Conceptual Model for Determining the Statistical Significance of Predictive Indicators for Bus Transit Demand Forecasting
Author
Abstract
Suggested Citation
Download full text from publisher
References listed on IDEAS
- Llorca, Carlos & Ji, Joanna & Molloy, Joseph & Moeckel, Rolf, 2018. "The usage of location based big data and trip planning services for the estimation of a long-distance travel demand model. Predicting the impacts of a new high speed rail corridor," Research in Transportation Economics, Elsevier, vol. 72(C), pages 27-36.
- Yun Xiang & Chengcheng Xu & Weijie Yu & Shuyi Wang & Xuedong Hua & Wei Wang, 2019. "Investigating Dominant Trip Distance for Intercity Passenger Transport Mode Using Large-Scale Location-Based Service Data," Sustainability, MDPI, vol. 11(19), pages 1-17, September.
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.- Shafida Azwina Mohd Shafie & Lee Vien Leong & Ahmad Farhan Mohd Sadullah, 2021. "A Trip Generation Model for a Petrol Station with a Convenience Store and a Fast-Food Restaurant," Sustainability, MDPI, vol. 13(22), pages 1-17, November.
- Borhan, Muhamad Nazri & Ibrahim, Ahmad Nazrul Hakimi & Miskeen, Manssour A. Abdulasalm, 2019. "Extending the theory of planned behaviour to predict the intention to take the new high-speed rail for intercity travel in Libya: Assessment of the influence of novelty seeking, trust and external inf," Transportation Research Part A: Policy and Practice, Elsevier, vol. 130(C), pages 373-384.
- Xiaofei Ye & Min Li & Zhongzhen Yang & Xingchen Yan & Jun Chen, 2020. "A Dynamic Adjustment Model of Cruising Taxicab Fleet Size Combined the Operating and Flied Survey Data," Sustainability, MDPI, vol. 12(7), pages 1-18, April.
- Mohsen Momenitabar & Zhila Dehdari Ebrahimi & Mohammad Arani, 2020. "A Systematic and Analytical Review of the Socioeconomic and Environmental Impact of the Deployed High-Speed Rail (HSR) Systems on the World," Papers 2003.04452, arXiv.org, revised Mar 2020.
- Van Acker, Veronique & Kessels, Roselinde & Palhazi Cuervo, Daniel & Lannoo, Steven & Witlox, Frank, 2020. "Preferences for long-distance coach transport: Evidence from a discrete choice experiment," Transportation Research Part A: Policy and Practice, Elsevier, vol. 132(C), pages 759-779.
- Deng, Taotao & Gan, Chen & Du, Huiping & Hu, Yukun & Wang, Dandan, 2021. "Do high speed rail configurations matter to tourist arrivals? Empirical evidence from China's prefecture-level cities," Research in Transportation Economics, Elsevier, vol. 90(C).
- Fan Yang & Linchao Li & Fan Ding & Huachun Tan & Bin Ran, 2020. "A Data-Driven Approach to Trip Generation Modeling for Urban Residents and Non-local Travelers," Sustainability, MDPI, vol. 12(18), pages 1-15, September.
- Mohsen Momenitabar & Raj Bridgelall & Zhila Dehdari Ebrahimi & Mohammad Arani, 2021. "Literature Review of Socioeconomic and Environmental Impacts of High-Speed Rail in the World," Sustainability, MDPI, vol. 13(21), pages 1-27, November.
- Sharma, Ishant & Mishra, Sabyasachee & Kabiri, Aliakbar & Ghader, Sepehr & Zhang, Lei, 2024. "Use of passive data for determining link level long distance trips," Transportation Research Part A: Policy and Practice, Elsevier, vol. 179(C).
- Fan Yang & Fan Ding & Xu Qu & Bin Ran, 2019. "Estimating Urban Shared-Bike Trips with Location-Based Social Networking Data," Sustainability, MDPI, vol. 11(11), pages 1-14, June.
- Avogadro, Nicolò & Cattaneo, Mattia & Paleari, Stefano & Redondi, Renato, 2021. "Replacing short-medium haul intra-European flights with high-speed rail: Impact on CO2 emissions and regional accessibility," Transport Policy, Elsevier, vol. 114(C), pages 25-39.
More about this item
Keywords
passenger demand prediction; travel demand modelling; public transit planning; big data; statistical significance testing; multiple regression;All these keywords.
Statistics
Access and download statisticsCorrections
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:gam:jsusta:v:15:y:2022:i:1:p:749-:d:1021562. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.