IDEAS home Printed from https://ideas.repec.org/a/eee/transa/v124y2019icp549-556.html
   My bibliography  Save this article

Autonomous vehicles, risk perceptions and insurance demand: An individual survey in China

Author

Listed:
  • Xu, Xian
  • Fan, Chiang-Ku

Abstract

Based on an online survey with 1164 participants, this paper investigates the risk perceptions and anticipation of insurance demand for autonomous vehicles in the Chinese market. The findings reveal that autonomous vehicles are highly familiar and have a positive impression in China. Of the respondents, 42.35% and 45.28% expect lower risk and lower insurance premiums for autonomous vehicles, respectively. By using one-way analyses of variance, this paper further examines the statistical effects of perception of autonomous vehicles, insurance purchases and claim experiences as well as personal information on responses to risk perception and insurance anticipation. Several significant factors were found that correlate with each other. Both the understanding of autonomous vehicles and personal information affect risk perception of autonomous vehicles, all of which collectively determine the anticipation of insurance demand for autonomous vehicles.

Suggested Citation

  • Xu, Xian & Fan, Chiang-Ku, 2019. "Autonomous vehicles, risk perceptions and insurance demand: An individual survey in China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 124(C), pages 549-556.
    • Handle: RePEc:eee:transa:v:124:y:2019:i:c:p:549-556
    DOI: 10.1016/j.tra.2018.04.009
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0965856417310595
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.tra.2018.04.009?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Fagnant, Daniel J. & Kockelman, Kara, 2015. "Preparing a nation for autonomous vehicles: opportunities, barriers and policy recommendations," Transportation Research Part A: Policy and Practice, Elsevier, vol. 77(C), pages 167-181.
    2. Ming‐Chou Ho & Daigee Shaw & Shuyeu Lin & Yao‐Chu Chiu, 2008. "How Do Disaster Characteristics Influence Risk Perception?," Risk Analysis, John Wiley & Sons, vol. 28(3), pages 635-643, June.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Foroughi, Behzad & Nhan, Pham Viet & Iranmanesh, Mohammad & Ghobakhloo, Morteza & Nilashi, Mehrbakhsh & Yadegaridehkordi, Elaheh, 2023. "Determinants of intention to use autonomous vehicles: Findings from PLS-SEM and ANFIS," Journal of Retailing and Consumer Services, Elsevier, vol. 70(C).
    2. Wang, Fei & Zhang, Zhentai & Lin, Shoufu, 2023. "Purchase intention of Autonomous vehicles and industrial Policies: Evidence from a national survey in China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 173(C).
    3. Yoo, Sunbin & Kumagai, Junya & Kawabata, Yuta & Keeley, Alexander & Managi, Shunsuke, 2021. "Willingness to Buy and/or Pay Disparity: Evidence from Fully Autonomous Vehicles," MPRA Paper 108882, University Library of Munich, Germany.
    4. Wu, Jingwen & Liao, Hua & Wang, Jin-Wei, 2020. "Analysis of consumer attitudes towards autonomous, connected, and electric vehicles: A survey in China," Research in Transportation Economics, Elsevier, vol. 80(C).
    5. Guo, Yuntao & Souders, Dustin & Labi, Samuel & Peeta, Srinivas & Benedyk, Irina & Li, Yujie, 2021. "Paving the way for autonomous Vehicles: Understanding autonomous vehicle adoption and vehicle fuel choice under user heterogeneity," Transportation Research Part A: Policy and Practice, Elsevier, vol. 154(C), pages 364-398.
    6. Limin Tan & Changxi Ma & Xuecai Xu & Jin Xu, 2019. "Choice Behavior of Autonomous Vehicles Based on Logistic Models," Sustainability, MDPI, vol. 12(1), pages 1-16, December.
    7. Zhang, Lixuan & Yencha, Christopher, 2022. "Examining perceptions towards hiring algorithms," Technology in Society, Elsevier, vol. 68(C).
    8. Demeulenaere, Xavier, 2020. "How challenges of human reliability will hinder the deployment of semi-autonomous vehicles," Technological Forecasting and Social Change, Elsevier, vol. 157(C).
    9. Md. Mokhlesur Rahman & Jean-Claude Thill, 2023. "What Drives People’s Willingness to Adopt Autonomous Vehicles? A Review of Internal and External Factors," Sustainability, MDPI, vol. 15(15), pages 1-29, July.
    10. Andrew Chapman & Hidemichi Fujii, 2022. "The Potential Role of Flying Vehicles in Progressing the Energy Transition," Energies, MDPI, vol. 15(19), pages 1-11, October.
    11. Darren Shannon & Tim Jannusch & Florian David‐Spickermann & Martin Mullins & Martin Cunneen & Finbarr Murphy, 2021. "Connected and autonomous vehicle injury loss events: Potential risk and actuarial considerations for primary insurers," Risk Management and Insurance Review, American Risk and Insurance Association, vol. 24(1), pages 5-35, March.
    12. Chikaraishi, Makoto & Khan, Diana & Yasuda, Banri & Fujiwara, Akimasa, 2020. "Risk perception and social acceptability of autonomous vehicles: A case study in Hiroshima, Japan," Transport Policy, Elsevier, vol. 98(C), pages 105-115.
    13. Nader Zali & Sara Amiri & Tan Yigitcanlar & Ali Soltani, 2022. "Autonomous Vehicle Adoption in Developing Countries: Futurist Insights," Energies, MDPI, vol. 15(22), pages 1-26, November.

    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. Loredana Antronico & Roberto Coscarelli & Francesco De Pascale & Giovanni Gull?, 2018. "La comunicazione del rischio e la percezione pubblica dei disastri: il caso studio della frana di Maierato (Calabria, Italia)," PRISMA Economia - Societ? - Lavoro, FrancoAngeli Editore, vol. 2018(3), pages 9-29.
    2. Jones, Lindsey & d'Errico, Marco, 2019. "Whose resilience matters? Like-for-like comparison of objective and subjective evaluations of resilience," World Development, Elsevier, vol. 124(C), pages 1-1.
    3. Xu, Zhengtian & Yin, Yafeng & Zha, Liteng, 2017. "Optimal parking provision for ride-sourcing services," Transportation Research Part B: Methodological, Elsevier, vol. 105(C), pages 559-578.
    4. Tscharaktschiew, Stefan & Reimann, Felix, 2021. "On employer-paid parking and parking (cash-out) policy: A formal synthesis of different perspectives," Transport Policy, Elsevier, vol. 110(C), pages 499-516.
    5. Kolarova, Viktoriya & Steck, Felix & Bahamonde-Birke, Francisco J., 2019. "Assessing the effect of autonomous driving on value of travel time savings: A comparison between current and future preferences," Transportation Research Part A: Policy and Practice, Elsevier, vol. 129(C), pages 155-169.
    6. Pons-Prats, Jordi & Živojinović, Tanja & Kuljanin, Jovana, 2022. "On the understanding of the current status of urban air mobility development and its future prospects: Commuting in a flying vehicle as a new paradigm," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 166(C).
    7. Gurumurthy, Krishna Murthy & Kockelman, Kara M., 2021. "Impacts of shared automated vehicles on airport access and operations, with opportunities for revenue recovery: Case Study of Austin, Texas," Research in Transportation Economics, Elsevier, vol. 90(C).
    8. Nordhoff, Sina & Stapel, Jork & van Arem, Bart & Happee, Riender, 2020. "Passenger opinions of the perceived safety and interaction with automated shuttles: A test ride study with ‘hidden’ safety steward," Transportation Research Part A: Policy and Practice, Elsevier, vol. 138(C), pages 508-524.
    9. Delphine Boutin & Laurène Petifour & Haris Megzari, 2022. "Instability of preferences due to Covid-19 Crisis and emotions: a natural experiment from urban Burkina Faso," Working Papers hal-03623601, HAL.
    10. Kassens-Noor, Eva & Cai, Meng & Kotval-Karamchandani, Zeenat & Decaminada, Travis, 2021. "Autonomous vehicles and mobility for people with special needs," Transportation Research Part A: Policy and Practice, Elsevier, vol. 150(C), pages 385-397.
    11. KASHIWAGI Yuzuka & TODO Yasuyuki, 2022. "Trade Disruption and Risk Perception," Discussion papers 22086, Research Institute of Economy, Trade and Industry (RIETI).
    12. Tianlong Yu & Hao Yang & Xiaowei Luo & Yifeng Jiang & Xiang Wu & Jingqi Gao, 2021. "Scientometric Analysis of Disaster Risk Perception: 2000–2020," IJERPH, MDPI, vol. 18(24), pages 1-19, December.
    13. Zhang, Fang & Lu, Jian & Hu, Xiaojian & Meng, Qiang, 2023. "Integrated deployment of dedicated lane and roadside unit considering uncertain road capacity under the mixed-autonomy traffic environment," Transportation Research Part B: Methodological, Elsevier, vol. 174(C).
    14. Samuel Nii Ardey Codjoe & Vivian Adams Nabie, 2014. "Climate Change and Cerebrospinal Meningitis in the Ghanaian Meningitis Belt," IJERPH, MDPI, vol. 11(7), pages 1-17, July.
    15. 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.
    16. Kevin Fox Gotham & Richard Campanella & Katie Lauve‐Moon & Bradford Powers, 2018. "Hazard Experience, Geophysical Vulnerability, and Flood Risk Perceptions in a Postdisaster City, the Case of New Orleans," Risk Analysis, John Wiley & Sons, vol. 38(2), pages 345-356, February.
    17. Kalra, Nidhi & Paddock, Susan M., 2016. "Driving to safety: How many miles of driving would it take to demonstrate autonomous vehicle reliability?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 94(C), pages 182-193.
    18. Gruber, Mario, 2020. "An evolutionary perspective on adoption-diffusion theory," Journal of Business Research, Elsevier, vol. 116(C), pages 535-541.
    19. Mendonca, Marcos Barreto de & Gullo, Fernanda Teles, 2020. "Landslide risk perception survey in Angra dos Reis (Rio de Janeiro, southeastern Brazil): A contribution to support planning of non structural measures," Land Use Policy, Elsevier, vol. 91(C).
    20. Saeed, Tariq Usman & Burris, Mark W. & Labi, Samuel & Sinha, Kumares C., 2020. "An empirical discourse on forecasting the use of autonomous vehicles using consumers’ preferences," Technological Forecasting and Social Change, Elsevier, vol. 158(C).

    More about this item

    Statistics

    Access and download statistics

    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:eee:transa:v:124:y:2019:i:c:p:549-556. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/547/description#description .

    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.