Do transportation network companies reduce public transit use in the U.S.?

2019 ◽  
Vol 130 ◽  
pp. 351-372 ◽  
Author(s):  
Narendra Malalgoda ◽  
Siew Hoon Lim
Keyword(s):  
Public Transit ◽  
Transportation Network ◽  
Transit Use ◽  
The U.S ◽  
Transportation Network Companies

Uber Economics: Evaluating the Monetary and Travel Time Trade-Offs of Transportation Network Companies and Transit Service in Chicago, Illinois

2019 ◽  
Vol 2673 (4) ◽  
pp. 295-304 ◽  
Author(s):  
Joseph P. Schwieterman
Keyword(s):  
Travel Time ◽  
Public Transit ◽  
Transportation Network ◽  
Cost Effective ◽  
Service Levels ◽  
Metropolitan Regions ◽  
Transit Service ◽  
Trade Offs ◽  
The U.S ◽  
Transportation Network Companies

The potential diversion of passengers from public transit to transportation network companies (TNCs) is attracting considerable attention in metropolitan regions. Despite this, relatively little microeconomic analysis has been made available to explore how service attributes affect choices between the services offered by TNCs and public transit. To fill this shortfall, this study evaluates prices and service levels for Lyft, Lyft Line, UberX, UberPool, and Chicago Transit Authority (CTA) services in Chicago. Analysis of 3,075 fares and estimated travel times for 620 trips in the 4- to 11-mile range shows TNCs tend to be relatively costly when expressed in relation to the additional amount spent per unit of time saved. The average traveler using these four TNC services, across the entire sample, spends the equivalent of $42–$108 per hour saved—well above the $14.95/hr. the U.S. Department of Transportation (U.S. DOT) recommends assigning to the average transit passenger when conducting analyses about the value of time. However, for travelers on business and those between locations poorly served by transit, including trips between neighborhoods with less transit service than the downtown district, the analysis shows a significant share of passengers will likely find TNCs cost-effective options based on the U.S. DOT standard. The approach taken illustrates how the mobility benefits and competitive issues associated with TNCs can be systematically evaluated by reviewing the price and travel time characteristics of each trip.

Partnerships with Technology-Enabled Mobility Companies

2017 ◽  
Vol 2649 (1) ◽  
pp. 106-112 ◽  
Author(s):  
Marla Westervelt ◽  
Joshua Schank ◽  
Emma Huang
Keyword(s):  
Service Delivery ◽  
Public Transit ◽  
Transportation Network ◽  
Public Agencies ◽  
On Demand ◽  
Transportation Network Companies

The rise and the proliferation of the on-demand economy are creating a new mobility marketplace. This research explored how these new options could be synergistic with public transit models and detailed the experiences of two transit operators that entered into service delivery partnerships with a transportation network company and a micro-transit operator. Based on a series of interviews and the experiences of these two public agencies, this research provides a set of key takeaways and recommendations for transit operators exploring the potential of partnering with new mobility services such as transportation network companies (e.g., Uber or Lyft) and microtransit (e.g., Bridj or Via).

Impacts on Vehicle Occupancy and Airport Curb Congestion of Transportation Network Companies at Airports

2018 ◽  
Vol 2672 (23) ◽  
pp. 52-58 ◽  
Author(s):  
Karina Hermawan ◽  
Amelia C. Regan
Keyword(s):  
Los Angeles ◽  
San Francisco ◽  
Public Transit ◽  
Transportation Network ◽  
Light Rail ◽  
International Airport ◽  
Using Data ◽  
Standard Service ◽  
Transportation Network Companies

How does the growth of transportation network companies (TNCs) at airports affect the use of shared modes and congestion? Using data from the 2015 passenger survey from Los Angeles International Airport (LAX), San Francisco International Airport (SFO), and Oakland International Airport (OAK), this research analyzes TNCs’ relationship with shared modes (modes that typically have higher vehicle-occupancy and include public transit such as buses and light rail, shared vans or shuttles) and the demand for their shared vs. standard service at the airport. Because TNCs both replace shared rides and make them possible, the research also measured the net effects at these airports. The results suggest that in 2015, TNCs caused 215,000 and 25,000 passengers to switch from shared to private modes at SFO and OAK, respectively. By 2020, the increase is expected to be about 840,000 and 107,000 passengers per year, respectively.

Evolution of Transportation Network Companies and Taxis through 2013–2018 in Chicago

2020 ◽  
Vol 2674 (7) ◽  
pp. 385-397
Author(s):  
Sneha Roy ◽  
Anurag Komanduri ◽  
Kimon Proussaloglou
Keyword(s):  
Transportation Network ◽  
Temporal Distribution ◽  
Level Of Service ◽  
Large Urban Area ◽  
On Demand ◽  
The City ◽  
Compare And Contrast ◽  
The U.S ◽  
Travel Distances ◽  
Transportation Network Companies

The objective of this paper is to highlight important differences between taxis and transportation network companies (TNCs) in a large urban area. We analyze the publicly available dataset from Chicago which includes taxi and transportation network company (TNC) utilization and the level of service measures from five months in 2013–2014 and the same five months in 2018–2019. We compare and contrast the data from these two points in time to document utilization of taxis and TNCs and to measure differences in travel times, travel distances, fares, destinations served, and the spatial and temporal distribution of these trips. Travel to and from airports has been evaluated separately owing to the exceptionally high number of trips they generate. Striking differences between pooled and unpooled TNC trip volumes and other travel metrics have been assessed to highlight their operational diversity despite being considered as the same mode. The exploratory analysis has been carried out across the shared-ride, time, and mode dimensions. The study revealed both similarities and differences in taxi trip characteristics between the two evaluation periods and also outlined how the ridehailing market has grown over the years despite the near stagnation in population and employment in the city. We believe that assessing how taxis have fared through this time and highlighting the intrinsic differences between how the old and new mode of on-demand ride services coexist is important. This study aims to help understand how new-age mobility services are impacting transportation in one of the largest cities in the U.S.

scholarly journals Do transportation network companies increase or decrease transit ridership? Empirical evidence from San Francisco

2021 ◽  
Author(s):  
Gregory D. Erhardt ◽  
Richard Alexander Mucci ◽  
Drew Cooper ◽  
Bhargava Sana ◽  
Mei Chen ◽  
...  
Keyword(s):  
San Francisco ◽  
Transportation Network ◽  
Transportation Systems ◽  
Light Rail ◽  
Transit Ridership ◽  
Application Programming ◽  
Transit Agencies ◽  
Using Data ◽  
Transit Use ◽  
Transportation Network Companies

AbstractTransportation network companies (TNCs), such as Uber and Lyft, have been hypothesized to both complement and compete with public transit. Existing research on the topic is limited by a lack of detailed data on the timing and location of TNC trips. This study overcomes that limitation by using data scraped from the Application Programming Interfaces of two TNCs, combined with Automated Passenger Count data on transit use and other supporting data. Using a panel data model of the change in bus ridership in San Francisco between 2010 and 2015, and confirming the result with a separate time-series model, we find that TNCs are responsible for a net ridership decline of about 10%, offsetting net gains from other factors such as service increases and population growth. We do not find a statistically significant effect on light rail ridership. Cities and transit agencies should recognize the transit-competitive nature of TNCs as they plan, regulate and operate their transportation systems.

scholarly journals Assessing senior perspectives' towards ride for free public transportation: a case study in Oakville, Ontario

2021 ◽  
Author(s):  
Stephanie Mah
Keyword(s):  
Mixed Methods ◽  
Public Transportation ◽  
Public Transit ◽  
Travel Behaviour ◽  
Independent Mobility ◽  
Mixed Methods Approach ◽  
Transit Use ◽  
Transportation Program

This research investigated the Ride for Free Public Transportation program for seniors in Oakville, Canada. Using a mixed-methods approach, participants were surveyed (n=131) to understand their travel behaviour, and interviewed (n=16) to understand their perspectives towards taking public transportation. While 63% of seniors said that the Ride for Free Transit Program did not impact their travel behaviour, 37% said that it increased their public transit use. The most popular reason for seniors to use public transportation was taking it by themselves. Some interview respondents said that they used public transportation because they would not have to ask others for rides or they did not have access to a car. Seniors suggested that more education of how to use the bus and transfer could increase senior ridership. This research may aid other municipalities considering similar programs, which could help to sustain the independent mobility of seniors.

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