decision-making algorithms, and networked driverless technologies. Contemporary Readings in Law and Social Justice, 12(2), 25-33. Search in Google Scholar

Noor, N. L. M., Hashim, M., Haron, H., & Aiffin, S. (2005). Community acceptance of knowledge sharing system in the travel and tourism websites: an application of an extension of TAM. 13th European Conference on Information Systems, Information Systems in a Rapidly Changing Economy, ECIS, Regensburg, Germany. Search in Google Scholar

Park, E., Cho, Y., Han, J., & Kwon, S. J. (2017). Comprehensive approaches to user acceptance of Internet of Things in a smart home environment. IEEE Internet of Things Journal, 4(6), 2342-2350. doi: 10.1109/JIOT.2017.2750765 Search in Google Scholar

Patil, K. (2016). Retail adoption of Internet of Things: Applying TAM model. 2016 International conference on computing, analytics and security trends (CAST). Search in Google Scholar

Poisson, C., Safin, S., Langlois, S., Forzy, J.-F., & Decortis, F. (2016). Determinants and experience of the takeover of an autonomous vehicle. 15th Ergo’IA “Ergonomie Et Informatique Avancée” Conference. Search in Google Scholar

Prakken, H. (2017). On making autonomous vehicles respect traffic law: a case study for dutch law. 16th edition of the International Conference on Articial Intelligence and Law. Search in Google Scholar

Rathnaweera, L., & Karunasena, A. (2020). Influencial Factors of Adopting Digital Banking by Users in Western Province of Sri Lanka. 2nd International Conference on Advancements in Computing (ICAC). Search in Google Scholar

Raut, R., Priyadarshinee, P., & Jha, M. (2018). Understanding the mediation effect of cloud computing adoption in Indian organization: integrating TAM-TOE-Risk model. In Technology Adoption and Social Issues: Concepts, Methodologies, Tools, and Applications (pp. 675-697). IGI Global. Search in Google Scholar

Revels, J., Tojib, D., & Tsarenko, Y. (2010). Understanding consumer intention to use mobile services. Australasian Marketing Journal, 18(2), 74-80. Search in Google Scholar

Roth, M. L. (2019). Regulating the Future: Autonomous Vehicles and the Role of Government. Iowa Law Review, 105, 1411-1446. Search in Google Scholar

Sangkaew, P., Jago, L., & Gkritzali, A. (2019). Adapting the Technology Acceptance Model (TAM) For Business Events: The Event Organizer Perspectives. Event Management, 23(6), 773-788. doi: 10.3727/152599519X15506259855832 Search in Google Scholar

Schwab, K. (2017). The Fourth Industrial Revolution. Penguin Books Limited. Search in Google Scholar

Shao, S. (2020). Iterative Autonomous Vehicle Regulation and Governance: How Distributed Regulatory Experiments and Inter-Regional Coopetition within Federal Boundaries Can Nurture the Future of Mobility. Journal of Law, Technology & Policy, 2020(2), 325-359. Search in Google Scholar

Showalter, S. (2005). The law governing autonomous undersea vehicles: what an operator needs to know. OCEANS 2005 MTS/IEEE. Search in Google Scholar

Sıcakyüz, C., & Hacire, Y. O. (2020). Exploring resistance factors on the usage of hospital information systems from the perspective of the Markus’s Model and the Technology Acceptance Model. Journal of Entrepreneurship, Management and Innovation, 16(2), 93-131. doi: 10.7341/20201624 Search in Google Scholar

Straub, E. R., & Schaefer, K. E. (2019). It takes two to Tango: Automated vehicles and human beings do the dance of driving – Four social considerations for policy. Transportation Research Part A: Policy and Practice, 122, 173-183. doi: 10.1016/j.tra.2018.03.005 Search in Google Scholar

Tho, Q. H., Phap, H. C., & Phuong, P. A. (2019). A solution to ethical and legal problem with the decision-making model of autonomous vehicles. 11th International Conference on Knowledge and Systems Engineering (KSE). Search in Google Scholar

Thongkoo, K., Daungcharone, K., & Thanyaphongphat, J. (2020). Students’ Acceptance of Digital Learning Tools in Programming Education Course using Technology Acceptance Model. Joint International Conference on Digital Arts, Media and Technology with ECTI Northern Section Conference on Electrical, Electronics, Computer and Telecommunications Engineering (ECTI DAMT & NCON). Search in Google Scholar

Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425-478. Search in Google Scholar

Wang, S.-M., Huang, Y.-K., & Wang, C.-C. (2020). A model of consumer perception and behavioral intention for AI service. 2nd International Conference on Management Science and Industrial Engineering. Search in Google Scholar

Wang, T.-L. (2011). An effect of trust and attitude in the initial adoption of online shopping: An empirical study. International Conference on Information Society (i-Society 2011). Search in Google Scholar

Williams, B. (2021). Automated Vehicles and MaaS: Removing the Barriers. John Wiley & Sons. Search in Google Scholar

Wright, S. A. (2020). AI in the Law: Towards Assessing Ethical Risks. 2020 IEEE International Conference on Big Data (Big Data). Search in Google Scholar

Yijia, Z., Jiaqi, H., Guiqin, L., Feng, C., & Zhiyuan, G. (2019). Autonomous Driving Ethics Case Study for Engineering Ethics Education. International Conference on Modern Educational Technology. Search in Google Scholar

Yin, H., To, K. H., Keung, C. P. C., & Tam, W. W. Y. (2019). Professional learning communities count: Examining the relationship between faculty trust and teacher professional learning in Hong Kong kindergartens. Teaching and Teacher Education, 82, 153-163. Search in Google Scholar

Zhao, J., Fang, S., & Jin, P. (2018). Modeling and quantifying user acceptance of personalized business modes based on TAM, trust and attitude. Sustainability, 10(2), 356. Search in Google Scholar

Zhou, J., Chen, F., Berry, A., Reed, M., Zhang, S., & Savage, S. (2020). A Survey on Ethical Principles of AI and Implementations. IEEE Symposium Series on Computational Intelligence (SSCI). Search in Google Scholar

Zolotov, M. N., Oliveira, T., & Casteleyn, S. (2018). E-participation adoption models research in the last 17 years: A weight and meta-analytical review. Computers in Human Behavior, 81, 350-365. doi: 10.1016/j.chb.2017.12.031 Search in Google Scholar