IDEAS home Printed from https://ideas.repec.org/a/kap/transp/v49y2022i3d10.1007_s11116-021-10201-8.html
   My bibliography  Save this article

The influence of panel effects and inertia on travel cost elasticities for car use and public transport

Author

Listed:
  • Lissy Paix

    (University of Twente
    LLC.)

  • Abu Toasin Oakil

    (DAT.Mobility)

  • Frank Hofman

    (Rijkswaterstaat WVL)

  • Karst Geurs

    (University of Twente)

Abstract

Studies on the impact of changes in travel costs on car and public transport use are typically based on cross-sectional travel survey data or time series analysis and do not capture intrapersonal variation in travel patterns, which can result in biased cost elasticities. This paper examines the influence of panel effects and inertia in travel behaviour on travel cost sensitiveness, based on four waves of the Mobility Panel for the Netherlands (comprising around 90,000 trips). This paper analyses the monetary costs of travel. Panel effects reflect (within wave) intrapersonal variations in mode choice, based on three-day trip diary data available for each wave. The impact of intrapersonal variation on cost sensitiveness is shown by comparing mode choice models with panel effects (mixed logit mode choice models with error components) and without panel effects (multinomial logit models). Inertia represents variability in mode choice between waves, measured as the effect of mode choice decisions made in a previous wave on the decisions made in the current wave. Additionally, all mode choice models include socio-economic and spatial variables but also mode preferences and life events. The effect of inertia on travel cost elasticities is measured by estimating mixed logit mode choice models with and without inertia effects. The main conclusion is that the inclusion of intrapersonal effects tends to increase cost sensitiveness whereas the inclusion of inertia effects decreases travel cost sensitiveness for car and public transport modes. Car users are identified as inert travellers, whereas public transport users show a lower tendency to maintain their usual mode choice. This paper reveals the inertia effects over four waves of repeated respondent’s data repeated yearly.

Suggested Citation

  • Lissy Paix & Abu Toasin Oakil & Frank Hofman & Karst Geurs, 2022. "The influence of panel effects and inertia on travel cost elasticities for car use and public transport," Transportation, Springer, vol. 49(3), pages 989-1016, June.
  • Handle: RePEc:kap:transp:v:49:y:2022:i:3:d:10.1007_s11116-021-10201-8
    DOI: 10.1007/s11116-021-10201-8
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11116-021-10201-8
    File Function: Abstract
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1007/s11116-021-10201-8?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. María Yáñez & Patricio Mansilla & Juan de Ortúzar, 2010. "The Santiago Panel: measuring the effects of implementing Transantiago," Transportation, Springer, vol. 37(1), pages 125-149, January.
    2. Thomas, Tom & La Paix Puello, Lissy & Geurs, Karst, 2019. "Intrapersonal mode choice variation: Evidence from a four-week smartphone-based travel survey in the Netherlands," Journal of Transport Geography, Elsevier, vol. 76(C), pages 287-300.
    3. Kenneth Train ., 2000. "Halton Sequences for Mixed Logit," Economics Working Papers E00-278, University of California at Berkeley.
    4. Dahl, Carol A., 2012. "Measuring global gasoline and diesel price and income elasticities," Energy Policy, Elsevier, vol. 41(C), pages 2-13.
    5. Víctor Cantillo & Juan de Dios Ortúzar & Huw C. W. L. Williams, 2007. "Modeling Discrete Choices in the Presence of Inertia and Serial Correlation," Transportation Science, INFORMS, vol. 41(2), pages 195-205, May.
    6. Paulley, Neil & Balcombe, Richard & Mackett, Roger & Titheridge, Helena & Preston, John & Wardman, Mark & Shires, Jeremy & White, Peter, 2006. "The demand for public transport: The effects of fares, quality of service, income and car ownership," Transport Policy, Elsevier, vol. 13(4), pages 295-306, July.
    7. Juan De Dios Ortúzar & Jimmy Armoogum & Jean‐Loup Madre & Françoise Potier, 2011. "Continuous Mobility Surveys: The State of Practice," Transport Reviews, Taylor & Francis Journals, vol. 31(3), pages 293-312.
    8. Jou, Rong-Chang & Chen, Ke-Hong, 2013. "An application of cumulative prospect theory to freeway drivers’ route choice behaviours," Transportation Research Part A: Policy and Practice, Elsevier, vol. 49(C), pages 123-131.
    9. Elisabetta Cherchi & Francesco Manca, 2011. "Accounting for inertia in modal choices: some new evidence using a RP/SP dataset," Transportation, Springer, vol. 38(4), pages 679-695, July.
    10. Peer, Stefanie & Knockaert, Jasper & Koster, Paul & Verhoef, Erik T., 2014. "Over-reporting vs. overreacting: Commuters’ perceptions of travel times," Transportation Research Part A: Policy and Practice, Elsevier, vol. 69(C), pages 476-494.
    11. González, Rosa Marina & Marrero, Ángel Simón & Cherchi, Elisabetta, 2017. "Testing for inertia effect when a new tram is implemented," Transportation Research Part A: Policy and Practice, Elsevier, vol. 98(C), pages 150-159.
    12. Kroesen, Maarten, 2014. "Modeling the behavioral determinants of travel behavior: An application of latent transition analysis," Transportation Research Part A: Policy and Practice, Elsevier, vol. 65(C), pages 56-67.
    13. de Haas, M.C. & Scheepers, C.E. & Harms, L.W.J. & Kroesen, M., 2018. "Travel pattern transitions: Applying latent transition analysis within the mobility biographies framework," Transportation Research Part A: Policy and Practice, Elsevier, vol. 107(C), pages 140-151.
    14. Cherchi, Elisabetta & Cirillo, Cinzia & Ortúzar, Juan de Dios, 2017. "Modelling correlation patterns in mode choice models estimated on multiday travel data," Transportation Research Part A: Policy and Practice, Elsevier, vol. 96(C), pages 146-153.
    15. La Paix Puello, Lissy & Olde-Kalter, Marie-José & Geurs, Karst T., 2017. "Measurement of non-random attrition effects on mobility rates using trip diaries data," Transportation Research Part A: Policy and Practice, Elsevier, vol. 106(C), pages 51-64.
    16. Tang, Yue & Gao, Song & Ben-Elia, Eran, 2017. "An exploratory study of instance-based learning for route choice with random travel times," Journal of choice modelling, Elsevier, vol. 24(C), pages 22-35.
    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. Maria Fernanda Guajardo Ortega & Heike Link, 2023. "Estimating Mode Choice Inertia and Price Elasticities after a Price Intervention – Evidence from Three Months of almost Fare-free Public Transport in Germany," Discussion Papers of DIW Berlin 2052, DIW Berlin, German Institute for Economic Research.

    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. Prateek Bansal & Daniel Horcher & Daniel J. Graham, 2020. "A Dynamic Choice Model with Heterogeneous Decision Rules: Application in Estimating the User Cost of Rail Crowding," Papers 2007.03682, arXiv.org.
    2. Di Ciommo, Floridea & Comendador, Julio & López-Lambas, María Eugenia & Cherchi, Elisabetta & Ortúzar, Juan de Dios, 2014. "Exploring the role of social capital influence variables on travel behaviour," Transportation Research Part A: Policy and Practice, Elsevier, vol. 68(C), pages 46-55.
    3. Thomas, Tom & La Paix Puello, Lissy & Geurs, Karst, 2019. "Intrapersonal mode choice variation: Evidence from a four-week smartphone-based travel survey in the Netherlands," Journal of Transport Geography, Elsevier, vol. 76(C), pages 287-300.
    4. Olde Kalter, Marie-José & La Paix Puello, Lissy & Geurs, Karst T., 2020. "Do changes in travellers’ attitudes towards car use and ownership over time affect travel mode choice? A latent transition approach in the Netherlands," Transportation Research Part A: Policy and Practice, Elsevier, vol. 132(C), pages 1-17.
    5. Manca, Francesco & Sivakumar, Aruna & Polak, John W., 2022. "Capturing the effect of multiple social influence sources on the adoption of new transport technologies and services," Journal of choice modelling, Elsevier, vol. 42(C).
    6. Kun Gao & Minhua Shao & Kay W. Axhausen & Lijun Sun & Huizhao Tu & Yihong Wang, 2022. "Inertia effects of past behavior in commuting modal shift behavior: interactions, variations and implications for demand estimation," Transportation, Springer, vol. 49(4), pages 1063-1097, August.
    7. La Paix Puello, Lissy & Olde-Kalter, Marie-José & Geurs, Karst T., 2017. "Measurement of non-random attrition effects on mobility rates using trip diaries data," Transportation Research Part A: Policy and Practice, Elsevier, vol. 106(C), pages 51-64.
    8. Kazagli, Evanthia & de Lapparent, Matthieu, 2023. "A discrete choice modeling framework of heterogenous decision rules accounting for non-trading behavior," Journal of choice modelling, Elsevier, vol. 48(C).
    9. Zhou, Yuyang & Wang, Peiyu & Zheng, Shuyan & Zhao, Minhe & Lam, William H.K. & Chen, Anthony & Sze, N.N. & Chen, Yanyan, 2024. "Modeling dynamic travel mode choices using cumulative prospect theory," Transportation Research Part A: Policy and Practice, Elsevier, vol. 179(C).
    10. Ahmad Termida, Nursitihazlin & Susilo, Yusak O. & Franklin, Joel P., 2016. "Observing dynamic behavioural responses due to the extension of a tram line by using panel survey," Transportation Research Part A: Policy and Practice, Elsevier, vol. 86(C), pages 78-95.
    11. Chen, Roger B., 2018. "Models of count with endogenous choices," Transportation Research Part B: Methodological, Elsevier, vol. 117(PB), pages 862-875.
    12. Schmid, Basil & Becker, Felix & Axhausen, Kay W. & Widmer, Paul & Stein, Petra, 2023. "A simultaneous model of residential location, mobility tool ownership and mode choice using latent variables," Transportation Research Part A: Policy and Practice, Elsevier, vol. 178(C).
    13. González, Rosa Marina & Marrero, Ángel Simón & Cherchi, Elisabetta, 2017. "Testing for inertia effect when a new tram is implemented," Transportation Research Part A: Policy and Practice, Elsevier, vol. 98(C), pages 150-159.
    14. Rashedi, Zohreh & Mahmoud, Mohamed & Hasnine, Sami & Habib, Khandker Nurul, 2017. "On the factors affecting the choice of regional transit for commuting in Greater Toronto and Hamilton Area: Application of an advanced RP-SP choice model," Transportation Research Part A: Policy and Practice, Elsevier, vol. 105(C), pages 1-13.
    15. Gao, Kun & Sun, Lijun & Yang, Ying & Meng, Fanyu & Qu, Xiaobo, 2021. "Cumulative prospect theory coupled with multi-attribute decision making for modeling travel behavior," Transportation Research Part A: Policy and Practice, Elsevier, vol. 148(C), pages 1-21.
    16. Pan, Xiaofeng & Rasouli, Soora & Timmermans, Harry, 2019. "Modeling social influence using sequential stated adaptation experiments: A study of city trip itinerary choice," Transportation Research Part A: Policy and Practice, Elsevier, vol. 130(C), pages 652-672.
    17. Timmer, Sebastian & Merfeld, Katrin & Henkel, Sven, 2023. "Exploring motivations for multimodal commuting: A hierarchical means-end chain analysis," Transportation Research Part A: Policy and Practice, Elsevier, vol. 176(C).
    18. Haustein, Sonja & Kroesen, Maarten, 2022. "Shifting to more sustainable mobility styles: A latent transition approach," Journal of Transport Geography, Elsevier, vol. 103(C).
    19. Albert Solé-Ribalta & Sergio Gómez & Alex Arenas, 2018. "Decongestion of Urban Areas with Hotspot Pricing," Networks and Spatial Economics, Springer, vol. 18(1), pages 33-50, March.
    20. Danique Ton & Lara-Britt Zomer & Florian Schneider & Sascha Hoogendoorn-Lanser & Dorine Duives & Oded Cats & Serge Hoogendoorn, 2020. "Latent classes of daily mobility patterns: the relationship with attitudes towards modes," Transportation, Springer, vol. 47(4), pages 1843-1866, August.

    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:kap:transp:v:49:y:2022:i:3:d:10.1007_s11116-021-10201-8. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.