IDEAS home Printed from https://ideas.repec.org/a/eee/transa/v103y2017icp377-390.html
   My bibliography  Save this article

A probability-based indicator for measuring the degree of multimodality in transportation investments

Author

Listed:
  • Lee, Changju
  • Miller, John S.

Abstract

Although decision makers may favor a “multimodal” transportation system, it can be difficult to indicate the extent to which a given transportation investment is, or is not, multimodal. This lack of an indicator can be acute when the project selection process requires consideration of how a given investment supports increased multimodality. In response to this need, this research reports on a taxonomy for classifying the degree of multimodality for transportation projects. Probability theory was employed with principal component analysis to create a new indicator based on both demand (modal shares) and supply (monetary investment for each mode). The indicator offers three main benefits in the area of performance measurement: (1) it is applicable in cases when some data are missing; (2) it provides a way of comparing multimodality from diverse projects such as high-occupancy toll lanes or multimodal centers; and (3) it can help decision-makers quantify how multimodality has changed over time. For example, application of the indicator to six U.S. public-private partnership projects in Colorado, Florida, Rhode Island, and Virginia showed that the degree of multimodality increased by an average value of 57%. (While the manner in which the impact boundary is defined affects this calculation for specific projects, the average value remained relatively stable whether the impact boundary was equal to the average commute trip length or less than half that amount.) Given that some planners view multimodality as societally beneficial, the indicator proposed herein can help one evaluate the multimodal potential of proposed transportation investments.

Suggested Citation

  • Lee, Changju & Miller, John S., 2017. "A probability-based indicator for measuring the degree of multimodality in transportation investments," Transportation Research Part A: Policy and Practice, Elsevier, vol. 103(C), pages 377-390.
    • Handle: RePEc:eee:transa:v:103:y:2017:i:c:p:377-390
    DOI: 10.1016/j.tra.2017.06.003
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0965856416306085
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.tra.2017.06.003?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. Kanafani, Adib & Wang, Rui, 2010. "Measuring Multimodal Transport Level of Service," University of California Transportation Center, Working Papers qt9k74n1b5, University of California Transportation Center.
    2. Chen, Shaopei & Tan, Jianjun & Claramunt, Christophe & Ray, Cyril, 2011. "Multi-scale and multi-modal GIS-T data model," Journal of Transport Geography, Elsevier, vol. 19(1), pages 147-161.
    3. Bielli, Maurizio & Boulmakoul, Azedine & Mouncif, Hicham, 2006. "Object modeling and path computation for multimodal travel systems," European Journal of Operational Research, Elsevier, vol. 175(3), pages 1705-1730, December.
    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. Sangwan Lee, 2022. "Exploring Associations between Multimodality and Built Environment Characteristics in the U.S," Sustainability, MDPI, vol. 14(11), pages 1-16, May.

    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. Chen, Shaopei & Claramunt, Christophe & Ray, Cyril, 2014. "A spatio-temporal modelling approach for the study of the connectivity and accessibility of the Guangzhou metropolitan network," Journal of Transport Geography, Elsevier, vol. 36(C), pages 12-23.
    2. Duff, Thomas J. & Chong, Derek M. & Tolhurst, Kevin G., 2015. "Using discrete event simulation cellular automata models to determine multi-mode travel times and routes of terrestrial suppression resources to wildland fires," European Journal of Operational Research, Elsevier, vol. 241(3), pages 763-770.
    3. Linzhong Liu & Haibo Mu & Juhua Yang, 2017. "Toward algorithms for multi-modal shortest path problem and their extension in urban transit network," Journal of Intelligent Manufacturing, Springer, vol. 28(3), pages 767-781, March.
    4. Caramia, M. & Guerriero, F., 2009. "A heuristic approach to long-haul freight transportation with multiple objective functions," Omega, Elsevier, vol. 37(3), pages 600-614, June.
    5. Woldeamanuel, Mintesnot & Olwert, Craig, 2016. "The Multimodal Connectivity at Bus Rapid Transit (BRT) Stations and the Impact on Ridership," Journal of the Transportation Research Forum, Transportation Research Forum, vol. 55(1), April.
    6. Bao, Danwen & Hua, Songyi & Gu, Jiayu, 2016. "Relevance of airport accessibility and airport competition," Journal of Air Transport Management, Elsevier, vol. 55(C), pages 52-60.
    7. Celikoglu, Hilmi Berk, 2013. "Reconstructing freeway travel times with a simplified network flow model alternating the adopted fundamental diagram," European Journal of Operational Research, Elsevier, vol. 228(2), pages 457-466.
    8. Guedes, M. Carmo M. & Oliveira, Natália & Santiago, Sérgio & Smirnov, Georgi, 2012. "On the evaluation of a public transportation network quality: Criteria validation methodology," Research in Transportation Economics, Elsevier, vol. 36(1), pages 39-44.
    9. Garaix, Thierry & Artigues, Christian & Feillet, Dominique & Josselin, Didier, 2010. "Vehicle routing problems with alternative paths: An application to on-demand transportation," European Journal of Operational Research, Elsevier, vol. 204(1), pages 62-75, July.

    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:eee:transa:v:103:y:2017:i:c:p:377-390. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/547/description#description .

    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.