IDEAS home Printed from https://ideas.repec.org/p/cdl/itsdav/qt6zw5v1jz.html
   My bibliography  Save this paper

Factors Influencing Mode Choice for Intercity Travel from Northern New England to Major Northeastern Cities

Author

Listed:
  • Neely, Sean

Abstract

Long-distance and intercity travel generally make up a small portion of the total number of trips taken by an individual, while representing a large portion of aggregate distance traveled on the transportation system. While some research exists on intercity travel behavior between large metropolitan centers, this report addresses a need for more research on travel behavior between non-metropolitan areas and large metropolitan centers. This research specifically considers travel from home locations in northern New England, going to Boston, New York City, Philadelphia, and Washington, DC. These trips are important for quality of life, multimodal planning, and rural economies. This research identifies and quantifies factors that influence people’s mode choice (automobile, intercity bus, passenger rail, or commercial air travel) for these trips. The research uses survey questionnaire data, latent factor analysis, and discrete choice modeling methods. Factors include sociodemographic, built environment, latent attitudes, and trip characteristics. The survey, designed by the University of Vermont Transportation Research Center and the New England Transportation Institute, was conducted by Resource Systems Group, Inc. in 2014, with an initial sample size of 2560. Factor analysis was used to prepare 6 latent attitudinal factors, based on 70 attitudinal responses from the survey statements. The survey data were augmented with built environment variables using geographic information systems (GIS) analysis. A set of multinomial logit models, and a set of nested logit models, were estimated for business and non-business trip mode choice. Results indicate that for this type of travel, factors influencing mode choice for both business and non-business trips include trip distance; land use; personal use of technology; and latent attitudes about auto dependence, preference for automobile, and comfort with personal space and safety on public transportation. Gender is a less significant factor. Age is only significant for non-business trips. View the NCST Project Webpage

Suggested Citation

  • Neely, Sean, 2016. "Factors Influencing Mode Choice for Intercity Travel from Northern New England to Major Northeastern Cities," Institute of Transportation Studies, Working Paper Series qt6zw5v1jz, Institute of Transportation Studies, UC Davis.
  • Handle: RePEc:cdl:itsdav:qt6zw5v1jz
    as

    Download full text from publisher

    File URL: https://www.escholarship.org/uc/item/6zw5v1jz.pdf;origin=repeccitec
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Jan K. Brueckner, 2003. "Airline Traffic and Urban Economic Development," Urban Studies, Urban Studies Journal Limited, vol. 40(8), pages 1455-1469, July.
    2. Ajzen, Icek, 1991. "The theory of planned behavior," Organizational Behavior and Human Decision Processes, Elsevier, vol. 50(2), pages 179-211, December.
    3. Yasasvi Popuri & Kimon Proussaloglou & Cemal Ayvalik & Frank Koppelman & Aimee Lee, 2011. "Importance of traveler attitudes in the choice of public transportation to work: findings from the Regional Transportation Authority Attitudinal Survey," Transportation, Springer, vol. 38(4), pages 643-661, July.
    4. Dargay, Joyce M. & Clark, Stephen, 2012. "The determinants of long distance travel in Great Britain," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(3), pages 576-587.
    5. Louviere,Jordan J. & Hensher,David A. & Swait,Joffre D. With contributions by-Name:Adamowicz,Wiktor, 2000. "Stated Choice Methods," Cambridge Books, Cambridge University Press, number 9780521788304.
    6. E. Fuller & W. Hemmerle, 1966. "Robustness of the maximum-likelihood estimation procedure in factor analysis," Psychometrika, Springer;The Psychometric Society, vol. 31(2), pages 255-266, June.
    7. Hjorthol, Randi J. & Levin, Lena & Sirén, Anu, 2010. "Mobility in different generations of older persons," Journal of Transport Geography, Elsevier, vol. 18(5), pages 624-633.
    8. Andrew Daly & Stephane Hess & Bhanu Patruni & Dimitris Potoglou & Charlene Rohr, 2012. "Using ordered attitudinal indicators in a latent variable choice model: a study of the impact of security on rail travel behaviour," Transportation, Springer, vol. 39(2), pages 267-297, March.
    9. Koppelman, Frank S. & Sethi, Vaneet, 2005. "Incorporating variance and covariance heterogeneity in the Generalized Nested Logit model: an application to modeling long distance travel choice behavior," Transportation Research Part B: Methodological, Elsevier, vol. 39(9), pages 825-853, November.
    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. Andy S. Choi & Kelly S. Fielding, 2016. "Cultural Attitudes as WTP Determinants: A Revised Cultural Worldview Scale," Sustainability, MDPI, vol. 8(6), pages 1-18, June.
    2. Thorhauge, Mikkel & Swait, Joffre & Cherchi, Elisabetta, 2020. "The habit-driven life: Accounting for inertia in departure time choices for commuting trips," Transportation Research Part A: Policy and Practice, Elsevier, vol. 133(C), pages 272-289.
    3. Potoglou, Dimitris & Palacios, Juan & Feijoo, Claudio & Gómez Barroso, Jose-Luis, 2015. "The supply of personal information: A study on the determinants of information provision in e-commerce scenarios," 26th European Regional ITS Conference, Madrid 2015 127174, International Telecommunications Society (ITS).
    4. Vij, Akshay & Walker, Joan L., 2016. "How, when and why integrated choice and latent variable models are latently useful," Transportation Research Part B: Methodological, Elsevier, vol. 90(C), pages 192-217.
    5. Koo, Tay T.R. & Wu, Cheng-Lung (Richard) & Dwyer, Larry, 2010. "Ground travel mode choices of air arrivals at regional destinations: The significance of tourism attributes and destination contexts," Research in Transportation Economics, Elsevier, vol. 26(1), pages 44-53.
    6. Charalampia N. Anastasiou & Kiriaki M. Keramitsoglou & Nikos Kalogeras & Maria I. Tsagkaraki & Ioanna Kalatzi & Konstantinos P. Tsagarakis, 2017. "Can the “Euro-Leaf” Logo Affect Consumers’ Willingness-To-Buy and Willingness-To-Pay for Organic Food and Attract Consumers’ Preferences? An Empirical Study in Greece," Sustainability, MDPI, vol. 9(8), pages 1-17, August.
    7. Li, Zhengtao & Hu, Bin, 2018. "Perceived health risk, environmental knowledge, and contingent valuation for improving air quality: New evidence from the Jinchuan mining area in China," Economics & Human Biology, Elsevier, vol. 31(C), pages 54-68.
    8. Caroline Roussy & Aude Ridier & Karim Chaïb, 2014. "Adoption d’innovations par les agriculteurs : rôle des perceptions et des préférences," Post-Print hal-01123427, HAL.
    9. Márquez, Luis & Pineda, Laura X. & Poveda, Juan C., 2022. "Mobility-impaired people’s preferences for a specialized paratransit service as BRT’s feeder: The role of autonomy, relatedness, and competence," Transportation Research Part A: Policy and Practice, Elsevier, vol. 165(C), pages 172-185.
    10. 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.
    11. Ahmadi Azari, Kian & Arintono, Sulistyo & Hamid, Hussain & Rahmat, Riza Atiq O.K., 2013. "Modelling demand under parking and cordon pricing policy," Transport Policy, Elsevier, vol. 25(C), pages 1-9.
    12. Czakon, Wojciech & Niemand, Thomas & Gast, Johanna & Kraus, Sascha & Frühstück, Lisa, 2020. "Designing coopetition for radical innovation: An experimental study of managers' preferences for developing self-driving electric cars," Technological Forecasting and Social Change, Elsevier, vol. 155(C).
    13. repec:ags:aare05:139316 is not listed on IDEAS
    14. Grebitus, Carola & Steiner, Bodo & Veeman, Michele, 2015. "The roles of human values and generalized trust on stated preferences when food is labeled with environmental footprints: Insights from Germany," Food Policy, Elsevier, vol. 52(C), pages 84-91.
    15. Lefebvre, Marianne & Raggi, Meri & Gomez Y Paloma, Sergio & Viaggi, Davide, 2014. "An analysis of the intention-realisation discrepancy in EU farmers’ land investment decisions," Review of Agricultural and Environmental Studies - Revue d'Etudes en Agriculture et Environnement (RAEStud), Institut National de la Recherche Agronomique (INRA), vol. 95(1).
    16. Le Goff, Alix & Monchambert, Guillaume & Raux, Charles, 2022. "Are solo driving commuters ready to switch to carpool? Heterogeneity of preferences in Lyon's urban area," Transport Policy, Elsevier, vol. 115(C), pages 27-39.
    17. Raux, Charles & Chevalier, Amandine & Bougna, Emmanuel & Hilton, Denis, 2021. "Mobility choices and climate change: Assessing the effects of social norms, emissions information and economic incentives," Research in Transportation Economics, Elsevier, vol. 90(C).
    18. Choi, Andy S., 2011. "Implicit prices for longer temporary exhibitions in a heritage site and a test of preference heterogeneity: A segmentation-based approach," Tourism Management, Elsevier, vol. 32(3), pages 511-519.
    19. Azari, Kian Ahmadi & Arintono, Sulistyo & Hamid, Hussain & Davoodi, Seyed Rasoul, 2013. "Evaluation of demand for different trip purposes under various congestion pricing scenarios," Journal of Transport Geography, Elsevier, vol. 29(C), pages 43-51.
    20. 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.
    21. Claudy, Marius C. & Michelsen, Claus & O'Driscoll, Aidan, 2011. "The diffusion of microgeneration technologies - assessing the influence of perceived product characteristics on home owners' willingness to pay," Energy Policy, Elsevier, vol. 39(3), pages 1459-1469, March.

    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:cdl:itsdav:qt6zw5v1jz. 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: Lisa Schiff (email available below). General contact details of provider: https://edirc.repec.org/data/itucdus.html .

    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.