IDEAS home Printed from https://ideas.repec.org/a/eee/transa/v118y2018icp494-505.html
   My bibliography  Save this article

Modeling frequency of rural demand response transit trips

Author

Listed:
  • Sultana, Zohora
  • Mishra, Sabyasachee
  • Cherry, Christopher R.
  • Golias, Mihalis M.
  • Tabrizizadeh Jeffers, Saman

Abstract

Captive riders do not have many travel choices to meet the travel needs as fixed route transit services are not generally provided in rural areas. In many states, demand response transit (DRT) services are provided to meet such needs. However, state public agencies face the dilemma of whether to increase or decrease the service availability for on-call services. To enhance decision making of identifying what the causal factors related to DRT trips, the authors present a set of econometric models by integrating a sample DRT data with other explanatory variables such as land use, socio-economic, and demographic characteristics. Seven count data models including Poisson, Negative Binomial, Zero-inflated Poisson, Zero-inflated Negative Binomial (ZINB), Hurdle Poisson, Hurdle Negative Binomial, and ZINB Mixed Effect were developed to understand the factors that affect DRT trips. The ZINB Mixed Effect model that combines a zero-inflated negative binomial model with random effect was found to provide the best fit. A number of factors showed significant relationship with DRT trip frequency including distance, population density, elderly population, average income, and others. Further, the elasticity effects of these different factors were computed to quantify the magnitude of their impact on DRT. The proposed model can be helpful for transit agencies to predict the frequency of DRT trips and to provide adequate services in rural areas.

Suggested Citation

  • Sultana, Zohora & Mishra, Sabyasachee & Cherry, Christopher R. & Golias, Mihalis M. & Tabrizizadeh Jeffers, Saman, 2018. "Modeling frequency of rural demand response transit trips," Transportation Research Part A: Policy and Practice, Elsevier, vol. 118(C), pages 494-505.
    • Handle: RePEc:eee:transa:v:118:y:2018:i:c:p:494-505
    DOI: 10.1016/j.tra.2018.10.006
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0965856418300326
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.tra.2018.10.006?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. Chao Wang & Mohammed Quddus & Marcus Enoch & Tim Ryley & Lisa Davison, 2014. "Multilevel modelling of Demand Responsive Transport (DRT) trips in Greater Manchester based on area-wide socio-economic data," Transportation, Springer, vol. 41(3), pages 589-610, May.
    2. Hongtai Yang & Christopher R. Cherry, 2017. "Use characteristics and demographics of rural transit riders: a case study in Tennessee," Transportation Planning and Technology, Taylor & Francis Journals, vol. 40(2), pages 213-227, February.
    3. Davison, Lisa & Enoch, Marcus & Ryley, Tim & Quddus, Mohammed & Wang, Chao, 2014. "A survey of Demand Responsive Transport in Great Britain," Transport Policy, Elsevier, vol. 31(C), pages 47-54.
    4. Gurmu, Shiferaw, 1998. "Generalized hurdle count data regression models," Economics Letters, Elsevier, vol. 58(3), pages 263-268, March.
    5. Abbas Moghimbeigi & Mohammed Reza Eshraghian & Kazem Mohammad & Brian Mcardle, 2008. "Multilevel zero-inflated negative binomial regression modeling for over-dispersed count data with extra zeros," Journal of Applied Statistics, Taylor & Francis Journals, vol. 35(10), pages 1193-1202.
    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. Tiznado-Aitken, Ignacio & Guerrero B., Thomas E. & Sagaris, Lake, 2024. "Uncovering gender-based violence and harassment in public transport: Lessons for spatial and transport justice," Journal of Transport Geography, Elsevier, vol. 114(C).
    2. Sharma, Ishant & Mishra, Sabyasachee & Golias, Mihalis M. & Welch, Timothy F. & Cherry, Christopher R., 2020. "Equity of transit connectivity in Tennessee cities," Journal of Transport Geography, Elsevier, vol. 86(C).
    3. Yu, Zhao & Zhao, Pengjun, 2021. "The factors in residents' mobility in rural towns of China: Car ownership, road infrastructure and public transport services," Journal of Transport Geography, Elsevier, vol. 91(C).
    4. Miwa, Tomio & Wang, Jianbiao & Morikawa, Takayuki, 2023. "Are seniors in mountainous areas able to realize their desired trips? A novel approach to estimate trip demand," Transportation Research Part A: Policy and Practice, Elsevier, vol. 175(C).
    5. Zhao, Pengjun & Yu, Zhao, 2020. "Investigating mobility in rural areas of China: Features, equity, and factors," Transport Policy, Elsevier, vol. 94(C), pages 66-77.

    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. Knierim, Lukas & Schlüter, Jan Christian, 2021. "The attitude of potentially less mobile people towards demand responsive transport in a rural area in central Germany," Journal of Transport Geography, Elsevier, vol. 96(C).
    2. Berrada, Jaâfar & Poulhès, Alexis, 2021. "Economic and socioeconomic assessment of replacing conventional public transit with demand responsive transit services in low-to-medium density areas," Transportation Research Part A: Policy and Practice, Elsevier, vol. 150(C), pages 317-334.
    3. Wang, Jiangbo & Yamamoto, Toshiyuki & Liu, Kai, 2022. "Exploring the subscribing behavior of customized bus passengers: Active users versus inactive users," Journal of choice modelling, Elsevier, vol. 43(C).
    4. Sanaullah, Irum & Alsaleh, Nael & Djavadian, Shadi & Farooq, Bilal, 2021. "Spatio-temporal analysis of on-demand transit: A case study of Belleville, Canada," Transportation Research Part A: Policy and Practice, Elsevier, vol. 145(C), pages 284-301.
    5. Schasché, Stephanie E. & Sposato, Robert G. & Hampl, Nina, 2022. "The dilemma of demand-responsive transport services in rural areas: Conflicting expectations and weak user acceptance," Transport Policy, Elsevier, vol. 126(C), pages 43-54.
    6. Jani-Pekka Jokinen, 2021. "Modelling Optimal Policies of Demand Responsive Transport and Interrelationships between Occupancy Rate and Costs," Papers 2103.00565, arXiv.org.
    7. Yip, Karen C.H. & Yau, Kelvin K.W., 2005. "On modeling claim frequency data in general insurance with extra zeros," Insurance: Mathematics and Economics, Elsevier, vol. 36(2), pages 153-163, April.
    8. Wang, Liang & Xie, Zaiyang & Abdi, Majid & Lee, June Y. & Li, Stan Xiao, 2024. "The rise of female board representation in China as a glocalization process (2010–2018)," Journal of Business Research, Elsevier, vol. 172(C).
    9. Zhang, Jie & Wang, David Z.W. & Meng, Meng, 2018. "Which service is better on a linear travel corridor: Park & ride or on-demand public bus?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 118(C), pages 803-818.
    10. Peter Džupka & Radovan Dráb & Marek Gróf & Tomáš Štofa, 2024. "Exploring Willingness to Pay across Different Passenger Traits," Sustainability, MDPI, vol. 16(2), pages 1-16, January.
    11. Jokinen, Jani-Pekka & Sihvola, Teemu & Mladenovic, Milos N., 2019. "Policy lessons from the flexible transport service pilot Kutsuplus in the Helsinki Capital Region," Transport Policy, Elsevier, vol. 76(C), pages 123-133.
    12. Teresa Bago d'Uva & Maarten Lindeboom & Owen O'Donnell & Eddy van Doorslaer, 2011. "Education‐related inequity in healthcare with heterogeneous reporting of health," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 174(3), pages 639-664, July.
    13. Isihara, Paul & Shi, Chaojun & Ward, Jonathan & O'Malley, Leo & Laney, Skyler & Diedrichs, Danilo & Flores, Gabriel, 2020. "Identifying most typical and most ideal attribute levels in small populations of expert decision makers: Studying the Go/No Go decision of disaster relief organizations," Journal of choice modelling, Elsevier, vol. 35(C).
    14. Zhang, Zhaolin & Zhai, Guocong & Xie, Kun & Xiao, Feng, 2022. "Exploring the nonlinear effects of ridesharing on public transit usage: A case study of San Diego," Journal of Transport Geography, Elsevier, vol. 104(C).
    15. Vij, Akshay & Ryan, Stacey & Sampson, Spring & Harris, Susan, 2020. "Consumer preferences for on-demand transport in Australia," Transportation Research Part A: Policy and Practice, Elsevier, vol. 132(C), pages 823-839.
    16. Joan Costa-Font & Sergi Jiménez-Martín & Cristina Vilaplana, 2016. "Does long-term care subsidisation reduce unnecessary hospitalisations?," Economics Working Papers 1535, Department of Economics and Business, Universitat Pompeu Fabra.
    17. Ana María Martínez-Rodríguez & Antonio Conde-Sánchez & María José Olmo-Jiménez, 2019. "A new approach to truncated regression for count data," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 103(4), pages 503-526, December.
    18. Elisabetta Vitale Brovarone & Giancarlo Cotella, 2020. "Improving Rural Accessibility: A Multilayer Approach," Sustainability, MDPI, vol. 12(7), pages 1-20, April.
    19. Costa-Font, Joan & Jiménez-Martínez, Sergi & Vilaplana, Cristina, 2016. "Does long-term care subsidisation reduce hospital admissions?," LSE Research Online Documents on Economics 67911, London School of Economics and Political Science, LSE Library.
    20. Kong, Maiying & Xu, Sheng & Levy, Steven M. & Datta, Somnath, 2015. "GEE type inference for clustered zero-inflated negative binomial regression with application to dental caries," Computational Statistics & Data Analysis, Elsevier, vol. 85(C), pages 54-66.

    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:118:y:2018:i:c:p:494-505. 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.