297
Views
0
CrossRef citations to date
0
Altmetric
Research Article

Acceptance of Highly Automated Vehicles: The Role of Facilitating Condition, Technology Anxiety, Social Influence and Trust

, , , & ORCID Icon
Received 29 Dec 2022, Accepted 31 Jan 2024, Published online: 20 Feb 2024

References

  • Abraham, H., Lee, C., Brady, S., Fitzgerald, C., Mehler, B., Reimer, B., & Coughlin, J. F. (2017). Autonomous vehicles and alternatives to driving: Trust, preferences, and effects of age [Paper Presentation]. Proceedings of the Transportation Research Board 96th Annual Meeting (TRB'17), Washington.
  • Adnan, N., Nordin, S. M., bin Bahruddin, M. A., & Ali, M. (2018). How trust can drive forward the user acceptance to the technology? In-vehicle technology for autonomous vehicle. Transportation Research Part A: Policy and Practice, 118, 819–836. https://doi.org/10.1016/j.tra.2018.10.019
  • European Environment Agency. (2016). Electric vehicles in Europe. https://www.eea.europa.eu/publications/electric-vehicles-in-europe.
  • Al-Saedi, K., Al-Emran, M., Ramayah, T., & Abusham, E. (2020). Developing a general extended UTAUT model for M-payment adoption. Technology in Society, 62, 101293. https://doi.org/10.1016/j.techsoc.2020.101293
  • Baccarella, C. V., Wagner, T. F., Scheiner, C. W., Maier, L., & Voigt, K.-I. (2020). Investigating consumer acceptance of autonomous technologies: The case of self-driving automobiles. European Journal of Innovation Management, 24(4), 1210–1232. https://doi.org/10.1108/EJIM-09-2019-0245
  • Beldad, A. D., & Hegner, S. M. (2018). Expanding the technology acceptance model with the inclusion of trust, social influence, and health valuation to determine the predictors of German users’ willingness to continue using a fitness app: A structural equation modeling approach. International Journal of Human–Computer Interaction, 34(9), 882–893. https://doi.org/10.1080/10447318.2017.1403220
  • Berliner, R. M., Hardman, S., & Tal, G. (2019). Uncovering early adopter’s perceptions and purchase intentions of automated vehicles: Insights from early adopters of electric vehicles in California. Transportation Research Part F: Traffic Psychology and Behaviour, 60, 712–722. https://doi.org/10.1016/j.trf.2018.11.010
  • Buckley, L., Kaye, S.-A., & Pradhan, A. K. (2018). Psychosocial factors associated with intended use of automated vehicles: A simulated driving study. Accident; Analysis and Prevention, 115, 202–208. https://doi.org/10.1016/j.aap.2018.03.021
  • Camilleri, M. A., & Camilleri, A. C. (2022). The acceptance of learning management systems and video conferencing technologies: Lessons learned from COVID-19. Technology, Knowledge and Learning, 27(4), 1311–1333. https://doi.org/10.1007/s10758-021-09561-y
  • César, B. (2021). Human perception inside of a self-driving robotic car. IPSI Transactions on Advanced Research, 17(2), 50–56.
  • Cronbach, L. J., & Meehl, P. E. (1955). Construct validity in psychological tests. Psychological Bulletin, 52(4), 281–302. https://doi.org/10.1037/h0040957
  • Cunningham, M. L., Regan, M. A., Horberry, T., Weeratunga, K., & Dixit, V. (2019). Public opinion about automated vehicles in Australia: Results from a large-scale national survey. Transportation Research Part A: Policy and Practice, 129, 1–18. https://doi.org/10.1016/j.tra.2019.08.002
  • Davies, A. (2018). GM will launch robocars without steering wheels next year. Wired. https://www.wired.com/story/gm-cruise-self-driving-car-launch-2019/
  • Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340. https://doi.org/10.2307/249008
  • Dean, M. D., & Kockelman, K. (2022). Our self-driving future will be shaped by policies of today. Nature Electronics, 5(1), 2–4. https://doi.org/10.1038/s41928-021-00708-4
  • Dirsehan, T., & Can, C. (2020). Examination of trust and sustainability concerns in autonomous vehicle adoption. Technology in Society, 63, 101361. https://doi.org/10.1016/j.techsoc.2020.101361
  • Elliott, K., Meng, J. G., & Hall, M. (2021). An integrated approach for predicting consumer acceptance of self-driving vehicles in the United States. Journal of Marketing Development and Competitiveness, 15(2), 10–20. https://doi.org/10.33423/jmdc.v15i2.4330
  • Etemad-Sajadi, R., & Dos Santos, G. G. (2019). Senior citizens’ acceptance of connected health technologies in their homes. International Journal of Health Care Quality Assurance, 32(8), 1162–1174. https://doi.org/10.1108/IJHCQA-10-2018-0240
  • Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50. https://doi.org/10.1177/002224378101800313
  • Fraedrich, E., Heinrichs, D., Bahamonde-Birke, F. J., & Cyganski, R. (2019). Autonomous driving, the built environment and policy implications. Transportation Research Part A: Policy and Practice, 122, 162–172. https://doi.org/10.1016/j.tra.2018.02.018
  • Guggemos, J., Seufert, S., & Sonderegger, S. (2020). Humanoid robots in higher education: Evaluating the acceptance of Pepper in the context of an academic writing course using the UTAUT. British Journal of Educational Technology, 51(5), 1864–1883. https://doi.org/10.1111/bjet.13006
  • Guo, J., Yuan, Q., Yu, J., Chen, X., Yu, W., Cheng, Q., Wang, W., Luo, W., & Jiang, X. (2022). External human–machine interfaces for autonomous vehicles from pedestrians’ perspective: A survey study. Sensors, 22(9), 3339. https://doi.org/10.3390/s22093339
  • Hajiheydari, N., & Ashkani, M. (2018). Mobile application user behavior in the developing countries: A survey in Iran. Information Systems, 77, 22–33. https://doi.org/10.1016/j.is.2018.05.004
  • Hamid, M. R. A., Sami, W., & Sidek, M. H. M. (2017). Discriminant validity assessment: Use of Fornell & Larcker criterion versus HTMT criterion. Journal of Physics: Conference Series, 890(1), 012163. https://doi.org/10.1088/1742-6596/890/1/012163
  • Huang, L., Li, X., Li, X., Wen, Y., & Yuan, F. (2021). Research on the influencing factors of gerontechnology acceptance by seniors: A case study of Beijing elderly citizens. Innovation and Development Policy, 3, 91–109.
  • Jing, P., Xu, G., Chen, Y., Shi, Y., & Zhan, F. (2020). The determinants behind the acceptance of autonomous vehicles: A systematic review. Sustainability, 12(5), 1719. https://doi.org/10.3390/su12051719
  • Kapser, S., & Abdelrahman, M. (2020). Acceptance of autonomous delivery vehicles for last-mile delivery in Germany–extending UTAUT2 with risk perceptions. Transportation Research Part C: Emerging Technologies, 111, 210–225. https://doi.org/10.1016/j.trc.2019.12.016
  • Kaye, S.-A., Lewis, I., Buckley, L., & Rakotonirainy, A. (2019). Examining Queensland drivers’ a priori acceptance of conditional and full automated vehicles. Proceedings of the 2019 Australasian Road Safety Conference, Adelaide, Australia.
  • Kaye, S.-A., Lewis, I., Forward, S., & Delhomme, P. (2020). A priori acceptance of highly automated cars in Australia, France, and Sweden: A theoretically-informed investigation guided by the TPB and UTAUT. Accident; Analysis and Prevention, 137, 105441. https://doi.org/10.1016/j.aap.2020.105441
  • Kaye, S.-A., Li, X., Oviedo-Trespalacios, O., & Afghari, A. P. (2022). Getting in the path of the robot: Pedestrians acceptance of crossing roads near fully automated vehicles. Travel Behaviour and Society, 26, 1–8. https://doi.org/10.1016/j.tbs.2021.07.012
  • Keszey, T. (2020). Behavioural intention to use autonomous vehicles: Systematic review and empirical extension. Transportation Research Part C: Emerging Technologies, 119, 102732. https://doi.org/10.1016/j.trc.2020.102732
  • Kline, R. B. (2016). Principles and practice of structural equation modeling. Guilford Press.
  • König, M., & Neumayr, L. (2017). Users’ resistance towards radical innovations: The case of the self-driving car. Transportation Research Part F: Traffic Psychology and Behaviour, 44, 42–52. https://doi.org/10.1016/j.trf.2016.10.013
  • Köttl, H., Cohn-Schwartz, E., & Ayalon, L. (2021). Self-perceptions of aging and everyday ICT engagement: A test of reciprocal associations. The Journals of Gerontology. Series B, Psychological Sciences and Social Sciences, 76(9), 1913–1922. https://doi.org/10.1093/geronb/gbaa168
  • Lee, J. D., & Kolodge, K. (2020). Exploring trust in self-driving vehicles through text analysis. Human Factors, 62(2), 260–277. https://doi.org/10.1177/0018720819872672
  • Lee, J. D., & See, K. A. (2004). Trust in automation: Designing for appropriate reliance. Human Factors, 46(1), 50–80. https://doi.org/10.1518/hfes.46.1.50_30392
  • Lee, W. K. H., Man, S. S., & Chan, A. H. S. (2022). Cogeneration system acceptance in the hotel industry: A qualitative study. Journal of Hospitality and Tourism Management, 51, 339–345. https://doi.org/10.1016/j.jhtm.2022.04.004
  • Liu, H., Yang, R., Wang, L., & Liu, P. (2019). Evaluating initial public acceptance of highly and fully autonomous vehicles. International Journal of Human–Computer Interaction, 35(11), 919–931. https://doi.org/10.1080/10447318.2018.1561791
  • Liu, P., Xu, Z., & Zhao, X. (2019). Road tests of self-driving vehicles: Affective and cognitive pathways in acceptance formation. Transportation Research Part A: Policy and Practice, 124, 354–369. https://doi.org/10.1016/j.tra.2019.04.004
  • Liu, P., Yang, R., & Xu, Z. (2019). Public acceptance of fully automated driving: Effects of social trust and risk/benefit perceptions. Risk Analysis, 39(2), 326–341. https://doi.org/10.1111/risa.13143
  • Louw, T., Markkula, G., Boer, E., Madigan, R., Carsten, O., & Merat, N. (2017). Coming back into the loop: Drivers’ perceptual-motor performance in critical events after automated driving. Accident; Analysis and Prevention, 108, 9–18. https://doi.org/10.1016/j.aap.2017.08.011
  • Madigan, R., Louw, T., Wilbrink, M., Schieben, A., & Merat, N. (2017). What influences the decision to use automated public transport? Using UTAUT to understand public acceptance of automated road transport systems. Transportation Research Part F: Traffic Psychology and Behaviour, 50, 55–64. https://doi.org/10.1016/j.trf.2017.07.007
  • Man, S. S., Guo, Y., Chan, A. H. S., & Zhuang, H. (2022). Acceptance of online mapping technology among older adults: Technology acceptance model with facilitating condition, compatibility, and self-satisfaction. ISPRS International Journal of Geo-Information, 11(11), 558. https://doi.org/10.3390/ijgi11110558
  • 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. https://doi.org/10.1109/ACCESS.2020.3001929
  • Mariano, J., Marques, S., Ramos, M. R., Gerardo, F., Cunha, C. L. d., Girenko, A., Alexandersson, J., Stree, B., Lamanna, M., Lorenzatto, M., Mikkelsen, L. P., Bundgård-Jørgensen, U., Rêgo, S., & de Vries, H. (2022). Too old for technology? Stereotype threat and technology use by older adults. Behaviour & Information Technology, 41(7), 1503–1514. https://doi.org/10.1080/0144929X.2021.1882577
  • Marletto, G. (2019). Who will drive the transition to self-driving? A socio-technical analysis of the future impact of automated vehicles. Technological Forecasting and Social Change, 139, 221–234. https://doi.org/10.1016/j.techfore.2018.10.023
  • McCrae, R. R., Costa, P. T., Pedroso de Lima, M., Simões, A., Ostendorf, F., Angleitner, A., Marusić, I., Bratko, D., Caprara, G. V., Barbaranelli, C., Chae, J. H., & Piedmont, R. L. (1999). Age differences in personality across the adult life span: Parallels in five cultures. Developmental Psychology, 35(2), 466–477. https://doi.org/10.1037//0012-1649.35.2.466
  • Meuter, M. L., Ostrom, A. L., Bitner, M. J., & Roundtree, R. (2003). The influence of technology anxiety on consumer use and experiences with self-service technologies. Journal of Business Research, 56(11), 899–906. https://doi.org/10.1016/S0148-2963(01)00276-4
  • Molnar, L. J., Ryan, L. H., Pradhan, A. K., Eby, D. W., Louis, R. M. S., & Zakrajsek, J. S. (2018). Understanding trust and acceptance of automated vehicles: An exploratory simulator study of transfer of control between automated and manual driving. Transportation Research Part F: Traffic Psychology and Behaviour, 58, 319–328. https://doi.org/10.1016/j.trf.2018.06.004
  • Nastjuk, I., Herrenkind, B., Marrone, M., Brendel, A. B., & Kolbe, L. M. (2020). What drives the acceptance of autonomous driving? An investigation of acceptance factors from an end-user’s perspective. Technological Forecasting and Social Change, 161, 120319. https://doi.org/10.1016/j.techfore.2020.120319
  • Neufville, R., Abdalla, H., & Abbas, A. (2022). Potential of connected fully autonomous vehicles in reducing congestion and associated carbon emissions. Sustainability, 14(11), 6910. https://doi.org/10.3390/su14116910
  • Nikitas, A., Thomopoulos, N., & Milakis, D. (2021). The environmental and resource dimensions of automated transport: A nexus for enabling vehicle automation to support sustainable urban mobility. Annual Review of Environment and Resources, 46(1), 167–192. https://doi.org/10.1146/annurev-environ-012220-024657
  • Nordhoff, S., Louw, T., Innamaa, S., Lehtonen, E., Beuster, A., Torrao, G., Bjorvatn, A., Kessel, T., Malin, F., Happee, R., & Merat, N. (2020). Using the UTAUT2 model to explain public acceptance of conditionally automated (L3) cars: A questionnaire study among 9,118 car drivers from eight European countries. Transportation Research Part F: Traffic Psychology and Behaviour, 74, 280–297. https://doi.org/10.1016/j.trf.2020.07.015
  • Olatoye, R. (2011). Levels of participation in ICT training programmes, computer anxiety and ICT utilization among selected professionals. International Journal of Education and Development Using ICT, 7(2), 15–26.
  • Özungur, F., & Hazer, O. (2018). Analyses of the acceptance of communicaction technologies by technology acceptance model of the elderly: Example of the Adana Province. International Journal of Eurasia Social Sciences, 9(31), 238–275.
  • Pal, D., Funilkul, S., Charoenkitkarn, N., & Kanthamanon, P. (2018). Internet-of-things and smart homes for elderly healthcare: An end user perspective. IEEE Access, 6, 10483–10496. https://doi.org/10.1109/ACCESS.2018.2808472
  • Park, J., Hong, E., & Le, H. T. (2021). Adopting autonomous vehicles: The moderating effects of demographic variables. Journal of Retailing and Consumer Services, 63, 102687. https://doi.org/10.1016/j.jretconser.2021.102687
  • Patel, A. V., Friedenreich, C. M., Moore, S. C., Hayes, S. C., Silver, J. K., Campbell, K. L., Winters-Stone, K., Gerber, L. H., George, S. M., Fulton, J. E., Denlinger, C., Morris, G. S., Hue, T., Schmitz, K. H., & Matthews, C. E. (2019). American College of Sports Medicine roundtable report on physical activity, sedentary behavior, and cancer prevention and control. Medicine and Science in Sports and Exercise, 51(11), 2391–2402. https://doi.org/10.1249/MSS.0000000000002117
  • Pettigrew, S., Fritschi, L., & Norman, R. (2018). The potential implications of autonomous vehicles in and around the workplace. International Journal of Environmental Research and Public Health, 15(9), 1876. https://doi.org/10.3390/ijerph15091876
  • Rahman, M. M., Lesch, M. F., Horrey, W. J., & Strawderman, L. (2017). Assessing the utility of TAM, TPB, and UTAUT for advanced driver assistance systems. Accident; Analysis and Prevention, 108, 361–373. https://doi.org/10.1016/j.aap.2017.09.011
  • Rajak, M., & Shaw, K. (2021). An extension of technology acceptance model for mHealth user adoption. Technology in Society, 67, 101800. https://doi.org/10.1016/j.techsoc.2021.101800
  • Raman, P. (2019). Understanding female consumers’ intention to shop online: The role of trust, convenience and customer service. Asia Pacific Journal of Marketing and Logistics, 31(4), 1138–1160. https://doi.org/10.1108/APJML-10-2018-0396
  • Ramjan, S., & Sangkaew, P. (2022). Understanding the adoption of autonomous vehicles in Thailand: An extended TAM approach. Engineering Management in Production and Services, 14(1), 49–62. https://doi.org/10.2478/emj-2022-0005
  • Ribeiro, M. A., Gursoy, D., & Chi, O. H. (2022). Customer acceptance of autonomous vehicles in travel and tourism. Journal of Travel Research, 61(3), 620–636. https://doi.org/10.1177/0047287521993578
  • Rice, S., & Winter, S. R. (2019). Do gender and age affect willingness to ride in driverless vehicles: If so, then why? Technology in Society, 58, 101145. https://doi.org/10.1016/j.techsoc.2019.101145
  • Rojas-Rueda, D., Nieuwenhuijsen, M. J., Khreis, H., & Frumkin, H. (2020). Autonomous vehicles and public health. Annual Review of Public Health, 41(1), 329–345. https://doi.org/10.1146/annurev-publhealth-040119-094035
  • Ryan, M. (2020). The future of transportation: Ethical, legal, social and economic impacts of self-driving vehicles in the year 2025. Science and Engineering Ethics, 26(3), 1185–1208. https://doi.org/10.1007/s11948-019-00130-2
  • Sarkar, S., Chauhan, S., & Khare, A. (2020). A meta-analysis of antecedents and consequences of trust in mobile commerce. International Journal of Information Management, 50, 286–301. https://doi.org/10.1016/j.ijinfomgt.2019.08.008
  • Song, C. S., & Kim, Y.-K. (2022). The role of the human-robot interaction in consumers’ acceptance of humanoid retail service robots. Journal of Business Research, 146, 489–503. https://doi.org/10.1016/j.jbusres.2022.03.087
  • Stilgoe, J. (2021). How can we know a self-driving car is safe? Ethics and Information Technology, 23(4), 635–647. https://doi.org/10.1007/s10676-021-09602-1
  • Sukendro, S., Habibi, A., Khaeruddin, K., Indrayana, B., Syahruddin, S., Makadada, F. A., & Hakim, H. (2020). Using an extended technology acceptance model to understand students’ use of e-learning during Covid-19: Indonesian sport science education context. Heliyon, 6(11), e05410. https://doi.org/10.1016/j.heliyon.2020.e05410
  • Taeihagh, A., & Lim, H. S. M. (2019). Governing autonomous vehicles: Emerging responses for safety, liability, privacy, cybersecurity, and industry risks. Transport Reviews, 39(1), 103–128. https://doi.org/10.1080/01441647.2018.1494640
  • Talukder, M. S., Laato, S., Islam, A. N., & Bao, Y. (2021). Continued use intention of wearable health technologies among the elderly: An enablers and inhibitors perspective. Internet Research, 31(5), 1611–1640. https://doi.org/10.1108/INTR-10-2020-0586
  • 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. https://doi.org/10.2307/30036540
  • Wang, X., Wong, Y. D., Li, K. X., & Yuen, K. F. (2020). This is not me! Technology-identity concerns in consumers’ acceptance of autonomous vehicle technology. Transportation Research Part F: Traffic Psychology and Behaviour, 74, 345–360. https://doi.org/10.1016/j.trf.2020.06.005
  • Wellik, T., & Kockelman, K. (2020). Anticipating land-use impacts of self-driving vehicles in the Austin, Texas, region. Journal of Transport and Land Use, 13(1), 185–205. https://doi.org/10.5198/jtlu.2020.1717
  • Wong, T. K. M., Man, S. S., & Chan, A. H. S. (2021). Exploring the acceptance of PPE by construction workers: An extension of the technology acceptance model with safety management practices and safety consciousness. Safety Science, 139, 105239. https://doi.org/10.1016/j.ssci.2021.105239
  • Xu, Z., Zhang, K., Min, H., Wang, Z., Zhao, X., & Liu, P. (2018). What drives people to accept automated vehicles? Findings from a field experiment. Transportation Research Part C: Emerging Technologies, 95, 320–334. https://doi.org/10.1016/j.trc.2018.07.024
  • Yang, L., Bian, Y., Zhao, X., Liu, X., & Yao, X. (2021). Drivers’ acceptance of mobile navigation applications: An extended technology acceptance model considering drivers’ sense of direction, navigation application affinity and distraction perception. International Journal of Human-Computer Studies, 145, 102507. https://doi.org/10.1016/j.ijhcs.2020.102507
  • Zhang, T., Tao, D., Qu, X., Zhang, X., Lin, R., & Zhang, W. (2019). The roles of initial trust and perceived risk in public’s acceptance of automated vehicles. Transportation Research Part C: Emerging Technologies, 98, 207–220. https://doi.org/10.1016/j.trc.2018.11.018
  • Zhang, T., Tao, D., Qu, X., Zhang, X., Zeng, J., Zhu, H., & Zhu, H. (2020). Automated vehicle acceptance in China: Social influence and initial trust are key determinants. Transportation Research Part C: Emerging Technologies, 112, 220–233. https://doi.org/10.1016/j.trc.2020.01.027
  • Zhang, T., Zeng, W., Zhang, Y., Tao, D., Li, G., & Qu, X. (2021). What drives people to use automated vehicles? A meta-analytic review. Accident; Analysis and Prevention, 159, 106270. https://doi.org/10.1016/j.aap.2021.106270
  • Zhang, W., & Liu, L. (2022). How consumers’ adopting intentions towards eco-friendly smart home services are shaped? An extended technology acceptance model. The Annals of Regional Science, 68(2), 307–330. https://doi.org/10.1007/s00168-021-01082-x
  • Zmud, J., Sener, I. N., & Wagner, J. (2016). Consumer acceptance and travel behavior: Impacts of automated vehicles. Transportation Research Record: Journal of the Transportation Research Board, 2565(1), 57–64. https://doi.org/10.3141/2565-07
  • Zoellick, J. C., Kuhlmey, A., Schenk, L., Schindel, D., & Blüher, S. (2019). Amused, accepted, and used? Attitudes and emotions towards automated vehicles, their relationships, and predictive value for usage intention. Transportation Research Part F: Traffic Psychology and Behaviour, 65, 68–78. https://doi.org/10.1016/j.trf.2019.07.009

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.