IDEAS home Printed from https://ideas.repec.org/a/eee/transa/v36y2002i2p127-144.html
   My bibliography  Save this article

Cross-town bus routes as a solution for decentralized travel: a cost-benefit analysis for Monterrey, Mexico

Author

Listed:
  • El-Hifnawi, M. B.

Abstract

No abstract is available for this item.

Suggested Citation

  • El-Hifnawi, M. B., 2002. "Cross-town bus routes as a solution for decentralized travel: a cost-benefit analysis for Monterrey, Mexico," Transportation Research Part A: Policy and Practice, Elsevier, vol. 36(2), pages 127-144, February.
    • Handle: RePEc:eee:transa:v:36:y:2002:i:2:p:127-144
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0965-8564(00)00040-9
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    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. Kenneth Train, 1980. "A Structured Logit Model of Auto Ownership and Mode Choice," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 47(2), pages 357-370.
    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. Hwe, Siu Kei & Cheung, Raymond K. & Wan, Yat-wah, 2006. "Merging bus routes in Hong Kong's central business district: Analysis and models," Transportation Research Part A: Policy and Practice, Elsevier, vol. 40(10), pages 918-935, December.
    2. Gschwender, Antonio & Jara-Díaz, Sergio & Bravo, Claudia, 2016. "Feeder-trunk or direct lines? Economies of density, transfer costs and transit structure in an urban context," Transportation Research Part A: Policy and Practice, Elsevier, vol. 88(C), pages 209-222.
    3. Hyard, Alexandra, 2012. "Cost-benefit analysis according to Sen: An application in the evaluation of transport infrastructures in France," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(4), pages 707-719.

    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. Hakim Hammadou & Claire Papaix, 2015. "Policy packages for modal shift and CO2 reduction in Lille, France," Working Papers 1501, Chaire Economie du climat.
    2. Schuster, Monica & Vranken, Liesbet & Maertens, Miet, 2017. "You Can(’t) Always Get the Job You Want: Stated versus Revealed Employment Preferences in the Peruvian Agro-industry," Working Papers 254076, Katholieke Universiteit Leuven, Centre for Agricultural and Food Economics.
    3. Donna, Javier D., 2018. "Measuring Long-Run Price Elasticities in Urban Travel Demand," MPRA Paper 90059, University Library of Munich, Germany.
    4. Zhi (Aaron) Cheng & Min-Seok Pang & Paul A. Pavlou, 2020. "Mitigating Traffic Congestion: The Role of Intelligent Transportation Systems," Information Systems Research, INFORMS, vol. 31(3), pages 653-674, September.
    5. Duncan, Michael & Christensen, Robert K., 2013. "An analysis of park-and-ride provision at light rail stations across the US," Transport Policy, Elsevier, vol. 25(C), pages 148-157.
    6. Jeremy Webb & Max Briggs & Clevo Wilson, 2018. "Breaking automotive modal lock-in: a choice modelling study of Jakarta commuters," Environmental Economics and Policy Studies, Springer;Society for Environmental Economics and Policy Studies - SEEPS, vol. 20(1), pages 47-68, January.
    7. Commins, Nicola & Nolan, Anne, 2011. "The determinants of mode of transport to work in the Greater Dublin Area," Transport Policy, Elsevier, vol. 18(1), pages 259-268, January.
    8. Lahiri, Kajal & Gao, Jian, 2002. "Bayesian analysis of nested logit model by Markov chain Monte Carlo," Journal of Econometrics, Elsevier, vol. 111(1), pages 103-133, November.
    9. Viteri Mejía, César & Brandt, Sylvia, 2015. "Managing tourism in the Galapagos Islands through price incentives: A choice experiment approach," Ecological Economics, Elsevier, vol. 117(C), pages 1-11.
    10. Safirova, Elena A. & Houde, Sébastien & Harrington, Winston, 2007. "Spatial Development and Energy Consumption," RFF Working Paper Series dp-07-51, Resources for the Future.
    11. Jennifer Roberts & Gurleen Popli & Rosemary J. Harris, 2018. "Do environmental concerns affect commuting choices?: hybrid choice modelling with household survey data," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 181(1), pages 299-320, January.
    12. Smart, Michael J., 2014. "A volatile relationship: The effect of changing gasoline prices on public support for mass transit," Transportation Research Part A: Policy and Practice, Elsevier, vol. 61(C), pages 178-185.
    13. Shenhao Wang & Qingyi Wang & Jinhua Zhao, 2019. "Multitask Learning Deep Neural Networks to Combine Revealed and Stated Preference Data," Papers 1901.00227, arXiv.org, revised Aug 2019.
    14. Basnak, Paul & Giesen, Ricardo & Muñoz, Juan Carlos, 2020. "Technology choices in public transport planning: A classification framework," Research in Transportation Economics, Elsevier, vol. 83(C).
    15. Mingzhu Song & Yi Zhang & Meng Li & Yi Zhang, 2021. "Accessibility of Transit Stops with Multiple Feeder Modes: Walking and Private-Bike Cycling," Sustainability, MDPI, vol. 13(6), pages 1-27, March.
    16. John Eakins, 2013. "The Determinants of Household Car Ownership: Empirical Evidence from the Irish Household Budget Survey," Surrey Energy Economics Centre (SEEC), School of Economics Discussion Papers (SEEDS) 144, Surrey Energy Economics Centre (SEEC), School of Economics, University of Surrey.
    17. Wang, Qingyi & Wang, Shenhao & Zheng, Yunhan & Lin, Hongzhou & Zhang, Xiaohu & Zhao, Jinhua & Walker, Joan, 2024. "Deep hybrid model with satellite imagery: How to combine demand modeling and computer vision for travel behavior analysis?," Transportation Research Part B: Methodological, Elsevier, vol. 179(C).
    18. Can, Vo Van, 2013. "Estimation of travel mode choice for domestic tourists to Nha Trang using the multinomial probit model," Transportation Research Part A: Policy and Practice, Elsevier, vol. 49(C), pages 149-159.
    19. Shenhao Wang & Baichuan Mo & Jinhua Zhao, 2020. "Theory-based residual neural networks: A synergy of discrete choice models and deep neural networks," Papers 2010.11644, arXiv.org.
    20. Samir Ghazouani & Mohamed Goaïed, 1993. "Analyse micro-économétrique de la demande de transport urbain pour la ville de Tunis," Économie et Prévision, Programme National Persée, vol. 108(2), pages 47-62.

    More about this item

    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:transa:v:36:y:2002:i:2:p:127-144. 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.