IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i6p5028-d1094988.html
   My bibliography  Save this article

An Empirical Study of the Factors Influencing Users’ Intention to Use Automotive AR-HUD

Author

Listed:
  • Tiansheng Xia

    (School of Art and Design, Guangdong University of Technology, Guangzhou 510090, China)

  • Xiaowu Lin

    (School of Art and Design, Guangdong University of Technology, Guangzhou 510090, China)

  • Yongqing Sun

    (School of Art and Design, Guangdong University of Technology, Guangzhou 510090, China)

  • Tingting Liu

    (School of Art and Design, Guangdong University of Technology, Guangzhou 510090, China)

Abstract

An automotive augmented reality head-up display (AR-HUD) can provide an immersive experience for users and is anticipated to become one of the ultimate terminals for human–machine interaction in future intelligent vehicles within the context of smart cities. However, the majority of the current research on AR-HUD is focused on technological implementation and interaction interface design, and there are relatively few studies that examine the psychological factors that may influence the public’s willingness to utilize this technology. Based on the theory of reasoned action (TRA) and the unified theory of acceptance and use of technology (UTAUT), this study constructs a model of users’ willingness to use automotive AR-HUD involving both cognitive and social factors. The study recruited 377 participants and collected data on users’ effort expectation, performance expectation, social influence, perceived trust, personal innovation, and AR-HUD usage intention through a questionnaire. It was found that users’ effort expectation influenced their intention to use AR-HUD through the mediating role of performance expectation. Social influence had an impact on users’ AR-HUD usage intention through the mediating role of perceived trust, and personal innovation moderated the strength of the role of social influence on perceived trust as a moderating variable.

Suggested Citation

  • Tiansheng Xia & Xiaowu Lin & Yongqing Sun & Tingting Liu, 2023. "An Empirical Study of the Factors Influencing Users’ Intention to Use Automotive AR-HUD," Sustainability, MDPI, vol. 15(6), pages 1-15, March.
  • Handle: RePEc:gam:jsusta:v:15:y:2023:i:6:p:5028-:d:1094988
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/6/5028/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/15/6/5028/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Thomas Leicht & Anis Chtourou & Kamel Ben Youssef, 2018. "Consumer innovativeness and intentioned autonomous car adoption," Post-Print hal-02511554, HAL.
    2. Alsajjan, Bander & Dennis, Charles, 2010. "Internet banking acceptance model: Cross-market examination," Journal of Business Research, Elsevier, vol. 63(9-10), pages 957-963, September.
    3. Featherman, Mauricio & Jia, Shizhen (Jasper) & Califf, Christopher B. & Hajli, Nick, 2021. "The impact of new technologies on consumers beliefs: Reducing the perceived risks of electric vehicle adoption," Technological Forecasting and Social Change, Elsevier, vol. 169(C).
    4. Jian Chen & Rui Li & Mi Gan & Zhiyan Fu & Fatao Yuan, 2020. "Public Acceptance of Driverless Buses in China: An Empirical Analysis Based on an Extended UTAUT Model," Discrete Dynamics in Nature and Society, Hindawi, vol. 2020, pages 1-13, November.
    5. Midgley, David F & Dowling, Grahame R, 1978. "Innovativeness: The Concept and Its Measurement," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 4(4), pages 229-242, March.
    6. Felix Becker & Kay W. Axhausen, 2017. "Literature review on surveys investigating the acceptance of automated vehicles," Transportation, Springer, vol. 44(6), pages 1293-1306, November.
    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. Li, Dun & Huang, Youlin & Qian, Lixian, 2022. "Potential adoption of robotaxi service: The roles of perceived benefits to multiple stakeholders and environmental awareness," Transport Policy, Elsevier, vol. 126(C), pages 120-135.
    2. Zhiyuan Yu & Doudou Jin, 2021. "Determinants of Users’ Attitude and Intention to Intelligent Connected Vehicle Infotainment in the 5G-V2X Mobile Ecosystem," IJERPH, MDPI, vol. 18(19), pages 1-19, September.
    3. Kapser, Sebastian & Abdelrahman, Mahmoud & Bernecker, Tobias, 2021. "Autonomous delivery vehicles to fight the spread of Covid-19 – How do men and women differ in their acceptance?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 148(C), pages 183-198.
    4. Xiaobei Jiang & Wenlin Yu & Wenjie Li & Jiawen Guo & Xizheng Chen & Hongwei Guo & Wuhong Wang & Tao Chen, 2021. "Factors Affecting the Acceptance and Willingness-to-Pay of End-Users: A Survey Analysis on Automated Vehicles," Sustainability, MDPI, vol. 13(23), pages 1-12, November.
    5. Peng Jing & Gang Xu & Yuexia Chen & Yuji Shi & Fengping Zhan, 2020. "The Determinants behind the Acceptance of Autonomous Vehicles: A Systematic Review," Sustainability, MDPI, vol. 12(5), pages 1-26, February.
    6. Yavuz, Yigit Can, 2024. "Exploring university students’ acceptability of autonomous vehicles and urban air mobility," Journal of Air Transport Management, Elsevier, vol. 115(C).
    7. Zhao, Jinjing & Su, Yiming & Fang, Mingjie & Su, Miao, 2024. "Embracing new energy vehicles: An empirical examination of female consumer perspectives," Journal of Retailing and Consumer Services, Elsevier, vol. 80(C).
    8. Singha Chaveesuk & Wornchanok Chaiyasoonthorn & Nayika Kamales & Zdzislawa Dacko-Pikiewicz & Wiesław Liszewski & Bilal Khalid, 2023. "Evaluating the Determinants of Consumer Adoption of Autonomous Vehicles in Thailand—An Extended UTAUT Model," Energies, MDPI, vol. 16(2), pages 1-22, January.
    9. Eun-Jung Kim & Jinkyung Jenny Kim & Sang-Ho Han, 2021. "Understanding Student Acceptance of Online Learning Systems in Higher Education: Application of Social Psychology Theories with Consideration of User Innovativeness," Sustainability, MDPI, vol. 13(2), pages 1-14, January.
    10. Nastjuk, Ilja & Herrenkind, Bernd & Marrone, Mauricio & Brendel, Alfred Benedikt & Kolbe, Lutz 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, Elsevier, vol. 161(C).
    11. Koh, Le Yi & Yuen, Kum Fai, 2023. "Public acceptance of autonomous vehicles: Examining the joint influence of perceived vehicle performance and intelligent in-vehicle interaction quality," Transportation Research Part A: Policy and Practice, Elsevier, vol. 178(C).
    12. Benoît Lécureux & Adrien Bonnet & Ouassim Manout & Jaâfar Berrada & Louafi Bouzouina, 2022. "Acceptance of Shared Autonomous Vehicles: A Literature Review of stated choice experiments," Working Papers hal-03814947, HAL.
    13. Kyunam Kim, 2024. "An Input–Output Analysis for the Economic Potential of a New Convergence Industry: A Focus on the Autonomous Vehicle Sector in South Korea," Sustainability, MDPI, vol. 16(20), pages 1-21, October.
    14. Hasan, Rajibul & Lowe, Ben & Petrovici, Dan, 2020. "Consumer adoption of pro-poor service innovations in subsistence marketplaces," Journal of Business Research, Elsevier, vol. 121(C), pages 461-475.
    15. Catherine Viot & Caroline Bayart & Agnes Lancini, 2017. "The Consumer Intention to Adopt Smart Connected-Products: Does the Category Matter?," Post-Print hal-01991186, HAL.
    16. Lindgren, Thomas & Pink, Sarah & Fors, Vaike, 2021. "Fore-sighting autonomous driving - An Ethnographic approach," Technological Forecasting and Social Change, Elsevier, vol. 173(C).
    17. Wenyao Zhang & Qingpu Zhang, 2017. "Exploring Antecedent Difference between Early and Late Adopters of Disruptive Innovation in E-business Microcredit Context: Evidence from China," International Journal of Innovation and Technology Management (IJITM), World Scientific Publishing Co. Pte. Ltd., vol. 14(06), pages 1-29, December.
    18. Barbour, Natalia & Menon, Nikhil & Zhang, Yu & Mannering, Fred, 2019. "Shared automated vehicles: A statistical analysis of consumer use likelihoods and concerns," Transport Policy, Elsevier, vol. 80(C), pages 86-93.
    19. Lokesh Jasrai, 2014. "Measuring Mobile Telecom Service Innovativeness Among Youth," Paradigm, , vol. 18(1), pages 103-116, June.
    20. Pamela D. Morrison & John H. Roberts & Eric von Hippel, 2000. "Determinants of User Innovation and Innovation Sharing in a Local Market," Management Science, INFORMS, vol. 46(12), pages 1513-1527, December.

    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:15:y:2023:i:6:p:5028-:d:1094988. 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.