IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v9y2017i11p2120-d119389.html
   My bibliography  Save this article

Using New Mode Choice Model Nesting Structures to Address Emerging Policy Questions: A Case Study of the Pittsburgh Central Business District

Author

Listed:
  • Zulqarnain H. Khattak

    (Center for Transportation Studies, Department of Civil and Environmental Engineering, Thornton Hall D101, 351 McCormick Road, University of Virginia, Charlottesville, VA 22904, USA
    All authors contributed substantially to the research article.)

  • Mark J. Magalotti

    (Center for Sustainable Transportation Infrastructure, 706 Benedum Hall, University of Pittsburgh, Pittsburgh, PA 15213, USA
    All authors contributed substantially to the research article.)

  • John S. Miller

    (Virginia Transportation Research Council, 530 Edgemont Rd., Charlottesville, VA 22903, USA
    All authors contributed substantially to the research article.)

  • Michael D. Fontaine

    (Virginia Transportation Research Council, 530 Edgemont Rd., Charlottesville, VA 22903, USA
    All authors contributed substantially to the research article.)

Abstract

As transportation activities affect a region’s environmental quality, knowing why individuals prefer certain modes can help a region make judicious transportation investments. Using a nested logit model, this paper studies the behavior of commuters to downtown Pittsburgh who use auto, bus, light rail, walking, and biking. Although statistical measures influence the selection of a nesting structure, another criterion for model selection is the policy questions such models inform. Hence this paper demonstrates how an alternative model structure allows planners to consider new policy questions. For example, how might a change in parking fee affect greenhouse gas emission (GHGs)? The proposed model showed that a 5%, 10% and 15% increase in parking cost reduces GHGs by 7.3%, 9% and 13.2%, respectively, through increasing carpoolers’ mode share. Because the proposed model forecasts mode choices of certain groups of travelers with higher accuracy (compared to an older model that did not consider the model selection criteria presented here), the proposed model strengthens policymakers’ ability to consider environmental impacts of interest to the region (in this case, GHGs). The paper does not suggest that one nesting structure is always preferable; rather the nesting structure must be chosen with the policy considerations in mind.

Suggested Citation

  • Zulqarnain H. Khattak & Mark J. Magalotti & John S. Miller & Michael D. Fontaine, 2017. "Using New Mode Choice Model Nesting Structures to Address Emerging Policy Questions: A Case Study of the Pittsburgh Central Business District," Sustainability, MDPI, vol. 9(11), pages 1-16, November.
  • Handle: RePEc:gam:jsusta:v:9:y:2017:i:11:p:2120-:d:119389
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/9/11/2120/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/9/11/2120/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Mcfadden, Daniel L., 2002. "The Path to Discrete-Choice Models," University of California Transportation Center, Working Papers qt87h9p7j1, University of California Transportation Center.
    2. Kilani, Moez & de Palma, André & Proost, Stef, 2017. "Are users better-off with new transit lines?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 103(C), pages 95-105.
    3. Adeel, Muhammad & Yeh, Anthony Gar-On & Zhang, Feng, 2016. "Transportation disadvantage and activity participation in the cities of Rawalpindi and Islamabad, Pakistan," Transport Policy, Elsevier, vol. 47(C), pages 1-12.
    4. Khandker Nurul Habib & Yuan Tian & Hamid Zaman, 2011. "Modelling commuting mode choice with explicit consideration of carpool in the choice set formation," Transportation, Springer, vol. 38(4), pages 587-604, July.
    5. Easton, Sue & Ferrari, Ed, 2015. "Children's travel to school—the interaction of individual, neighbourhood and school factors," Transport Policy, Elsevier, vol. 44(C), pages 9-18.
    6. Ben-Akiva, Moshe & McFadden, Daniel & Train, Kenneth & Börsch-Supan, Axel, 2002. "Hybrid Choice Models: Progress and Challenges," Sonderforschungsbereich 504 Publications 02-29, Sonderforschungsbereich 504, Universität Mannheim;Sonderforschungsbereich 504, University of Mannheim.
    7. Subbarao, S.S.V. & Krishna Rao, K,V., 2013. "Trip Chaining Behavior in Developing Countries: A Study of Mumbai Metropolitan Region, India," European Transport \ Trasporti Europei, ISTIEE, Institute for the Study of Transport within the European Economic Integration, issue 53, pages 1-7.
    8. Dissanayake, Dilum & Morikawa, Takayuki, 2010. "Investigating household vehicle ownership, mode choice and trip sharing decisions using a combined revealed preference/stated preference Nested Logit model: case study in Bangkok Metropolitan Region," Journal of Transport Geography, Elsevier, vol. 18(3), pages 402-410.
    9. Muhammad Adeel & Anthony Gar-On Yeh & Feng Zhang, 2016. "Transportation disadvantage and activity participation in the cities of Rawalpindi and Islamabad, Pakistan," LSE Research Online Documents on Economics 65025, London School of Economics and Political Science, LSE Library.
    10. Kamargianni, Maria & Dubey, Subodh & Polydoropoulou, Amalia & Bhat, Chandra, 2015. "Investigating the subjective and objective factors influencing teenagers’ school travel mode choice – An integrated choice and latent variable model," Transportation Research Part A: Policy and Practice, Elsevier, vol. 78(C), pages 473-488.
    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. Ander Pijoan & Oihane Kamara-Esteban & Ainhoa Alonso-Vicario & Cruz E. Borges, 2018. "Transport Choice Modeling for the Evaluation of New Transport Policies," Sustainability, MDPI, vol. 10(4), pages 1-22, April.
    2. Wissam Qassim Al-Salih & Domokos Esztergár Kiss, 2022. "Activity Chains Modelling of Travellers by Using Logit Models Based on the Utility Function," Sustainability, MDPI, vol. 14(5), pages 1-36, March.

    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. Ton, Danique & Bekhor, Shlomo & Cats, Oded & Duives, Dorine C. & Hoogendoorn-Lanser, Sascha & Hoogendoorn, Serge P., 2020. "The experienced mode choice set and its determinants: Commuting trips in the Netherlands," Transportation Research Part A: Policy and Practice, Elsevier, vol. 132(C), pages 744-758.
    2. Joseph, Lucy & Neven, An & Martens, Karel & Kweka, Opportuna & Wets, Geert & Janssens, Davy, 2020. "Measuring individuals' travel behaviour by use of a GPS-based smartphone application in Dar es Salaam, Tanzania," Journal of Transport Geography, Elsevier, vol. 88(C).
    3. Milad Mehdizadeh & Alireza Ermagun, 2020. "“I’ll never stop driving my child to school”: on multimodal and monomodal car users," Transportation, Springer, vol. 47(3), pages 1071-1102, June.
    4. Ababio-Donkor, Augustus & Saleh, Wafaa & Fonzone, Achille, 2020. "The role of personal norms in the choice of mode for commuting," Research in Transportation Economics, Elsevier, vol. 83(C).
    5. Bouscasse, H., 2018. "Integrated choice and latent variable models: A literature review on mode choice," Working Papers 2018-07, Grenoble Applied Economics Laboratory (GAEL).
    6. Bansal, Prateek & Kumar, Rajeev Ranjan & Raj, Alok & Dubey, Subodh & Graham, Daniel J., 2021. "Willingness to pay and attitudinal preferences of Indian consumers for electric vehicles," Energy Economics, Elsevier, vol. 100(C).
    7. Scorrano, Mariangela & Danielis, Romeo, 2021. "Active mobility in an Italian city: Mode choice determinants and attitudes before and during the Covid-19 emergency," Research in Transportation Economics, Elsevier, vol. 86(C).
    8. Xiaofeng Ji & Haotian Guan & Mengyuan Lu & Fang Chen & Wenwen Qin, 2022. "International Research Progress in School Travel and Behavior: A Literature Review and Bibliometric Analysis," Sustainability, MDPI, vol. 14(14), pages 1-25, July.
    9. María del Carmen Pérez-Peña & Mercedes Jiménez-García & José Ruiz-Chico & Antonio Rafael Peña-Sánchez, 2021. "Transport Poverty with Special Reference to Sustainability: A Systematic Review of the Literature," Sustainability, MDPI, vol. 13(3), pages 1-13, January.
    10. Hélène Bouscasse, 2018. "Integrated choice and latent variable models: A literature review on mode choice," Working Papers hal-01795630, HAL.
    11. Md. Kamruzzaman & Tan Yigitcanlar & Jay Yang & Mohd Afzan Mohamed, 2016. "Measures of Transport-Related Social Exclusion: A Critical Review of the Literature," Sustainability, MDPI, vol. 8(7), pages 1-30, July.
    12. Farhan Haider & Zia ur Rehman & Ammad Hassan Khan & Maryam Ilyas & Inamullah Khan, 2021. "Performance Evaluation of BRT Standard in Decision Support System for Integrated Transportation Policy," Sustainability, MDPI, vol. 13(4), pages 1-19, February.
    13. Marie Thynell, 2016. "The Quest for Gender-Sensitive and Inclusive Transport Policies in Growing Asian Cities," Social Inclusion, Cogitatio Press, vol. 4(3), pages 72-82.
    14. Aiman Musina & Aigul Abduldayeva & Bulat Suleimenov & Zharas Sembaev & Roza Suleimenova & Marzhan Myrzakhanova & Saltanat Urazova & Dana Assambayeva & Nazim Galimgozhina & Vsevolod Osipov & Kulzhami O, 2022. "The psychophysiological status of rail traffic operators and modern approaches to its correction," Public Transport, Springer, vol. 14(3), pages 635-653, October.
    15. Maljaee, Seyedeh Sara & Khadem Sameni, Melody, 2022. "Investigating factors affecting university students' use of subway before and after COVID-19 outbreak: A case study in Tehran," Journal of Transport Geography, Elsevier, vol. 105(C).
    16. Tao, Sui & He, Sylvia Y. & Kwan, Mei-Po & Luo, Shuli, 2020. "Does low income translate into lower mobility? An investigation of activity space in Hong Kong between 2002 and 2011," Journal of Transport Geography, Elsevier, vol. 82(C).
    17. Muhammad Adeel & Anthony G. O. Yeh & Feng Zhang, 2017. "Gender inequality in mobility and mode choice in Pakistan," Transportation, Springer, vol. 44(6), pages 1519-1534, November.
    18. Zhang, Rui & Yao, Enjian & Liu, Zhili, 2017. "School travel mode choice in Beijing, China," Journal of Transport Geography, Elsevier, vol. 62(C), pages 98-110.
    19. Zolnik, Edmund J. & Malik, Ammar & Irvin-Erickson, Yasemin, 2018. "Who benefits from bus rapid transit? Evidence from the Metro Bus System (MBS) in Lahore," Journal of Transport Geography, Elsevier, vol. 71(C), pages 139-149.
    20. Boyce, Christopher & Czajkowski, Mikołaj & Hanley, Nick, 2019. "Personality and economic choices," Journal of Environmental Economics and Management, Elsevier, vol. 94(C), pages 82-100.

    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:9:y:2017:i:11:p:2120-:d:119389. 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.