Transformation of ridehailing in New York City: A quantitative assessment

The proposed study contributes to the understanding of the ongoing transformation of ridehailing market by examining the New York City Taxi & Limousine Commission data from a fine spatial and temporal resolution. The authors examine taxi zone based demand data from NYC for each month and explore the reasons contributing to (a) the increase in ridehailing demand and (b) the shift from traditional taxi services to Transportation Networking Company (TNC) services. The first component – taxi zone ridehailing demand - is analyzed adopting a negative binomial count model. The second component - share of traditional and TNC services demand - is analyzed using a multinomial fractional split model. The two model components are stitched together in a joint framework that allows for the influence of repeated observations as well as for the presence of common unobserved factors affecting the two components. The model estimation considered a comprehensive set of independent variables including transportation infrastructure variables, land use and built environment variables, weather attributes, and temporal attributes. Several performance measures were generated using the joint model for estimation and validation datasets. A prediction exercise is conducted to illustrate how the proposed model system can be utilized for predicting future ridehailing trends. Finally, an elasticity exercise is conducted to estimate the influence of independent variables on the ridehailing market.

• Record URL:
  https://doi.org/10.1016/j.trc.2021.103235
• Record URL:
  http://www.sciencedirect.com/science/article/pii/S0968090X21002485
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/0968090X
• Supplemental Notes:
  • © 2021 Elsevier Ltd. All rights reserved. Abstract reprinted with permission of Elsevier.
• Authors:
  • Dey, Bibhas Kumar
  • Tirtha, Sudipta Dey
  • Eluru, Naveen
  • Konduri, Karthik C
• Publication Date: 2021-8

Language

• English

Media Info

• Media Type: Web
• Features: Figures; References; Tables;
• Pagination: 103235
• Serial:
  • Transportation Research Part C: Emerging Technologies
  • Volume: 129
  • Issue Number: 0
  • Publisher: Elsevier
  • ISSN: 0968-090X
  • Serial URL: http://www.sciencedirect.com/science/journal/0968090X

Subject/Index Terms

• TRT Terms: Mathematical models; Metrics (Quantitative assessment); Modal shift; Multinomial logits; Ridesourcing; Taxicabs
• Geographic Terms: New York (New York)
• Subject Areas: Highways; Planning and Forecasting; Public Transportation;

Filing Info

• Accession Number: 01782101
• Record Type: Publication
• Files: TRIS
• Created Date: Sep 22 2021 11:54AM