IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v10y2018i4p912-d137425.html
   My bibliography  Save this article

How Personal Accessibility and Frequency of Travel Affect Ownership Decisions on Mobility Resources

Author

Listed:
  • Vaclav Plevka

    (L-Mob Leuven Mobility Research Centre, KU Leuven, B-3000 Leuven, Belgium)

  • Paola Astegiano

    (L-Mob Leuven Mobility Research Centre, KU Leuven, B-3000 Leuven, Belgium)

  • Willem Himpe

    (L-Mob Leuven Mobility Research Centre, KU Leuven, B-3000 Leuven, Belgium)

  • Chris Tampère

    (L-Mob Leuven Mobility Research Centre, KU Leuven, B-3000 Leuven, Belgium)

  • Martina Vandebroek

    (Faculty of Economics and Business, KU Leuven, Naamsestraat 69, 3000 Leuven, Belgium
    Leuven Statistics Research Centre, KU Leuven, Celestijnenlaan 200B, 3001 Leuven, Belgium)

Abstract

This paper presents a mobility-resource ownership model. The model captures inter-related personal mobility decisions: which transport mode (out of those available to a decision-maker) to use for a particular trip and which mobility resources (e.g., car, bicycle, transit season ticket or a combination) should the decision-maker own to enable the most “appropriate” set of transport modes. Importantly, the mobility decisions are not evaluated only for a single trip or a single day. In fact, for each decision-maker, an entire set of trips, observed over multiple days, is evaluated. We call this personal accessibility to travel. We present a two-step discrete choice model that includes both mode choice and ownership decisions. The model is estimated based on household travel survey data from Germany. This paper also investigates the simulation of travel times for non-chosen modes that are required as an input. The estimation results show significant effects of the personal accessibility and travel frequency on mobility-resource ownership decisions. To further validate the estimation, the forecasting and sensitivity analysis of the model for different scenarios is evaluated. The proposed model offers an efficient solution to situations when the impact of transport sustainability measures on mobility behaviour needs to be plausibly predicted.

Suggested Citation

  • Vaclav Plevka & Paola Astegiano & Willem Himpe & Chris Tampère & Martina Vandebroek, 2018. "How Personal Accessibility and Frequency of Travel Affect Ownership Decisions on Mobility Resources," Sustainability, MDPI, vol. 10(4), pages 1-25, March.
  • Handle: RePEc:gam:jsusta:v:10:y:2018:i:4:p:912-:d:137425
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/10/4/912/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/10/4/912/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Simma, A. & Axhausen, K. W., 2001. "Structures of commitment in mode use: a comparison of Switzerland, Germany and Great Britain," Transport Policy, Elsevier, vol. 8(4), pages 279-288, October.
    2. Mulalic, Ismir & Rouwendal, Jan, 2020. "Does improving public transport decrease car ownership? Evidence from a residential sorting model for the Copenhagen metropolitan area," Regional Science and Urban Economics, Elsevier, vol. 83(C).
    3. Frans M. Dieleman & Martin Dijst & Guillaume Burghouwt, 2002. "Urban Form and Travel Behaviour: Micro-level Household Attributes and Residential Context," Urban Studies, Urban Studies Journal Limited, vol. 39(3), pages 507-527, March.
    4. Le Vine, Scott & Lee-Gosselin, Martin & Sivakumar, Aruna & Polak, John, 2013. "A new concept of accessibility to personal activities: development of theory and application to an empirical study of mobility resource holdings," Journal of Transport Geography, Elsevier, vol. 31(C), pages 1-10.
    5. Linn, Joshua & Yang, Jun & Liu, Antung A. & Qin, Ping, 2016. "The Effect of Owning a Car on Travel Behavior: Evidence from the Beijing License Plate Lottery," RFF Working Paper Series dp-16-18, Resources for the Future.
    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. Yifei Xie & Mazen Danaf & Carlos Lima Azevedo & Arun Prakash Akkinepally & Bilge Atasoy & Kyungsoo Jeong & Ravi Seshadri & Moshe Ben-Akiva, 2019. "Behavioral modeling of on-demand mobility services: general framework and application to sustainable travel incentives," Transportation, Springer, vol. 46(6), pages 2017-2039, December.
    2. Myung Ja Kim & C. Michael Hall & Mark Bonn, 2021. "Factors Affecting Pandemic Biosecurity Behaviors of International Travelers: Moderating Roles of Gender, Age, and Travel Frequency," Sustainability, MDPI, vol. 13(21), pages 1-17, November.

    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. Li, Jingjing & Kim, Changjoo & Sang, Sunhee, 2018. "Exploring impacts of land use characteristics in residential neighborhood and activity space on non-work travel behaviors," Journal of Transport Geography, Elsevier, vol. 70(C), pages 141-147.
    2. Scheiner, Joachim & Holz-Rau, Christian, 2013. "A comprehensive study of life course, cohort, and period effects on changes in travel mode use," Transportation Research Part A: Policy and Practice, Elsevier, vol. 47(C), pages 167-181.
    3. Dogterom, Nico & Ettema, Dick & Dijst, Martin, 2018. "Behavioural effects of a tradable driving credit scheme: Results of an online stated adaptation experiment in the Netherlands," Transportation Research Part A: Policy and Practice, Elsevier, vol. 107(C), pages 52-64.
    4. Jaroslav Burian & Lenka Zajíčková & Igor Ivan & Karel Macků, 2018. "Attitudes and Motivation to Use Public or Individual Transport: A Case Study of Two Middle-Sized Cities," Social Sciences, MDPI, vol. 7(6), pages 1-25, May.
    5. Nicolas, Jean-Pierre & Pelé, Nicolas, 2018. "Reprint of Measuring trends in household expenditures for daily mobility. The case in Lyon, France, between 1995 and 2015," Transport Policy, Elsevier, vol. 65(C), pages 19-29.
    6. Joachim Scheiner & Christian Holz-Rau, 2007. "Travel mode choice: affected by objective or subjective determinants?," Transportation, Springer, vol. 34(4), pages 487-511, July.
    7. Borghorst, Malte & Mulalic, Ismir & van Ommeren, Jos, 2021. "Commuting, Children and the Gender Wage Gap," Working Papers 15-2021, Copenhagen Business School, Department of Economics.
    8. Andrea CIRILLI & Paolo VENERI, 2010. "Spatial Structure and CO2 Emissions Due to Commuting: an Analysis on Italian Urban Areas," Working Papers 353, Universita' Politecnica delle Marche (I), Dipartimento di Scienze Economiche e Sociali.
    9. Van Acker, Veronique & Witlox, Frank, 2010. "Car ownership as a mediating variable in car travel behaviour research using a structural equation modelling approach to identify its dual relationship," Journal of Transport Geography, Elsevier, vol. 18(1), pages 65-74.
    10. Silva, Mafalda C. & Horta, Isabel M. & Leal, Vítor & Oliveira, Vítor, 2017. "A spatially-explicit methodological framework based on neural networks to assess the effect of urban form on energy demand," Applied Energy, Elsevier, vol. 202(C), pages 386-398.
    11. Nicolas, Jean-Pierre & Pelé, Nicolas, 2017. "Measuring trends in household expenditures for daily mobility. The case in Lyon, France, between 1995 and 2015," Transport Policy, Elsevier, vol. 59(C), pages 82-92.
    12. Elldér, Erik, 2014. "Residential location and daily travel distances: the influence of trip purpose," Journal of Transport Geography, Elsevier, vol. 34(C), pages 121-130.
    13. Rubin, Ori & Bertolini, Luca, 2016. "Social and environmental sustainability of travelling within family networks," Transport Policy, Elsevier, vol. 52(C), pages 72-80.
    14. 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.
    15. Hong, Jinhyun & Thakuriah, Piyushimita Vonu, 2018. "Examining the relationship between different urbanization settings, smartphone use to access the Internet and trip frequencies," Journal of Transport Geography, Elsevier, vol. 69(C), pages 11-18.
    16. Macharis, Cathy & De Witte, Astrid, 2012. "The typical company car user does not exist: The case of Flemish company car drivers," Transport Policy, Elsevier, vol. 24(C), pages 91-98.
    17. Böcker, Lars & Prillwitz, Jan & Dijst, Martin, 2013. "Climate change impacts on mode choices and travelled distances: a comparison of present with 2050 weather conditions for the Randstad Holland," Journal of Transport Geography, Elsevier, vol. 28(C), pages 176-185.
    18. Gillingham, Kenneth & Munk-Nielsen, Anders, 2019. "A tale of two tails: Commuting and the fuel price response in driving," Journal of Urban Economics, Elsevier, vol. 109(C), pages 27-40.
    19. Imran Khan, Muhammad, 2017. "Policy options for the sustainable development of natural gas as transportation fuel," Energy Policy, Elsevier, vol. 110(C), pages 126-136.
    20. Smith, Göran & Sochor, Jana & Karlsson, I.C. MariAnne, 2018. "Mobility as a Service: Development scenarios and implications for public transport," Research in Transportation Economics, Elsevier, vol. 69(C), pages 592-599.

    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:10:y:2018:i:4:p:912-:d:137425. 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.