IDEAS home Printed from https://ideas.repec.org/a/kap/transp/v50y2023i3d10.1007_s11116-022-10266-z.html
   My bibliography  Save this article

How does self-assessed health status relate to preferences for cycling infrastructure? A latent class and latent variable approach

Author

Listed:
  • Tomás Rossetti

    (Cornell University)

  • Ricardo Daziano

    (Cornell University)

Abstract

This study aims to understand how self-assessed health status relates to preferences for cycling infrastructure. An integrated latent class and latent variable choice model is fitted using responses to a stated preference experiment from a panel of New York City residents (N = 801). Estimates show that people with stated good physical health tend to have preference parameters similar to those of experienced cyclists. This result means that the provision of cycling infrastructure with the purpose of attracting non-cyclists also has the potential of attracting those with worse health outcomes. This result suggests a double benefit coming from car use reduction and lower health spending.

Suggested Citation

  • Tomás Rossetti & Ricardo Daziano, 2023. "How does self-assessed health status relate to preferences for cycling infrastructure? A latent class and latent variable approach," Transportation, Springer, vol. 50(3), pages 913-928, June.
  • Handle: RePEc:kap:transp:v:50:y:2023:i:3:d:10.1007_s11116-022-10266-z
    DOI: 10.1007/s11116-022-10266-z
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11116-022-10266-z
    File Function: Abstract
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1007/s11116-022-10266-z?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. Palma, David & Ortúzar, Juan de Dios & Rizzi, Luis Ignacio & Guevara, Cristian Angelo & Casaubon, Gerard & Ma, Huiqin, 2016. "Modelling choice when price is a cue for quality: a case study with Chinese consumers," Journal of choice modelling, Elsevier, vol. 19(C), pages 24-39.
    2. Walker, Joan & Ben-Akiva, Moshe, 2002. "Generalized random utility model," Mathematical Social Sciences, Elsevier, vol. 43(3), pages 303-343, July.
    3. 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.
    4. Junyi Shen, 2009. "Latent class model or mixed logit model? A comparison by transport mode choice data," Applied Economics, Taylor & Francis Journals, vol. 41(22), pages 2915-2924.
    5. Daly, Andrew & Hess, Stephane & de Jong, Gerard, 2012. "Calculating errors for measures derived from choice modelling estimates," Transportation Research Part B: Methodological, Elsevier, vol. 46(2), pages 333-341.
    6. Chorus, Caspar G. & Kroesen, Maarten, 2014. "On the (im-)possibility of deriving transport policy implications from hybrid choice models," Transport Policy, Elsevier, vol. 36(C), pages 217-222.
    7. Francisco J. Bahamonde-Birke & Uwe Kunert & Heike Link & Juan de Dios Ortúzar, 2017. "About attitudes and perceptions: finding the proper way to consider latent variables in discrete choice models," Transportation, Springer, vol. 44(3), pages 475-493, May.
    8. Nello-Deakin, Samuel, 2020. "Environmental determinants of cycling: Not seeing the forest for the trees?," Journal of Transport Geography, Elsevier, vol. 85(C).
    9. Beharry-Borg, Nesha & Scarpa, Riccardo, 2010. "Valuing quality changes in Caribbean coastal waters for heterogeneous beach visitors," Ecological Economics, Elsevier, vol. 69(5), pages 1124-1139, March.
    10. Hurtubia, Ricardo & Nguyen, My Hang & Glerum, Aurélie & Bierlaire, Michel, 2014. "Integrating psychometric indicators in latent class choice models," Transportation Research Part A: Policy and Practice, Elsevier, vol. 64(C), pages 135-146.
    11. Joan Walker & Jieping Li, 2007. "Latent lifestyle preferences and household location decisions," Journal of Geographical Systems, Springer, vol. 9(1), pages 77-101, April.
    12. Rossetti, Tomás & Guevara, C. Angelo & Galilea, Patricia & Hurtubia, Ricardo, 2018. "Modeling safety as a perceptual latent variable to assess cycling infrastructure," Transportation Research Part A: Policy and Practice, Elsevier, vol. 111(C), pages 252-265.
    13. Hess, Stephane & Palma, David, 2019. "Apollo: A flexible, powerful and customisable freeware package for choice model estimation and application," Journal of choice modelling, Elsevier, vol. 32(C), pages 1-1.
    14. Chandra R. Bhat, 1997. "An Endogenous Segmentation Mode Choice Model with an Application to Intercity Travel," Transportation Science, INFORMS, vol. 31(1), pages 34-48, February.
    15. Ralph Buehler & Jennifer Dill, 2016. "Bikeway Networks: A Review of Effects on Cycling," Transport Reviews, Taylor & Francis Journals, vol. 36(1), pages 9-27, 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. Rossetti, Tomás & Guevara, C. Angelo & Galilea, Patricia & Hurtubia, Ricardo, 2018. "Modeling safety as a perceptual latent variable to assess cycling infrastructure," Transportation Research Part A: Policy and Practice, Elsevier, vol. 111(C), pages 252-265.
    2. 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.
    3. Rossetti, Tomás & Yoon, So-Yeon & Daziano, Ricardo A., 2022. "Social distancing and store choice in times of a pandemic," Journal of Retailing and Consumer Services, Elsevier, vol. 65(C).
    4. Kim, Sung Hoo & Mokhtarian, Patricia L., 2023. "Finite mixture (or latent class) modeling in transportation: Trends, usage, potential, and future directions," Transportation Research Part B: Methodological, Elsevier, vol. 172(C), pages 134-173.
    5. Francisco J. Bahamonde-Birke & Juan de Dios Ortúzar, 2015. "About the Categorization of Latent Variables in Hybrid Choice Models," Discussion Papers of DIW Berlin 1527, DIW Berlin, German Institute for Economic Research.
    6. Xuemei Fu, 2021. "How habit moderates the commute mode decision process: integration of the theory of planned behavior and latent class choice model," Transportation, Springer, vol. 48(5), pages 2681-2707, October.
    7. Tomás Rossetti & Verónica Saud & Ricardo Hurtubia, 2019. "I want to ride it where I like: measuring design preferences in cycling infrastructure," Transportation, Springer, vol. 46(3), pages 697-718, June.
    8. Mikkel Thorhauge & Akshay Vij & Elisabetta Cherchi, 2021. "Heterogeneity in departure time preferences, flexibility and schedule constraints," Transportation, Springer, vol. 48(4), pages 1865-1893, August.
    9. Hurtubia, Ricardo & Nguyen, My Hang & Glerum, Aurélie & Bierlaire, Michel, 2014. "Integrating psychometric indicators in latent class choice models," Transportation Research Part A: Policy and Practice, Elsevier, vol. 64(C), pages 135-146.
    10. 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.
    11. 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.
    12. Weibo Li & Maria Kamargianni, 2020. "An Integrated Choice and Latent Variable Model to Explore the Influence of Attitudinal and Perceptual Factors on Shared Mobility Choices and Their Value of Time Estimation," Transportation Science, INFORMS, vol. 54(1), pages 62-83, January.
    13. Khakdaman, Masoud & Rezaei, Jafar & Tavasszy, Lóránt A., 2020. "Shippers’ willingness to delegate modal control in freight transportation," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 141(C).
    14. Strazzera, Elisabetta & Meleddu, Daniela & Atzori, Rossella, 2022. "A hybrid choice modelling approach to estimate the trade-off between perceived environmental risks and economic benefits," Ecological Economics, Elsevier, vol. 196(C).
    15. Tinessa, Fiore & Marzano, Vittorio & Papola, Andrea, 2020. "Mixing distributions of tastes with a Combination of Nested Logit (CoNL) kernel: Formulation and performance analysis," Transportation Research Part B: Methodological, Elsevier, vol. 141(C), pages 1-23.
    16. Morlotti, Chiara & Birolini, Sebastian & Malighetti, Paolo & Redondi, Renato, 2023. "A latent class approach to estimate air travelers’ propensity toward connecting itineraries," Research in Transportation Economics, Elsevier, vol. 99(C).
    17. Ardeshiri, Ali & Rashidi, Taha Hossein, 2020. "Willingness to pay for fast charging station for electric vehicles with limited market penetration making," Energy Policy, Elsevier, vol. 147(C).
    18. Wiktor Budziński & Mikołaj Czajkowski, 2022. "Endogeneity and Measurement Bias of the Indicator Variables in Hybrid Choice Models: A Monte Carlo Investigation," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 83(3), pages 605-629, November.
    19. Jia, Wenjian & Chen, T. Donna, 2023. "Investigating heterogeneous preferences for plug-in electric vehicles: Policy implications from different choice models," Transportation Research Part A: Policy and Practice, Elsevier, vol. 173(C).
    20. Sfeir, Georges & Abou-Zeid, Maya & Rodrigues, Filipe & Pereira, Francisco Camara & Kaysi, Isam, 2021. "Latent class choice model with a flexible class membership component: A mixture model approach," Journal of choice modelling, Elsevier, vol. 41(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:kap:transp:v:50:y:2023:i:3:d:10.1007_s11116-022-10266-z. 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.