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

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  • 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.

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  • 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
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    1. Elisabetta Cherchi & Juan Ortúzar, 2002. "Mixed RP/SP models incorporating interaction effects," Transportation, Springer, vol. 29(4), pages 371-395, November.
    2. 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.
    3. 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.
    4. 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.
    5. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521766555.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    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. 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.
    12. 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.
    13. 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.
    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. 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.
    16. 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.
    17. Jeroen C.J.M. van den Bergh (ed.), 1999. "Handbook of Environmental and Resource Economics," Books, Edward Elgar Publishing, number 801.
    18. 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.
    19. Banister, David, 2008. "The sustainable mobility paradigm," Transport Policy, Elsevier, vol. 15(2), pages 73-80, March.
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    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).

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    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

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