IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v16y2024i22p9696-d1515921.html
   My bibliography  Save this article

Research on the Behavior Influence Mechanism of Users’ Continuous Usage of Autonomous Driving Systems Based on the Extended Technology Acceptance Model and External Factors

Author

Listed:
  • Juncheng Mu

    (School of Fine Arts, Nanjing Normal University, Nanjing 210023, China)

  • Linglin Zhou

    (School of Fine Arts, Nanjing Normal University, Nanjing 210023, China)

  • Chun Yang

    (School of Design, Jiangnan University, Wuxi 214122, China)

Abstract

In recent years, with the advancement of urbanization and the increase in traffic congestion, the demand for autonomous driving has been steadily growing in order to promote sustainable urban development. The evolution of automotive autonomous driving systems significantly influences the progress of sustainable urban development. As these systems advance, user evaluations of their performance vary widely. Autonomous driving systems present both technological advantages and controversies, along with challenges. To foster the development of autonomous driving systems and facilitate transformative changes in urban traffic sustainability, this research aims to explore user behavior regarding the continued use of autonomous driving systems. It is based on an extended technology acceptance model, examining the impacts of user scale, perceived importance, post-experience regret, user driving habits, and external factors on the intention to continue using these systems. The conclusions are as follows. (1) A model design is constructed that uses user scale, perceived importance, and regret after experience as antecedent variables, with user driving habits as a mediating variable to explain the intention to continue using autonomous driving systems, demonstrating a degree of innovation. (2) It is verified that user driving habits are a key factor determining the intention to continue using these systems, highlighting the importance of user habits in the application of autonomous driving systems. (3) Perceived importance significantly affects both user driving habits and the intention to continue using the system, while regret after experience has a significant negative correlation only with habit formation and does not directly affect the intention to continue use, indicating that users are more concerned with the actual functionality and practicality of the system. (4) User scale is shown to indirectly influence the intention to continue using through various pathways, providing a new perspective for related theoretical research. (5) Aside from safety capabilities, other external factors such as economic benefits and technological stability significantly influence the intention to continue using, while the lack of significance for safety capabilities may be due to users trusting their own driving skills in critical moments. (6) The research results offer valuable references for the improvement and promotion of autonomous driving systems, emphasizing the practicality and usability of the system. (7) This study provides a new theoretical framework for the application of habit theory and regret theory in related fields. Therefore, through empirical analysis, this research delves into the key factors influencing the intention to continue using autonomous driving systems, offering certain reference value for the development of autonomous driving systems and contributing to their theoretical development and practical application.

Suggested Citation

  • Juncheng Mu & Linglin Zhou & Chun Yang, 2024. "Research on the Behavior Influence Mechanism of Users’ Continuous Usage of Autonomous Driving Systems Based on the Extended Technology Acceptance Model and External Factors," Sustainability, MDPI, vol. 16(22), pages 1-24, November.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:22:p:9696-:d:1515921
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/16/22/9696/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/16/22/9696/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. David E. Bell, 1982. "Regret in Decision Making under Uncertainty," Operations Research, INFORMS, vol. 30(5), pages 961-981, October.
    2. Supranee Lisawadi & S. Ejaz Ahmed & Orawan Reangsephet & Muhammad Kashif Ali Shah, 2019. "Simultaneous estimation of Cronbach’s alpha coefficients," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 48(13), pages 3236-3257, July.
    3. Viswanath Venkatesh & Fred D. Davis, 2000. "A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies," Management Science, INFORMS, vol. 46(2), pages 186-204, February.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Stroh, Tim & Mention, Anne-Laure & Duff, Cameron, 2023. "The impact of evolved psychological mechanisms on innovation and adoption: A systematic literature review," Technovation, Elsevier, vol. 125(C).
    2. Saeideh Sharifi fard & Ezhar Tamam & Md Salleh Hj Hassan & Moniza Waheed & Zeinab Zaremohzzabieh, 2016. "Factors affecting Malaysian university students’ purchase intention in social networking sites," Cogent Business & Management, Taylor & Francis Journals, vol. 3(1), pages 1182612-118, December.
    3. Yoichiro Fujii & Yusuke Osaki, 2018. "Regret-sensitive treatment decisions," Health Economics Review, Springer, vol. 8(1), pages 1-8, December.
    4. Chou, Jui-Sheng & Gusti Ayu Novi Yutami, I, 2014. "Smart meter adoption and deployment strategy for residential buildings in Indonesia," Applied Energy, Elsevier, vol. 128(C), pages 336-349.
    5. Philippe Cohard, 2020. "Information Systems Values: A Study of the Intranet in Three French Higher Education Institutions," Post-Print hal-02987225, HAL.
    6. Castro, Luciano de & Galvao, Antonio F. & Kim, Jeong Yeol & Montes-Rojas, Gabriel & Olmo, Jose, 2022. "Experiments on portfolio selection: A comparison between quantile preferences and expected utility decision models," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 97(C).
    7. Georgia Perakis & Guillaume Roels, 2008. "Regret in the Newsvendor Model with Partial Information," Operations Research, INFORMS, vol. 56(1), pages 188-203, February.
    8. Melih Engin & Fatih Gürses, 2019. "Adoption of Hospital Information Systems in Public Hospitals in Turkey: An Analysis with the Unified Theory of Acceptance and Use of Technology Model," International Journal of Innovation and Technology Management (IJITM), World Scientific Publishing Co. Pte. Ltd., vol. 16(06), pages 1-19, October.
    9. Morosan, Cristian, 2016. "An empirical examination of U.S. travelers’ intentions to use biometric e-gates in airports," Journal of Air Transport Management, Elsevier, vol. 55(C), pages 120-128.
    10. Amos Schurr & Yaakov Kareev & Judith Avrahami & Ilana Ritov, 2012. "Taking the Broad Perspective: Risky Choices in Repeated Proficiency Tasks," Discussion Paper Series dp621, The Federmann Center for the Study of Rationality, the Hebrew University, Jerusalem.
    11. Tsung Teng Chen, 2012. "The development and empirical study of a literature review aiding system," Scientometrics, Springer;Akadémiai Kiadó, vol. 92(1), pages 105-116, July.
    12. Jinyi Hu, 2023. "Linguistic Multiple-Attribute Decision Making Based on Regret Theory and Minimax-DEA," Mathematics, MDPI, vol. 11(20), pages 1-14, October.
    13. Sacha Bourgeois-Gironde, 2017. "How regret moves individual and collective choices towards rationality," Chapters, in: Morris Altman (ed.), Handbook of Behavioural Economics and Smart Decision-Making, chapter 11, pages 188-204, Edward Elgar Publishing.
    14. Martín Egozcue & Xu Guo & Wing-Keung Wong, 2015. "Optimal output for the regret-averse competitive firm under price uncertainty," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 5(2), pages 279-295, December.
    15. Abdesamad Zouine & Pierre Fenies, 2014. "The Critical Success Factors Of The ERP System Project: A Meta-Analysis Methodology," Post-Print hal-01419785, HAL.
    16. Debora Bettiga & Lucio Lamberti & Emanuele Lettieri, 2020. "Individuals’ adoption of smart technologies for preventive health care: a structural equation modeling approach," Health Care Management Science, Springer, vol. 23(2), pages 203-214, June.
    17. Kertcher, Zack & Venkatraman, Rohan & Coslor, Erica, 2020. "Pleasingly parallel: Early cross-disciplinary work for innovation diffusion across boundaries in grid computing," Journal of Business Research, Elsevier, vol. 116(C), pages 581-594.
    18. Colson, Gérard, 1993. "Prenons-nous assez de risque dans les théories du risque?," L'Actualité Economique, Société Canadienne de Science Economique, vol. 69(1), pages 111-141, mars.
    19. Talukder, Md. Shamim & Sorwar, Golam & Bao, Yukun & Ahmed, Jashim Uddin & Palash, Md. Abu Saeed, 2020. "Predicting antecedents of wearable healthcare technology acceptance by elderly: A combined SEM-Neural Network approach," Technological Forecasting and Social Change, Elsevier, vol. 150(C).
    20. Fang Li & Sheng Zhang & Yuhuan Jin, 2018. "Sustainability of University Technology Transfer: Mediating Effect of Inventor’s Technology Service," Sustainability, MDPI, vol. 10(6), pages 1-17, June.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:16:y:2024:i:22:p:9696-:d:1515921. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.