User characteristics and spatial correlates of ride-pooling demand – Evidence from Berlin and Munich

As ride-hailing services – such as Uber and Lyft – dominate the market for digitized on-demand mobility solutions, these cab-like services face strict regulations in Germany. Here, ride-pooling services have begun to establish themselves in multiple cities. Instead of transporting passengers individually, ride-pooling services try to bundle journeys with similar routes in real time. Since the launch of commercial ride-pooling services in Germany in 2016, CleverShuttle has been one of the most prominent providers. To get a better understanding of ride-pooling users and their travel behavior in an urban environment, this article shows empirical data from a survey of CleverShuttle users as well as a spatial analysis of CleverShuttle trips made during the year 2019 for the cities of Berlin and Munich. The authors perform spatial regressions to identify spatial correlates of ride-pooling demand. The analysis of both survey and trip data leads to complementary results. Ride-pooling users in Berlin and Munich tend to be young and low-income, with leisure activities in the evening being their primary purpose of travel, followed by commuting. An intermodal use of ride-pooling with rail transport can be assumed for long-distance travel with origins or destinations outside the city's boundaries, rather than for trips within the city centre. The results also suggest that ride-pooling offers a mobility solution complementary to public transport in times when public transport is inconvenient or not available.

• Record URL:
  https://doi.org/10.1016/j.jtrangeo.2023.103596
• Record URL:
  http://www.sciencedirect.com/science/article/pii/S0966692323000686
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/09666923
• Supplemental Notes:
  • © 2023 Elsevier Ltd. All rights reserved. Abstract reprinted with permission of Elsevier.
• Authors:
  • Gödde, Jan
  • Ruhrort, Lisa
  • Allert, Viktoria
  • Scheiner, Joachim
• Publication Date: 2023-5

Language

• English

Media Info

• Media Type: Web
• Features: References;
• Pagination: 103596
• Serial:
  • Journal of Transport Geography
  • Volume: 109
  • Issue Number: 0
  • Publisher: Elsevier
  • ISSN: 0966-6923
  • Serial URL: http://www.elsevier.com/locate/jtrangeo

Subject/Index Terms

• TRT Terms: Persons and personal characteristics; Ridesharing; Ridesourcing; Spatial analysis; Travel demand
• Geographic Terms: Berlin (Germany); Munich (Germany)
• Subject Areas: Data and Information Technology; Highways; Passenger Transportation; Safety and Human Factors;

Filing Info

• Accession Number: 01883625
• Record Type: Publication
• Files: TRIS
• Created Date: May 25 2023 5:41PM