IDEAS home Printed from https://ideas.repec.org/a/eee/jotrge/v102y2022ics0966692322000849.html
   My bibliography  Save this article

Examining motivations for owning autonomous vehicles: Implications for land use and transportation

Author

Listed:
  • Tao, Tao
  • Cao, Jason

Abstract

Illustrating the associations between built environment characteristics and autonomous vehicle (AV) ownership helps policymakers understand where AVs emerge first and their impacts on society. However, few studies have addressed interest in AV ownership from the spatial perspective. Using regional travel survey data from the Twin Cities, we applied the gradient boosting decision tree method to test three hypotheses (diffusion of innovation, efficiency, and modal substitution) underlying the relationships between respondents' interest in owning AVs and its correlates. Results showed that the innovation-diffusion hypothesis dominates the motivations for owning AVs, followed by preference for efficiency and then modal substitution. However, its associations with built environment variables suggest more of preference for efficiency than of diffusion of innovation and modal substitution. Population density, road connectivity, and land use entropy are negatively associated with the interest. The results provide suggestions to address the externalities of AVs in different areas.

Suggested Citation

  • Tao, Tao & Cao, Jason, 2022. "Examining motivations for owning autonomous vehicles: Implications for land use and transportation," Journal of Transport Geography, Elsevier, vol. 102(C).
    • Handle: RePEc:eee:jotrge:v:102:y:2022:i:c:s0966692322000849
    DOI: 10.1016/j.jtrangeo.2022.103361
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0966692322000849
    Download Restriction: no
    File URL: https://libkey.io/10.1016/j.jtrangeo.2022.103361?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
    ---><---

    References listed on IDEAS

    as
    1. Prateek Bansal & Kara M. Kockelman, 2018. "Are we ready to embrace connected and self-driving vehicles? A case study of Texans," Transportation, Springer, vol. 45(2), pages 641-675, March.
    2. Reid Ewing & Robert Cervero, 2010. "Travel and the Built Environment," Journal of the American Planning Association, Taylor & Francis Journals, vol. 76(3), pages 265-294.
    3. Mokhtarian, Patricia L. & Salomon, Ilan, 2001. "How derived is the demand for travel? Some conceptual and measurement considerations," Transportation Research Part A: Policy and Practice, Elsevier, vol. 35(8), pages 695-719, September.
    4. Mokhtarian, P.L., 2005. "Travel as a desired end, not just a means," Transportation Research Part A: Policy and Practice, Elsevier, vol. 39(2-3), pages 93-96.
    5. William P. Anderson & Lata Chatterjee & T.R. Lakshmanan, 2003. "E‐commerce, Transportation, and Economic Geography," Growth and Change, Wiley Blackwell, vol. 34(4), pages 415-432, September.
    6. Daniel W. Apley & Jingyu Zhu, 2020. "Visualizing the effects of predictor variables in black box supervised learning models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 82(4), pages 1059-1086, September.
    7. Nodjomian, Adam T. & Kockelman, Kara, 2019. "How does the built environment affect interest in the ownership and use of self-driving vehicles?," Journal of Transport Geography, Elsevier, vol. 78(C), pages 115-134.
    8. Xu, Yiming & Yan, Xiang & Liu, Xinyu & Zhao, Xilei, 2021. "Identifying key factors associated with ridesplitting adoption rate and modeling their nonlinear relationships," Transportation Research Part A: Policy and Practice, Elsevier, vol. 144(C), pages 170-188.
    9. Robert W. Wassmer, 2006. "The Influence of Local Urban Containment Policies and Statewide Growth Management on the Size of United States Urban Areas," Journal of Regional Science, Wiley Blackwell, vol. 46(1), pages 25-65, February.
    10. Ding, Chuan & Cao, Xinyu (Jason) & Næss, Petter, 2018. "Applying gradient boosting decision trees to examine non-linear effects of the built environment on driving distance in Oslo," Transportation Research Part A: Policy and Practice, Elsevier, vol. 110(C), pages 107-117.
    11. 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.
    12. Pettigrew, Simone & Dana, Liyuwork Mitiku & Norman, Richard, 2019. "Clusters of potential autonomous vehicles users according to propensity to use individual versus shared vehicles," Transport Policy, Elsevier, vol. 76(C), pages 13-20.
    13. Nadafianshahamabadi, Razieh & Tayarani, Mohammad & Rowangould, Gregory, 2021. "A closer look at urban development under the emergence of autonomous vehicles: Traffic, land use and air quality impacts," Journal of Transport Geography, Elsevier, vol. 94(C).
    14. 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).
    15. White, Lee V. & Sintov, Nicole D., 2017. "You are what you drive: Environmentalist and social innovator symbolism drives electric vehicle adoption intentions," Transportation Research Part A: Policy and Practice, Elsevier, vol. 99(C), pages 94-113.
    16. 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.
    17. Zhen, Feng & Du, Xiaojuan & Cao, Jason & Mokhtarian, Patricia L., 2018. "The association between spatial attributes and e-shopping in the shopping process for search goods and experience goods: Evidence from Nanjing," Journal of Transport Geography, Elsevier, vol. 66(C), pages 291-299.
    18. Yang, Linchuan & Ao, Yibin & Ke, Jintao & Lu, Yi & Liang, Yuan, 2021. "To walk or not to walk? Examining non-linear effects of streetscape greenery on walking propensity of older adults," Journal of Transport Geography, Elsevier, vol. 94(C).
    19. Aggelos Soteropoulos & Martin Berger & Francesco Ciari, 2019. "Impacts of automated vehicles on travel behaviour and land use: an international review of modelling studies," Transport Reviews, Taylor & Francis Journals, vol. 39(1), pages 29-49, January.
    20. Yang, Jiawen & Cao, Jason & Zhou, Yufei, 2021. "Elaborating non-linear associations and synergies of subway access and land uses with urban vitality in Shenzhen," Transportation Research Part A: Policy and Practice, Elsevier, vol. 144(C), pages 74-88.
    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. Yin, Chun & Cao, Jason & Sun, Bindong & Liu, Jiahang, 2023. "Exploring built environment correlates of walking for different purposes: Evidence for substitution," Journal of Transport Geography, Elsevier, vol. 106(C).
    2. Lixun Liu & Yujiang Wang & Robin Hickman, 2023. "How Rail Transit Makes a Difference in People’s Multimodal Travel Behaviours: An Analysis with the XGBoost Method," Land, MDPI, vol. 12(3), pages 1-23, March.

    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. Tao, Tao & Cao, Jason, 2023. "Exploring nonlinear and collective influences of regional and local built environment characteristics on travel distances by mode," Journal of Transport Geography, Elsevier, vol. 109(C).
    2. Shao, Qifan & Zhang, Wenjia & Cao, Xinyu (Jason) & Yang, Jiawen, 2023. "Built environment interventions for emission mitigation: A machine learning analysis of travel-related CO2 in a developing city," Journal of Transport Geography, Elsevier, vol. 110(C).
    3. Hu, Songhua & Xiong, Chenfeng & Chen, Peng & Schonfeld, Paul, 2023. "Examining nonlinearity in population inflow estimation using big data: An empirical comparison of explainable machine learning models," Transportation Research Part A: Policy and Practice, Elsevier, vol. 174(C).
    4. Yin, Chun & Cao, Jason & Sun, Bindong & Liu, Jiahang, 2023. "Exploring built environment correlates of walking for different purposes: Evidence for substitution," Journal of Transport Geography, Elsevier, vol. 106(C).
    5. Yang, Hongtai & Luo, Peng & Li, Chaojing & Zhai, Guocong & Yeh, Anthony G.O., 2023. "Nonlinear effects of fare discounts and built environment on ridesplitting adoption rates," Transportation Research Part A: Policy and Practice, Elsevier, vol. 169(C).
    6. Gao, Kun & Yang, Ying & Gil, Jorge & Qu, Xiaobo, 2023. "Data-driven interpretation on interactive and nonlinear effects of the correlated built environment on shared mobility," Journal of Transport Geography, Elsevier, vol. 110(C).
    7. Ding, Chuan & Cao, Xinyu & Yu, Bin & Ju, Yang, 2021. "Non-linear associations between zonal built environment attributes and transit commuting mode choice accounting for spatial heterogeneity," Transportation Research Part A: Policy and Practice, Elsevier, vol. 148(C), pages 22-35.
    8. 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.
    9. Li, Zhitao & Tang, Jinjun & Zhao, Chuyun & Gao, Fan, 2023. "Improved centrality measure based on the adapted PageRank algorithm for urban transportation multiplex networks," Chaos, Solitons & Fractals, Elsevier, vol. 167(C).
    10. Shi, Kunbo & De Vos, Jonas & Cheng, Long & Yang, Yongchun & Witlox, Frank, 2021. "The influence of the built environment on online purchases of intangible services: Examining the mediating role of online purchase attitudes," Transport Policy, Elsevier, vol. 114(C), pages 116-126.
    11. Vale, David S., 2013. "Does commuting time tolerance impede sustainable urban mobility? Analysing the impacts on commuting behaviour as a result of workplace relocation to a mixed-use centre in Lisbon," Journal of Transport Geography, Elsevier, vol. 32(C), pages 38-48.
    12. Yang, Hongtai & Zheng, Rong & Li, Xuan & Huo, Jinghai & Yang, Linchuan & Zhu, Tong, 2022. "Nonlinear and threshold effects of the built environment on e-scooter sharing ridership," Journal of Transport Geography, Elsevier, vol. 104(C).
    13. Limon Barua & Bo Zou & Yan Zhou & Yulin Liu, 2023. "Modeling household online shopping demand in the U.S.: a machine learning approach and comparative investigation between 2009 and 2017," Transportation, Springer, vol. 50(2), pages 437-476, April.
    14. Zhao, Xiaoyun & Susilo, Yusak O. & Pernestål, Anna, 2022. "The dynamic and long-term changes of automated bus service adoption," Transportation Research Part A: Policy and Practice, Elsevier, vol. 155(C), pages 450-463.
    15. Tianpei Tang & Xiwei Wang & Jianbing Wu & Meining Yuan & Yuntao Guo & Xunqian Xu, 2022. "Determinants and the Moderating Effects of Individual Characteristics on Autonomous Vehicle Adoption in China," IJERPH, MDPI, vol. 20(1), pages 1-17, December.
    16. Du, Manqing & Zhang, Tingru & Liu, Jinting & Xu, Zhigang & Liu, Peng, 2022. "Rumors in the air? Exploring public misconceptions about automated vehicles," Transportation Research Part A: Policy and Practice, Elsevier, vol. 156(C), pages 237-252.
    17. Liang Guo & Shuo Yang & Yuqing Peng & Man Yuan, 2023. "Examining the Nonlinear Effects of Residential and Workplace-built Environments on Active Travel in Short-Distance: A Random Forest Approach," IJERPH, MDPI, vol. 20(3), pages 1-21, January.
    18. Jindo Jeong & Jiwon Lee & Tae‐Hyoung Tommy Gim, 2022. "Travel mode choice as a representation of travel utility: A multilevel approach reflecting the hierarchical structure of trip, individual, and neighborhood characteristics," Papers in Regional Science, Wiley Blackwell, vol. 101(3), pages 745-765, June.
    19. Sharma, Ishant & Mishra, Sabyasachee, 2022. "Quantifying the consumer’s dependence on different information sources on acceptance of autonomous vehicles," Transportation Research Part A: Policy and Practice, Elsevier, vol. 160(C), pages 179-203.
    20. Hassan, Hany M. & Ferguson, Mark R. & Vrkljan, Brenda & Newbold, Bruce & Razavi, Saiedeh, 2021. "Older adults and their willingness to use semi and fully autonomous vehicles: A structural equation analysis11Revised manuscript prepared for publication at the special issue in Journal of Transport G," Journal of Transport Geography, Elsevier, vol. 95(C).

    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:jotrge:v:102:y:2022:i:c:s0966692322000849. 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: https://www.journals.elsevier.com/journal-of-transport-geography .

    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.