IDEAS home Printed from https://ideas.repec.org/a/eee/retrec/v86y2021ics0739885920301888.html
   My bibliography  Save this article

Train-feeder modes in Italy. Is there a role for active mobility?

Author

Listed:
  • Giansoldati, Marco
  • Danielis, Romeo
  • Rotaris, Lucia

Abstract

The transport mode used to reach a train station is an important determinant of the urban traffic and rail transport attractiveness. In this paper, we have investigated train-feeder mode choice on the basis of 185 interviews with Italian train users living in cities of different size. We analyzed their current choice and their stated choices under hypothetical scenarios using various discrete choice model specifications. Their current train-feeder mode choice is mainly car-based: 63.2% of the respondents use the car, as either drivers or passengers. The active modes cycling and walking are chosen by 18.4% and 9.7% of the respondents, respectively; the remaining using either the bus or the scooter. Our estimates confirm that travel time and travel cost play a relevant role with two covariates, commuter and gender, explaining the large heterogeneity of the active mobility travel time variable. However, the performed scenario analysis suggests that, in many instances, it is extremely difficult to alter the existing train-feeder mode choice in favor of the active modes and that promoting active mobility in Italy requires a coordinated effort at many levels, including territorial planning, infrastructural investment and traffic regulations.

Suggested Citation

  • Giansoldati, Marco & Danielis, Romeo & Rotaris, Lucia, 2021. "Train-feeder modes in Italy. Is there a role for active mobility?," Research in Transportation Economics, Elsevier, vol. 86(C).
    • Handle: RePEc:eee:retrec:v:86:y:2021:i:c:s0739885920301888
    DOI: 10.1016/j.retrec.2020.100990
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0739885920301888
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.retrec.2020.100990?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. Mark Wardman & Jonathan Tyler, 2000. "Rail network accessibility and the demand for inter-urban rail travel," Transport Reviews, Taylor & Francis Journals, vol. 20(1), pages 3-24, January.
    2. Vincent Chakour & Naveen Eluru, 2014. "Analyzing commuter train user behavior: a decision framework for access mode and station choice," Transportation, Springer, vol. 41(1), pages 211-228, January.
    3. Krygsman, Stephan & Dijst, Martin & Arentze, Theo, 2004. "Multimodal public transport: an analysis of travel time elements and the interconnectivity ratio," Transport Policy, Elsevier, vol. 11(3), pages 265-275, July.
    4. Zheng, Zuduo & Washington, Simon & Hyland, Paul & Sloan, Keith & Liu, Yulin, 2016. "Preference heterogeneity in mode choice based on a nationwide survey with a focus on urban rail," Transportation Research Part A: Policy and Practice, Elsevier, vol. 91(C), pages 178-194.
    5. Kevin Chan & Steven Farber, 0. "Factors underlying the connections between active transportation and public transit at commuter rail in the Greater Toronto and Hamilton Area," Transportation, Springer, vol. 0, pages 1-22.
    6. Elisabetta Cherchi & Juan Ortúzar, 2002. "Mixed RP/SP models incorporating interaction effects," Transportation, Springer, vol. 29(4), pages 371-395, November.
    7. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521766555, January.
    8. Gatta, Valerio & Marcucci, Edoardo & Scaccia, Luisa, 2015. "On finite sample performance of confidence intervals methods for willingness to pay measures," Transportation Research Part A: Policy and Practice, Elsevier, vol. 82(C), pages 169-192.
    9. Ahmed El-Geneidy & Michael Grimsrud & Rania Wasfi & Paul Tétreault & Julien Surprenant-Legault, 2014. "New evidence on walking distances to transit stops: identifying redundancies and gaps using variable service areas," Transportation, Springer, vol. 41(1), pages 193-210, January.
    10. 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.
    11. Bhat, Chandra R. & Castelar, Saul, 2002. "A unified mixed logit framework for modeling revealed and stated preferences: formulation and application to congestion pricing analysis in the San Francisco Bay area," Transportation Research Part B: Methodological, Elsevier, vol. 36(7), pages 593-616, August.
    12. Givoni, Moshe & Rietveld, Piet, 2007. "The access journey to the railway station and its role in passengers' satisfaction with rail travel," Transport Policy, Elsevier, vol. 14(5), pages 357-365, September.
    13. de Luca, Stefano & Di Pace, Roberta, 2015. "Modelling users’ behaviour in inter-urban carsharing program: A stated preference approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 71(C), pages 59-76.
    14. Weliwitiya, Hesara & Rose, Geoffrey & Johnson, Marilyn, 2019. "Bicycle train intermodality: Effects of demography, station characteristics and the built environment," Journal of Transport Geography, Elsevier, vol. 74(C), pages 395-404.
    15. Tirachini, Alejandro & Hensher, David A. & Jara-Díaz, Sergio R., 2010. "Comparing operator and users costs of light rail, heavy rail and bus rapid transit over a radial public transport network," Research in Transportation Economics, Elsevier, vol. 29(1), pages 231-242.
    16. Lissy La Paix & Karst T. Geurs, 2016. "Train station access and train use: a joint stated and revealed preference choice modelling study," Chapters, in: Karst T. Geurs & Roberto Patuelli & Tomaz Ponce Dentinho (ed.), Accessibility, Equity and Efficiency, chapter 8, pages 144-166, Edward Elgar Publishing.
    17. Bhat, Chandra R. & Sardesai, Rupali, 2006. "The impact of stop-making and travel time reliability on commute mode choice," Transportation Research Part B: Methodological, Elsevier, vol. 40(9), pages 709-730, November.
    18. Jeroen C.J.M. van den Bergh (ed.), 1999. "Handbook of Environmental and Resource Economics," Books, Edward Elgar Publishing, number 801.
    19. Banister, David, 2008. "The sustainable mobility paradigm," Transport Policy, Elsevier, vol. 15(2), pages 73-80, March.
    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. Yang, Xing-Qi & Huang, Hai-Jun, 2022. "Effects of HSR station location on urban spatial structure: A spatial equilibrium analysis for a two-city system," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 166(C).

    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. Jean-Philippe Meloche & Vincent Trotignon & François Vaillancourt, 2021. "Densification ou prolongement des réseaux de transport structurants ? Une recension des écrits sur les coûts et les bénéfices attendus," CIRANO Project Reports 2020rp-28, CIRANO.
    2. Bliemer, Michiel C.J. & Rose, John M. & Hensher, David A., 2009. "Efficient stated choice experiments for estimating nested logit models," Transportation Research Part B: Methodological, Elsevier, vol. 43(1), pages 19-35, January.
    3. 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.
    4. Puteri Paramita & Zuduo Zheng & Md Mazharul Haque & Simon Washington & Paul Hyland, 2018. "User satisfaction with train fares: A comparative analysis in five Australian cities," PLOS ONE, Public Library of Science, vol. 13(6), pages 1-26, June.
    5. Bhat, Chandra R., 2011. "The maximum approximate composite marginal likelihood (MACML) estimation of multinomial probit-based unordered response choice models," Transportation Research Part B: Methodological, Elsevier, vol. 45(7), pages 923-939, August.
    6. Brons, Martijn & Givoni, Moshe & Rietveld, Piet, 2009. "Access to railway stations and its potential in increasing rail use," Transportation Research Part A: Policy and Practice, Elsevier, vol. 43(2), pages 136-149, February.
    7. Aaron Gutiérrez & Daniel Miravet & Òscar Saladié & Salvador Anton Clavé, 2019. "Transport Mode Choice by Tourists Transferring from a Peripheral High-Speed Rail Station to Their Destinations: Empirical Evidence from Costa Daurada," Sustainability, MDPI, vol. 11(11), pages 1-15, June.
    8. Le Pira, Michela & Marcucci, Edoardo & Gatta, Valerio, 2021. "Roman holiday: Tourist heterogeneous preferences for walking path elements," Research in Transportation Economics, Elsevier, vol. 90(C).
    9. Allard, Ryan F. & Moura, Filipe, 2018. "Effect of transport transfer quality on intercity passenger mode choice," Transportation Research Part A: Policy and Practice, Elsevier, vol. 109(C), pages 89-107.
    10. Hossan, Md Sakoat & Asgari, Hamidreza & Jin, Xia, 2016. "Investigating preference heterogeneity in Value of Time (VOT) and Value of Reliability (VOR) estimation for managed lanes," Transportation Research Part A: Policy and Practice, Elsevier, vol. 94(C), pages 638-649.
    11. Krueger, Rico & Bierlaire, Michel & Daziano, Ricardo A. & Rashidi, Taha H. & Bansal, Prateek, 2021. "Evaluating the predictive abilities of mixed logit models with unobserved inter- and intra-individual heterogeneity," Journal of choice modelling, Elsevier, vol. 41(C).
    12. Hess, Stephane & Train, Kenneth E., 2011. "Recovery of inter- and intra-personal heterogeneity using mixed logit models," Transportation Research Part B: Methodological, Elsevier, vol. 45(7), pages 973-990, August.
    13. Becker, Felix & Danaf, Mazen & Song, Xiang & Atasoy, Bilge & Ben-Akiva, Moshe, 2018. "Bayesian estimator for Logit Mixtures with inter- and intra-consumer heterogeneity," Transportation Research Part B: Methodological, Elsevier, vol. 117(PA), pages 1-17.
    14. Sadhukhan, Shubhajit & Banerjee, Uttam K. & Maitra, Bhargab, 2016. "Commuters’ willingness-to-pay for improvement of transfer facilities in and around metro stations – A case study in Kolkata," Transportation Research Part A: Policy and Practice, Elsevier, vol. 92(C), pages 43-58.
    15. Bhat, Chandra R. & Sidharthan, Raghuprasad, 2011. "A simulation evaluation of the maximum approximate composite marginal likelihood (MACML) estimator for mixed multinomial probit models," Transportation Research Part B: Methodological, Elsevier, vol. 45(7), pages 940-953, August.
    16. Kun Gao & Minhua Shao & Kay W. Axhausen & Lijun Sun & Huizhao Tu & Yihong Wang, 2022. "Inertia effects of past behavior in commuting modal shift behavior: interactions, variations and implications for demand estimation," Transportation, Springer, vol. 49(4), pages 1063-1097, August.
    17. Bliemer, Michiel C.J. & Rose, John M., 2011. "Experimental design influences on stated choice outputs: An empirical study in air travel choice," Transportation Research Part A: Policy and Practice, Elsevier, vol. 45(1), pages 63-79, January.
    18. Scaccia, Luisa & Marcucci, Edoardo & Gatta, Valerio, 2023. "Prediction and confidence intervals of willingness-to-pay for mixed logit models," Transportation Research Part B: Methodological, Elsevier, vol. 167(C), pages 54-78.
    19. Weliwitiya, Hesara & Rose, Geoffrey & Johnson, Marilyn, 2019. "Bicycle train intermodality: Effects of demography, station characteristics and the built environment," Journal of Transport Geography, Elsevier, vol. 74(C), pages 395-404.
    20. Deka, Devajyoti & Carnegie, Jon, 2021. "Predicting transit mode choice of New Jersey workers commuting to New York City from a stated preference survey," Journal of Transport Geography, Elsevier, vol. 91(C).

    More about this item

    Keywords

    Active mobility; Walking; Cycling; Train feeder modes; Commuters; Gender; Revealed preferences; Stated preferences;
    All these keywords.

    JEL classification:

    • R41 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Transportation: Demand, Supply, and Congestion; Travel Time; Safety and Accidents; Transportation Noise
    • R42 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Government and Private Investment Analysis; Road Maintenance; Transportation Planning
    • R48 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Government Pricing and Policy

    Statistics

    Access and download statistics

    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:retrec:v:86:y:2021:i:c:s0739885920301888. 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/620614/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.