IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v17y2025i4p1614-d1591997.html
   My bibliography  Save this article

Breaking Commuting Habits: Are Unexpected Urban Disruptions an Opportunity for Shared Autonomous Vehicles?

Author

Listed:
  • Alessandro La Delfa

    (School of Economics and Management, Tongji University, Shanghai 200092, China)

  • Zheng Han

    (School of Economics and Management, Tongji University, Shanghai 200092, China)

Abstract

While extensive research has examined how major life events affect travel habits, less attention has been paid to the impact of minor environmental changes on commuting behavior, particularly regarding shared autonomous vehicles (SAVs). This study investigated how daily disruptions and incremental environmental changes influence commuter behavior patterns and SAV adoption in Shanghai, applying the theory of interpersonal behavior framework. The study surveyed 517 Shanghai residents, examining travel satisfaction, commuting habits, psychological factors (such as habit strength and satisfaction), and attitudes towards SAVs. Structural equation modeling was employed to test hypotheses about psychological factors influencing SAV adoption, while logistic regression analyzed how these factors affected mode choice across different disruption contexts. Analysis revealed that psychological factors, particularly habit and satisfaction, were stronger predictors of SAV adoption than attitude-based factors. Route obstructions and workplace relocations significantly increased SAV consideration. Even minor, recurring disruptions, such as construction zones, showed strong effects on commuting behavior, supporting the habit discontinuity hypothesis and emphasizing the importance of minor disruptions in driving behavioral change. The study extends the theory of interpersonal behavior by integrating habit discontinuity theory to explain how minor disruptions drive SAV adoption. This research provides actionable insights for urban planners and policymakers, recommending that SAV trials and targeted interventions be implemented during infrastructure changes or other commuting disruptions to promote SAV adoption and foster more sustainable transportation systems.

Suggested Citation

  • Alessandro La Delfa & Zheng Han, 2025. "Breaking Commuting Habits: Are Unexpected Urban Disruptions an Opportunity for Shared Autonomous Vehicles?," Sustainability, MDPI, vol. 17(4), pages 1-18, February.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:4:p:1614-:d:1591997
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/17/4/1614/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/17/4/1614/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Cristian Domarchi & Alejandro Tudela & Angélica González, 2008. "Effect of attitudes, habit and affective appraisal on mode choice: an application to university workers," Transportation, Springer, vol. 35(5), pages 585-599, August.
    2. Stephane Hess & John Polak & Andrew Daly & Geoffrey Hyman, 2007. "Flexible substitution patterns in models of mode and time of day choice: new evidence from the UK and the Netherlands," Transportation, Springer, vol. 34(2), pages 213-238, March.
    3. Michael L. Anderson, 2014. "Subways, Strikes, and Slowdowns: The Impacts of Public Transit on Traffic Congestion," American Economic Review, American Economic Association, vol. 104(9), pages 2763-2796, September.
    4. Ye, Jianhong & Wang, Daoge & Li, Xi & Axhausen, Kay W. & Jin, Yong, 2021. "Assessing one-way carsharing’s impacts on vehicle ownership: Evidence from Shanghai with an international comparison," Transportation Research Part A: Policy and Practice, Elsevier, vol. 150(C), pages 16-32.
    5. Small, Kenneth A, 1982. "The Scheduling of Consumer Activities: Work Trips," American Economic Review, American Economic Association, vol. 72(3), pages 467-479, June.
    6. Ajzen, Icek, 1991. "The theory of planned behavior," Organizational Behavior and Human Decision Processes, Elsevier, vol. 50(2), pages 179-211, December.
    7. Zhong, Lin & Zhang, Kenan & (Marco) Nie, Yu & Xu, Jiuping, 2020. "Dynamic carpool in morning commute: Role of high-occupancy-vehicle (HOV) and high-occupancy-toll (HOT) lanes," Transportation Research Part B: Methodological, Elsevier, vol. 135(C), pages 98-119.
    8. Anable, Jillian, 2005. "'Complacent Car Addicts' or 'Aspiring Environmentalists'? Identifying travel behaviour segments using attitude theory," Transport Policy, Elsevier, vol. 12(1), pages 65-78, January.
    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. Rico Krueger & Akshay Vij & Taha H. Rashidi, 2018. "Normative beliefs and modality styles: a latent class and latent variable model of travel behaviour," Transportation, Springer, vol. 45(3), pages 789-825, May.
    2. Thorhauge, Mikkel & Swait, Joffre & Cherchi, Elisabetta, 2020. "The habit-driven life: Accounting for inertia in departure time choices for commuting trips," Transportation Research Part A: Policy and Practice, Elsevier, vol. 133(C), pages 272-289.
    3. Gustav Bösehans & Ian Walker, 2020. "Do supra-modal traveller types exist? A travel behaviour market segmentation using Goal framing theory," Transportation, Springer, vol. 47(1), pages 243-273, February.
    4. Fu, Xuemei & Juan, Zhicai, 2017. "Exploring the psychosocial factors associated with public transportation usage and examining the “gendered” difference," Transportation Research Part A: Policy and Practice, Elsevier, vol. 103(C), pages 70-82.
    5. de Jong, Gerard & Kouwenhoven, Marco & Ruijs, Kim & van Houwe, Pieter & Borremans, Dana, 2016. "A time-period choice model for road freight transport in Flanders based on stated preference data," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 86(C), pages 20-31.
    6. Chen, Ching-Fu & Lai, Wen-Tai, 2011. "The effects of rational and habitual factors on mode choice behaviors in a motorcycle-dependent region: Evidence from Taiwan," Transport Policy, Elsevier, vol. 18(5), pages 711-718, September.
    7. Sascha von Behren & Lisa Bönisch & Ulrich Niklas & Bastian Chlond, 2020. "Revealing Motives for Car Use in Modern Cities—A Case Study from Berlin and San Francisco," Sustainability, MDPI, vol. 12(13), pages 1-18, June.
    8. Vinayak, Pragun & Dias, Felipe F. & Astroza, Sebastian & Bhat, Chandra R. & Pendyala, Ram M. & Garikapati, Venu M., 2018. "Accounting for multi-dimensional dependencies among decision-makers within a generalized model framework: An application to understanding shared mobility service usage levels," Transport Policy, Elsevier, vol. 72(C), pages 129-137.
    9. Mao Ye & Yajing Chen & Guixin Yang & Bo Wang & Qizhou Hu, 2020. "Mixed Logit Models for Travelers’ Mode Shifting Considering Bike-Sharing," Sustainability, MDPI, vol. 12(5), pages 1-18, March.
    10. Ghader, Sepehr & Carrion, Carlos & Zhang, Lei, 2019. "Autoregressive continuous logit: Formulation and application to time-of-day choice modeling," Transportation Research Part B: Methodological, Elsevier, vol. 123(C), pages 240-257.
    11. De Vos, Jonas & Derudder, Ben & Van Acker, Veronique & Witlox, Frank, 2012. "Reducing car use: changing attitudes or relocating? The influence of residential dissonance on travel behavior," Journal of Transport Geography, Elsevier, vol. 22(C), pages 1-9.
    12. Uba, Chijioke Dike & Chatzidakis, Andreas, 2016. "Understanding engagement and disengagement from pro-environmental behaviour: The role of neutralization and affirmation techniques in maintaining persistence in and desistance from car use," Transportation Research Part A: Policy and Practice, Elsevier, vol. 94(C), pages 278-294.
    13. Zhu, Charles & Zhu, Yiliang & Lu, Rongzhu & He, Ren & Xia, Zhaolin, 2012. "Perceptions and aspirations for car ownership among Chinese students attending two universities in the Yangtze Delta, China," Journal of Transport Geography, Elsevier, vol. 24(C), pages 315-323.
    14. Grischkat, Sylvie & Hunecke, Marcel & Böhler, Susanne & Haustein, Sonja, 2014. "Potential for the reduction of greenhouse gas emissions through the use of mobility services," Transport Policy, Elsevier, vol. 35(C), pages 295-303.
    15. Yoon-Young Chun & Mitsutaka Matsumoto & Kiyotaka Tahara & Kenichiro Chinen & Hideki Endo, 2019. "Exploring Factors Affecting Car Sharing Use Intention in the Southeast-Asia Region: A Case Study in Java, Indonesia," Sustainability, MDPI, vol. 11(18), pages 1-26, September.
    16. Mikkel Thorhauge & Elisabetta Cherchi & Joan L. Walker & Jeppe Rich, 2019. "The role of intention as mediator between latent effects and behavior: application of a hybrid choice model to study departure time choices," Transportation, Springer, vol. 46(4), pages 1421-1445, August.
    17. De Vos, Jonas, 2018. "Do people travel with their preferred travel mode? Analysing the extent of travel mode dissonance and its effect on travel satisfaction," Transportation Research Part A: Policy and Practice, Elsevier, vol. 117(C), pages 261-274.
    18. Brand, Christian & Schwanen, Tim & Anable, Jillian, 2020. "‘Online Omnivores’ or ‘Willing but struggling’? Identifying online grocery shopping behavior segments using attitude theory," Journal of Retailing and Consumer Services, Elsevier, vol. 57(C).
    19. Khan, Mubassira & Machemehl, Randy, 2017. "Commercial vehicles time of day choice behavior in urban areas," Transportation Research Part A: Policy and Practice, Elsevier, vol. 102(C), pages 68-83.
    20. Sottile, Eleonora & Giacchetti, Tommaso & Tuveri, Giovanni & Piras, Francesco & Calli, Daniele & Concas, Vittoria & Zamberlan, Leonardo & Meloni, Italo & Carrese, Stefano, 2021. "An innovative GPS smartphone based strategy for university mobility management: A case study at the University of RomaTre, Italy," Research in Transportation Economics, Elsevier, vol. 85(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:gam:jsusta:v:17:y:2025:i:4:p:1614-:d:1591997. 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.