IDEAS home Printed from https://ideas.repec.org/p/eti/dpaper/22017.html
   My bibliography  Save this paper

Achieving Inclusive Transportation: Fully Automated Vehicles with Social Support

Author

Listed:
  • Sunbin YOO
  • KUMAGAI Junya
  • KAWABATA Yuta
  • MANAGI Shunsuke

Abstract

We provide quantitative evidence of whether a representative sample of the newly introduced fully automatic vehicles (FAVs) are inclusive. We answer this question by examining FAV demand with a focus on natural disaster victims—people who have become physically or mentally challenged due to severe disaster damage, including those with post-traumatic stress disorder. We investigate whether the fear of natural disasters, social support, environmental concerns, the fear of potential accidents, and merits regarding FAVs are motivators of, or hindrances to, purchasing intentions of FAVs. To do so, we acquire a unique dataset covering disaster victims with traumatic disaster damages (12,286 observations in total) and people without such experiences (57,105 observations in total). Then, we construct a multigroup structural estimation model to estimate FAV demand. We conduct estimations of latent and socioeconomic variables which demonstrate people's attitudes. Our findings show that the social support of family, friends, and local authorities is a crucial factor in motivating disaster victims to appreciate and purchase FAVs. The positive impact of social support on appreciating/purchasing FAVs can offset the negative impacts of a fear of natural disasters and accidents, thus enabling more people to enjoy FAVs.

Suggested Citation

  • Sunbin YOO & KUMAGAI Junya & KAWABATA Yuta & MANAGI Shunsuke, 2022. "Achieving Inclusive Transportation: Fully Automated Vehicles with Social Support," Discussion papers 22017, Research Institute of Economy, Trade and Industry (RIETI).
  • Handle: RePEc:eti:dpaper:22017
    as

    Download full text from publisher

    File URL: https://www.rieti.go.jp/jp/publications/dp/22e017.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Chen, Chien-fei & Nelson, Hannah & Xu, Xiaojing & Bonilla, Gregory & Jones, Nicholas, 2021. "Beyond technology adoption: Examining home energy management systems, energy burdens and climate change perceptions during COVID-19 pandemic," Renewable and Sustainable Energy Reviews, Elsevier, vol. 145(C).
    2. David Souder & Akbar Zaheer & Harry Sapienza & Rebecca Ranucci, 2017. "How family influence, socioemotional wealth, and competitive conditions shape new technology adoption," Strategic Management Journal, Wiley Blackwell, vol. 38(9), pages 1774-1790, September.
    3. Gisela Wachinger & Ortwin Renn & Chloe Begg & Christian Kuhlicke, 2013. "The Risk Perception Paradox—Implications for Governance and Communication of Natural Hazards," Risk Analysis, John Wiley & Sons, vol. 33(6), pages 1049-1065, June.
    4. Walker, Joan & Ben-Akiva, Moshe, 2002. "Generalized random utility model," Mathematical Social Sciences, Elsevier, vol. 43(3), pages 303-343, July.
    5. Mohamed, Moataz & Higgins, Christopher D. & Ferguson, Mark & Réquia, Weeberb J., 2018. "The influence of vehicle body type in shaping behavioural intention to acquire electric vehicles: A multi-group structural equation approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 116(C), pages 54-72.
    6. Ashley Nunes & Bryan Reimer & Joseph F. Coughlin, 2018. "People must retain control of autonomous vehicles," Nature, Nature, vol. 556(7700), pages 169-171, April.
    7. Haddak, Mohamed Mouloud & Lefèvre, Marie & Havet, Nathalie, 2016. "Willingness-to-pay for road safety improvement," Transportation Research Part A: Policy and Practice, Elsevier, vol. 87(C), pages 1-10.
    8. Aklin, M. & Bayer, P. & Harish, S.P. & Urpelainen, J., 2018. "Economics of household technology adoption in developing countries: Evidence from solar technology adoption in rural India," Energy Economics, Elsevier, vol. 72(C), pages 35-46.
    9. Sardianou, E. & Genoudi, P., 2013. "Which factors affect the willingness of consumers to adopt renewable energies?," Renewable Energy, Elsevier, vol. 57(C), pages 1-4.
    10. Niu, Zhipeng & Hu, Xiaowei & Qi, Shouming & Yang, Haihua & Wang, Siqing & An, Shi, 2021. "Determinants to parking mode alternatives: A model integrating technology acceptance model and satisfaction–loyalty model," Transportation Research Part A: Policy and Practice, Elsevier, vol. 152(C), pages 216-234.
    11. Yi‐Wen Kung & Sue‐Huei Chen, 2012. "Perception of Earthquake Risk in Taiwan: Effects of Gender and Past Earthquake Experience," Risk Analysis, John Wiley & Sons, vol. 32(9), pages 1535-1546, September.
    12. Wadud, Zia & MacKenzie, Don & Leiby, Paul, 2016. "Help or hindrance? The travel, energy and carbon impacts of highly automated vehicles," Transportation Research Part A: Policy and Practice, Elsevier, vol. 86(C), pages 1-18.
    13. Faber, Koen & van Lierop, Dea, 2020. "How will older adults use automated vehicles? Assessing the role of AVs in overcoming perceived mobility barriers," Transportation Research Part A: Policy and Practice, Elsevier, vol. 133(C), pages 353-363.
    14. Araz Taeihagh & Hazel Si Min Lim, 2019. "Governing autonomous vehicles: emerging responses for safety, liability, privacy, cybersecurity, and industry risks," Transport Reviews, Taylor & Francis Journals, vol. 39(1), pages 103-128, January.
    15. Lai, Wen-Tai & Chen, Ching-Fu, 2011. "Behavioral intentions of public transit passengers--The roles of service quality, perceived value, satisfaction and involvement," Transport Policy, Elsevier, vol. 18(2), pages 318-325, March.
    16. 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.
    17. Nicolás C. Bronfman & Pamela C. Cisternas & Esperanza López-Vázquez & Luis A. Cifuentes, 2016. "Trust and risk perception of natural hazards: implications for risk preparedness in Chile," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 81(1), pages 307-327, March.
    18. Kwan, Calvin Lee, 2012. "Influence of local environmental, social, economic and political variables on the spatial distribution of residential solar PV arrays across the United States," Energy Policy, Elsevier, vol. 47(C), pages 332-344.
    19. Nicolás Bronfman & Pamela Cisternas & Esperanza López-Vázquez & Luis Cifuentes, 2016. "Trust and risk perception of natural hazards: implications for risk preparedness in Chile," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 81(1), pages 307-327, March.
    20. Goldberger, Arthur S, 1972. "Structural Equation Methods in the Social Sciences," Econometrica, Econometric Society, vol. 40(6), pages 979-1001, November.
    21. Shin, Kong Joo & Tada, Naoto & Managi, Shunsuke, 2019. "Consumer demand for fully automated driving technology," Economic Analysis and Policy, Elsevier, vol. 61(C), pages 16-28.
    22. Sanchez, Thomas W., 2008. "Poverty, policy, and public transportation," Transportation Research Part A: Policy and Practice, Elsevier, vol. 42(5), pages 833-841, June.
    23. Lee, Dasom & Hess, David J., 2020. "Regulations for on-road testing of connected and automated vehicles: Assessing the potential for global safety harmonization," Transportation Research Part A: Policy and Practice, Elsevier, vol. 136(C), pages 85-98.
    24. Bansal, Prateek & Kockelman, Kara M., 2017. "Forecasting Americans’ long-term adoption of connected and autonomous vehicle technologies," Transportation Research Part A: Policy and Practice, Elsevier, vol. 95(C), pages 49-63.
    25. Zhou, Fan & Zheng, Zuduo & Whitehead, Jake & Washington, Simon & Perrons, Robert K. & Page, Lionel, 2020. "Preference heterogeneity in mode choice for car-sharing and shared automated vehicles," Transportation Research Part A: Policy and Practice, Elsevier, vol. 132(C), pages 633-650.
    26. James A. Mourey & Jenny G. Olson & Carolyn Yoon, 2017. "Products as Pals: Engaging with Anthropomorphic Products Mitigates the Effects of Social Exclusion," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 44(2), pages 414-431.
    27. 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).
    28. Molin, Eric & Adjenughwure, Kingsley & de Bruyn, Menno & Cats, Oded & Warffemius, Pim, 2020. "Does conducting activities while traveling reduce the value of time? Evidence from a within-subjects choice experiment," Transportation Research Part A: Policy and Practice, Elsevier, vol. 132(C), pages 18-29.
    29. Azim Shariff & Jean-François Bonnefon & Iyad Rahwan, 2017. "Psychological roadblocks to the adoption of self-driving vehicles," Nature Human Behaviour, Nature, vol. 1(10), pages 694-696, October.
    30. Maria Kamargianni & Moshe Ben-Akiva & Amalia Polydoropoulou, 2014. "Incorporating social interaction into hybrid choice models," Transportation, Springer, vol. 41(6), pages 1263-1285, November.
    31. Montoya-Robledo, Valentina & Escovar-Álvarez, Germán, 2020. "Domestic workers’ commutes in Bogotá: Transportation, gender and social exclusion," Transportation Research Part A: Policy and Practice, Elsevier, vol. 139(C), pages 400-411.
    32. Motoaki, Yutaka & Daziano, Ricardo A., 2015. "A hybrid-choice latent-class model for the analysis of the effects of weather on cycling demand," Transportation Research Part A: Policy and Practice, Elsevier, vol. 75(C), pages 217-230.
    33. Manca, Francesco & Sivakumar, Aruna & Daina, Nicolò & Axsen, Jonn & Polak, John W, 2020. "Modelling the influence of peers’ attitudes on choice behaviour: Theory and empirical application on electric vehicle preferences," Transportation Research Part A: Policy and Practice, Elsevier, vol. 140(C), pages 278-298.
    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. Kim, Seheon & Rasouli, Soora, 2022. "The influence of latent lifestyle on acceptance of Mobility-as-a-Service (MaaS): A hierarchical latent variable and latent class approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 159(C), pages 304-319.
    2. Pel, Bonno & Raven, Rob & van Est, Rinie, 2020. "Transitions governance with a sense of direction: synchronization challenges in the case of the dutch ‘Driverless Car’ transition," Technological Forecasting and Social Change, Elsevier, vol. 160(C).
    3. Nicolás C. Bronfman & Pamela C. Cisternas & Paula B. Repetto & Javiera V. Castañeda & Eliana Guic, 2020. "Understanding the Relationship Between Direct Experience and Risk Perception of Natural Hazards," Risk Analysis, John Wiley & Sons, vol. 40(10), pages 2057-2070, October.
    4. Xuemei Fang & Liang Cao & Luyi Zhang & Binbin Peng, 2023. "Risk perception and resistance behavior intention of residents living near chemical industry parks: an empirical analysis in China," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 115(2), pages 1655-1675, January.
    5. Daniela Knuth & Doris Kehl & Lynn Hulse & Silke Schmidt, 2014. "Risk Perception, Experience, and Objective Risk: A Cross‐National Study with European Emergency Survivors," Risk Analysis, John Wiley & Sons, vol. 34(7), pages 1286-1298, July.
    6. Kaijing Xue & Shili Guo & Yi Liu & Shaoquan Liu & Dingde Xu, 2021. "Social Networks, Trust, and Disaster-Risk Perceptions of Rural Residents in a Multi-Disaster Environment: Evidence from Sichuan, China," IJERPH, MDPI, vol. 18(4), pages 1-25, February.
    7. Xing, Yingying & Zhou, Huiyu & Han, Xiao & Zhang, Meng & Lu, Jian, 2022. "What influences vulnerable road users’ perceptions of autonomous vehicles? A comparative analysis of the 2017 and 2019 Pittsburgh surveys," Technological Forecasting and Social Change, Elsevier, vol. 176(C).
    8. Aaditya, Bh. & Rahul, T.M., 2021. "Psychological impacts of COVID-19 pandemic on the mode choice behaviour: A hybrid choice modelling approach," Transport Policy, Elsevier, vol. 108(C), pages 47-58.
    9. 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).
    10. Alipour, M. & Salim, H. & Stewart, Rodney A. & Sahin, Oz, 2020. "Predictors, taxonomy of predictors, and correlations of predictors with the decision behaviour of residential solar photovoltaics adoption: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 123(C).
    11. Qian, Lixian & Yin, Juelin & Huang, Youlin & Liang, Ya, 2023. "The role of values and ethics in influencing consumers’ intention to use autonomous vehicle hailing services," Technological Forecasting and Social Change, Elsevier, vol. 188(C).
    12. 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.
    13. Rejali, Sina & Aghabayk, Kayvan & Esmaeli, Saeed & Shiwakoti, Nirajan, 2023. "Comparison of technology acceptance model, theory of planned behavior, and unified theory of acceptance and use of technology to assess a priori acceptance of fully automated vehicles," Transportation Research Part A: Policy and Practice, Elsevier, vol. 168(C).
    14. Nicolás Bronfman & Paula Repetto & Paola Cordón & Javiera Castañeda & Pamela Cisternas, 2021. "Gender Differences on Psychosocial Factors Affecting COVID-19 Preventive Behaviors," Sustainability, MDPI, vol. 13(11), pages 1-12, May.
    15. Yanbo Zhang & Yibao Wang & Ahmad Bayiz Ahmad & Ashfaq Ahmad Shah & Wen Qing, 2021. "How Do Individual-Level Characteristics Influence Cross-Domain Risk Perceptions Among Chinese Urban Residents?," SAGE Open, , vol. 11(2), pages 21582440211, April.
    16. Marcel Favereau & Luis F. Robledo & María T. Bull, 2020. "Homeostatic representation for risk decision making: a novel multi-method simulation approach for evacuation under volcanic eruption," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 103(1), pages 29-56, August.
    17. Lindgren, Thomas & Pink, Sarah & Fors, Vaike, 2021. "Fore-sighting autonomous driving - An Ethnographic approach," Technological Forecasting and Social Change, Elsevier, vol. 173(C).
    18. 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.
    19. Briguglio, Marie & Formosa, Glenn, 2017. "When households go solar: Determinants of uptake of a Photovoltaic Scheme and policy insights," Energy Policy, Elsevier, vol. 108(C), pages 154-162.
    20. Dubey, Subodh & Sharma, Ishant & Mishra, Sabyasachee & Cats, Oded & Bansal, Prateek, 2022. "A General Framework to Forecast the Adoption of Novel Products: A Case of Autonomous Vehicles," Transportation Research Part B: Methodological, Elsevier, vol. 165(C), pages 63-95.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:eti:dpaper:22017. 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: TANIMOTO, Toko (email available below). General contact details of provider: https://edirc.repec.org/data/rietijp.html .

    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.