Ride-Hailing and Public Transit - Revision history

Ssperoni: /* Findings */

2019-07-17T18:13:17Z

Findings

← Older revision		Revision as of 18:13, 17 July 2019
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	Finally, a 2014 study of 380 ridesourcing/TNC users (a 50.2 percent response rate) in San Francisco asked respondents about key trip characteristics, including trip purpose, origin and destination, and wait times.<ref name=":2">Rayle, Lisa, Danielle Dai, Nelson Chan, Robert Cervero, and Susan Shaheen. (2016). Just A Better Taxi? A Survey-Based Comparison of Taxis, Transit, and Ridesourcing Services in San Francisco. Transport Policy, Volume 45, pp. 168-178. <nowiki>http://dx.doi.org/10.1016/j.tranpol.2015.10.004</nowiki></ref> Most trips, 67 percent, were social or leisure in nature (such as trips to bars, restaurants, and concerts or visits to friends or family) in contrast to just 16 percent of trips that were work related. Of all trips reported, 47 percent originated somewhere other than home or work (e.g., restaurant, bar, gym), while 40 percent had a home-based origin. If ridesourcing/TNCs were unavailable, 39 percent of respondents reported they would have taken a taxi, 33 percent would have taken public transportation, 8 percent would have walked, and 6 percent would have driven their own vehicles. Another 11 percent of respondents said they would have taken another mode.<ref name=":2" /> Respondents were asked if they still would have made the trip had ridesourcing/TNC services not been available and, if so, how they would have traveled. Among respondents, 92 percent replied they still would have made the trip, suggesting that ridesourcing/TNCs has an 8 percent induced travel effect.<ref name=":2" />		Finally, a 2014 study of 380 ridesourcing/TNC users (a 50.2 percent response rate) in San Francisco asked respondents about key trip characteristics, including trip purpose, origin and destination, and wait times.<ref name=":2">Rayle, Lisa, Danielle Dai, Nelson Chan, Robert Cervero, and Susan Shaheen. (2016). Just A Better Taxi? A Survey-Based Comparison of Taxis, Transit, and Ridesourcing Services in San Francisco. Transport Policy, Volume 45, pp. 168-178. <nowiki>http://dx.doi.org/10.1016/j.tranpol.2015.10.004</nowiki></ref> Most trips, 67 percent, were social or leisure in nature (such as trips to bars, restaurants, and concerts or visits to friends or family) in contrast to just 16 percent of trips that were work related. Of all trips reported, 47 percent originated somewhere other than home or work (e.g., restaurant, bar, gym), while 40 percent had a home-based origin. If ridesourcing/TNCs were unavailable, 39 percent of respondents reported they would have taken a taxi, 33 percent would have taken public transportation, 8 percent would have walked, and 6 percent would have driven their own vehicles. Another 11 percent of respondents said they would have taken another mode.<ref name=":2" /> Respondents were asked if they still would have made the trip had ridesourcing/TNC services not been available and, if so, how they would have traveled. Among respondents, 92 percent replied they still would have made the trip, suggesting that ridesourcing/TNCs has an 8 percent induced travel effect.<ref name=":2" />

			== Partnerships ==
			See full article on [[Transit-Ridehail Partnerships]].

	==References==		==References==

	: [[Category:Market Response]] [[Category:First and Last Mile]]		: [[Category:Market Response]] [[Category:First and Last Mile]]
	<references />		<references />

Ssperoni: Ssperoni moved page Shared mobility and public transit to Ride-Hailing and Public Transit: Clarification of site purpose given the rise of scooter and bike-share shared mobility, preparing this page for expansion specific to ride-hailing/TNCs.

2019-05-01T23:44:50Z

Ssperoni moved page Shared mobility and public transit to Ride-Hailing and Public Transit: Clarification of site purpose given the rise of scooter and bike-share shared mobility, preparing this page for expansion specific to ride-hailing/TNCs.

← Older revision	Revision as of 23:44, 1 May 2019
(No difference)

Jmatute at 17:57, 13 April 2018

2018-04-13T17:57:27Z

← Older revision		Revision as of 17:57, 13 April 2018
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			[[Category:Shared Use Mobility]]
	[[Image:Uberlyft.jpg\|right\|thumb\|500px\|Shared mobility providers like ridesourcing companies Uber and Lyft are becoming an increasingly large part of California's transportation system. Source: [https://www.flickr.com/photos/nrkbeta/25511816003 Ståle Grut / NRKbeta.no]]]		[[Image:Uberlyft.jpg\|right\|thumb\|500px\|Shared mobility providers like ridesourcing companies Uber and Lyft are becoming an increasingly large part of California's transportation system. Source: [https://www.flickr.com/photos/nrkbeta/25511816003 Ståle Grut / NRKbeta.no]]]
	==Intro==		==Intro==

Westbywest12: /* Intro */ I added a citation to a recent DOT/FHA report on the use of Smartphone Applications for shared mobility.

2017-12-19T19:10:25Z

Intro: I added a citation to a recent DOT/FHA report on the use of Smartphone Applications for shared mobility.

← Older revision		Revision as of 19:10, 19 December 2017
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	==Intro==		==Intro==

	The last decade has seen a tremendous rise of shared mobility modes, including carsharing, bikesharing, ridesourcing (services like Uber and Lyft), and private shuttles (like Bay-Area tech shuttles). Transit agencies often struggle with these new transportation options, unsure of how to coexist with them and afraid of competition. Ridesoucring/Transportation Network Companies (TNCs) use smartphone apps to connect community drivers with passengers. Examples of these services include: Lyft, Uber (specifically, uberX, uberXL, and UberSELECT), as well as specialized services, such as Lift Hero (older adults and those with disabilities) and HopSkipDrive (rides for children either to/from school or afterschool). These services can provide many different vehicle types including: sedans, sports utility vehicles, vehicles with car seats, wheelchair accessible vehicles, and vehicles where the driver can assist older or disabled passengers. While taxis are often regulated to charge static fares, TNCs typically uses market-rate pricing, popularly known as “surge pricing” when prices usually go up during periods of high demand to incentivize more drivers to take ride requests.		The last decade has seen a tremendous rise of shared mobility modes, including carsharing, bikesharing, ridesourcing (services like Uber and Lyft), and private shuttles (like Bay-Area tech shuttles). Transit agencies often struggle with these new transportation options, unsure of how to coexist with them and afraid of competition. Ridesoucring/Transportation Network Companies (TNCs) use smartphone apps to connect community drivers with passengers.<ref>Shaheen, Susan; Cohen, Adam (April 2016). "Smartphone Applications to Influence Travel Choices: Practices and Policies". ''https://ops.fhwa.dot.gov/publications/fhwahop16023/fhwahop16023.pdf''</ref> Examples of these services include: Lyft, Uber (specifically, uberX, uberXL, and UberSELECT), as well as specialized services, such as Lift Hero (older adults and those with disabilities) and HopSkipDrive (rides for children either to/from school or afterschool). These services can provide many different vehicle types including: sedans, sports utility vehicles, vehicles with car seats, wheelchair accessible vehicles, and vehicles where the driver can assist older or disabled passengers. While taxis are often regulated to charge static fares, TNCs typically uses market-rate pricing, popularly known as “surge pricing” when prices usually go up during periods of high demand to incentivize more drivers to take ride requests.
	==Findings==		==Findings==
	Studies on the impacts of ridesourcing/TNCs are limited, particularly the effects of these innovative services on core transportation modes (e.g., taxis, public transportation). While one study Feigon and Murphy (2016) <ref>Feigon, Sharon and Murphy, Colin. (2016). Shared Mobility and the Transformation of Public Transit. American Public Transportation Association.		Studies on the impacts of ridesourcing/TNCs are limited, particularly the effects of these innovative services on core transportation modes (e.g., taxis, public transportation). While one study Feigon and Murphy (2016) <ref>Feigon, Sharon and Murphy, Colin. (2016). Shared Mobility and the Transformation of Public Transit. American Public Transportation Association.
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	==References==		==References==

	: [[Category:Market Response]] [[Category:First and Last Mile]]		: [[Category:Market Response]] [[Category:First and Last Mile]]
	<references />		<references />

Sashaheen at 18:54, 26 October 2017

2017-10-26T18:54:08Z

← Older revision		Revision as of 18:54, 26 October 2017
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	The last decade has seen a tremendous rise of shared mobility modes, including carsharing, bikesharing, ridesourcing (services like Uber and Lyft), and private shuttles (like Bay-Area tech shuttles). Transit agencies often struggle with these new transportation options, unsure of how to coexist with them and afraid of competition. Ridesoucring/Transportation Network Companies (TNCs) use smartphone apps to connect community drivers with passengers. Examples of these services include: Lyft, Uber (specifically, uberX, uberXL, and UberSELECT), as well as specialized services, such as Lift Hero (older adults and those with disabilities) and HopSkipDrive (rides for children either to/from school or afterschool). These services can provide many different vehicle types including: sedans, sports utility vehicles, vehicles with car seats, wheelchair accessible vehicles, and vehicles where the driver can assist older or disabled passengers. While taxis are often regulated to charge static fares, TNCs typically uses market-rate pricing, popularly known as “surge pricing” when prices usually go up during periods of high demand to incentivize more drivers to take ride requests.		The last decade has seen a tremendous rise of shared mobility modes, including carsharing, bikesharing, ridesourcing (services like Uber and Lyft), and private shuttles (like Bay-Area tech shuttles). Transit agencies often struggle with these new transportation options, unsure of how to coexist with them and afraid of competition. Ridesoucring/Transportation Network Companies (TNCs) use smartphone apps to connect community drivers with passengers. Examples of these services include: Lyft, Uber (specifically, uberX, uberXL, and UberSELECT), as well as specialized services, such as Lift Hero (older adults and those with disabilities) and HopSkipDrive (rides for children either to/from school or afterschool). These services can provide many different vehicle types including: sedans, sports utility vehicles, vehicles with car seats, wheelchair accessible vehicles, and vehicles where the driver can assist older or disabled passengers. While taxis are often regulated to charge static fares, TNCs typically uses market-rate pricing, popularly known as “surge pricing” when prices usually go up during periods of high demand to incentivize more drivers to take ride requests.
	==Findings==		==Findings==
	Studies on the impacts of TNCs are limited, particularly the effects of these innovative services on core transportation modes (e.g., taxis, public transportation). While one study Feigon and Murphy (2016) <ref>Feigon, Sharon and Murphy, Colin. (2016). Shared Mobility and the Transformation of Public Transit. American Public Transportation Association.		Studies on the impacts of ridesourcing/TNCs are limited, particularly the effects of these innovative services on core transportation modes (e.g., taxis, public transportation). While one study Feigon and Murphy (2016) <ref>Feigon, Sharon and Murphy, Colin. (2016). Shared Mobility and the Transformation of Public Transit. American Public Transportation Association.

	https://www.apta.com/resources/reportsandpublications/Documents/APTA-Shared-Mobility.pdf		https://www.apta.com/resources/reportsandpublications/Documents/APTA-Shared-Mobility.pdf
	</ref> concluded that TNCs substitute more automobile trips than public transit trips, three other studies suggest that TNCs may cannibalize trips made by public transit and active modes (cycling and walking. Henao (2017) surveyed 311 passengers in the greater Denver metropolitan area over a four-month period and found that 34 percent of riders said they would have either taken public transit, biked, or walked instead of using TNCs.<ref name=":0">Henao, Alejandro. (2017). Impacts of Ridesourcing – Lyft and Uber – on Transportation including VMT, Mode Replacement, Parking, and Travel Behavior. University of Colorado, Denver. https://www.cpr.org/sites/default/files/cu-uber-lyft-study.pdf</ref> ~~The~~ study also found that TNCs takes more vehicle trips to move fewer people. The study found that it takes an average of 100 vehicle miles to transport a passenger 60.8 miles.<ref name=":0" /> A study of TNCs in New York City by Schaller (2017) found that TNCs accounted for the addition of 600 million miles of vehicular travel to the city's roadway network between 2013 and 2016.<ref name=":1">Schaller, Bruce (2017). Unsustainable: The Growth of App-Based Ride Services and Traffic, Travel and the Future of New York City. Schaller Consulting. http://www.schallerconsult.com/rideservices/unsustainable.pdf</ref> ~~The~~ study also found that in Manhattan, western Queens, and western Brooklyn, TNCs added an estimated seven percent to existing miles driven by all vehicles. Furthermore, VMT continued to increase in spite of the availability of pooled options because single-passenger trips still predominate, and most TNC customers are coming from public transit, walking, and biking.<ref name=":1" />		</ref> concluded that ridesourcing/TNCs substitute more automobile trips than public transit trips, three other studies suggest that ridesourcing/TNCs may cannibalize trips made by public transit and active modes (cycling and walking). Henao (2017) surveyed 311 passengers in the greater Denver metropolitan area over a four-month period and found that 34 percent of riders said they would have either taken public transit, biked, or walked instead of using ridesourcing/TNCs.<ref name=":0">Henao, Alejandro. (2017). Impacts of Ridesourcing – Lyft and Uber – on Transportation including VMT, Mode Replacement, Parking, and Travel Behavior. University of Colorado, Denver. https://www.cpr.org/sites/default/files/cu-uber-lyft-study.pdf</ref> This study also found that ridesourcing/TNCs takes more vehicle trips to move fewer people. The study found that it takes an average of 100 vehicle miles to transport a passenger 60.8 miles.<ref name=":0" /> Another study of ridesourcing/TNCs in New York City by Schaller (2017) found that ridesourcing/TNCs accounted for the addition of 600 million miles of vehicular travel to the city's roadway network between 2013 and 2016.<ref name=":1">Schaller, Bruce (2017). Unsustainable: The Growth of App-Based Ride Services and Traffic, Travel and the Future of New York City. Schaller Consulting. http://www.schallerconsult.com/rideservices/unsustainable.pdf</ref> This study also found that in Manhattan, western Queens, and western Brooklyn, ridesourcing/TNCs added an estimated seven percent to existing miles driven by all vehicles. Furthermore, VMT continued to increase in spite of the availability of pooled options because single-passenger trips still predominate, and most ridesourcing/TNC customers are coming from public transit, walking, and biking.<ref name=":1" />

	A 2014 study of 380 TNC users (a 50.2 percent response rate) in San Francisco asked respondents about key trip characteristics, including trip purpose, origin and destination, and wait times.<ref name=":2">Rayle, Lisa, Danielle Dai, Nelson Chan, Robert Cervero, and Susan Shaheen. (2016). Just A Better Taxi? A Survey-Based Comparison of Taxis, Transit, and Ridesourcing Services in San Francisco. Transport Policy, Volume 45, pp. 168-178. <nowiki>http://dx.doi.org/10.1016/j.tranpol.2015.10.004</nowiki></ref> Most trips, 67 percent, were social or leisure in nature (such as trips to bars, restaurants, and concerts or visits to friends or family) in contrast to just 16 percent of trips that were work related. Of all trips reported, 47 percent originated somewhere other than home or work (e.g., restaurant, bar, gym), while 40 percent had a home-based origin. If TNCs were unavailable, 39 percent of respondents reported they would have taken a taxi, 33 percent would have taken public transportation, 8 percent would have walked, and 6 percent would have driven their own vehicles. Another 11 percent of respondents said they would have taken another mode.<ref name=":2" /> Respondents were asked if they still would have made the trip had TNC services not been available and, if so, how they would have traveled. Among respondents, 92 percent replied they still would have made the trip, suggesting that TNCs has an 8 percent induced travel effect.<ref name=":2" />		Finally, a 2014 study of 380 ridesourcing/TNC users (a 50.2 percent response rate) in San Francisco asked respondents about key trip characteristics, including trip purpose, origin and destination, and wait times.<ref name=":2">Rayle, Lisa, Danielle Dai, Nelson Chan, Robert Cervero, and Susan Shaheen. (2016). Just A Better Taxi? A Survey-Based Comparison of Taxis, Transit, and Ridesourcing Services in San Francisco. Transport Policy, Volume 45, pp. 168-178. <nowiki>http://dx.doi.org/10.1016/j.tranpol.2015.10.004</nowiki></ref> Most trips, 67 percent, were social or leisure in nature (such as trips to bars, restaurants, and concerts or visits to friends or family) in contrast to just 16 percent of trips that were work related. Of all trips reported, 47 percent originated somewhere other than home or work (e.g., restaurant, bar, gym), while 40 percent had a home-based origin. If ridesourcing/TNCs were unavailable, 39 percent of respondents reported they would have taken a taxi, 33 percent would have taken public transportation, 8 percent would have walked, and 6 percent would have driven their own vehicles. Another 11 percent of respondents said they would have taken another mode.<ref name=":2" /> Respondents were asked if they still would have made the trip had ridesourcing/TNC services not been available and, if so, how they would have traveled. Among respondents, 92 percent replied they still would have made the trip, suggesting that ridesourcing/TNCs has an 8 percent induced travel effect.<ref name=":2" />

	==References==		==References==

	: [[Category:Market Response]] [[Category:First and Last Mile]]		: [[Category:Market Response]] [[Category:First and Last Mile]]
	<references />		<references />

Sashaheen: /* Findings */

2017-10-26T18:41:48Z

Findings

← Older revision		Revision as of 18:41, 26 October 2017
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	https://www.apta.com/resources/reportsandpublications/Documents/APTA-Shared-Mobility.pdf		https://www.apta.com/resources/reportsandpublications/Documents/APTA-Shared-Mobility.pdf
	</ref> concluded that TNCs substitute more automobile trips than public transit trips, ~~two~~ other studies suggest that TNCs may cannibalize trips made by public transit and active modes (cycling and walking. Henao surveyed 311 passengers in the greater Denver metropolitan area over a four-month period and found that 34 percent of riders said they would have either taken public transit, biked, or walked instead of using TNCs.<ref name=":0">Henao, Alejandro. (2017). Impacts of Ridesourcing – Lyft and Uber – on Transportation including VMT, Mode Replacement, Parking, and Travel Behavior. University of Colorado, Denver. https://www.cpr.org/sites/default/files/cu-uber-lyft-study.pdf</ref> The study also found that TNCs takes more vehicle trips to move fewer people. The study found that it takes an average of 100 vehicle miles to transport a passenger 60.8 miles.<ref name=":0" /> A study of TNCs in New York City by Schaller (2017) found that TNCs accounted for the addition of 600 million miles of vehicular travel to the city's roadway network between 2013 and 2016.<ref name=":1">Schaller, Bruce (2017). Unsustainable: The Growth of App-Based Ride Services and Traffic, Travel and the Future of New York City. Schaller Consulting. http://www.schallerconsult.com/rideservices/unsustainable.pdf</ref> The study also found that in Manhattan, western Queens, and western Brooklyn, TNCs added an estimated seven percent to existing miles driven by all vehicles. Furthermore, VMT continued to increase in spite of the availability of pooled options because single-passenger trips still predominate, and most TNC customers are coming from public transit, walking, and biking.<ref name=":1" />		</ref> concluded that TNCs substitute more automobile trips than public transit trips, three other studies suggest that TNCs may cannibalize trips made by public transit and active modes (cycling and walking. Henao (2017) surveyed 311 passengers in the greater Denver metropolitan area over a four-month period and found that 34 percent of riders said they would have either taken public transit, biked, or walked instead of using TNCs.<ref name=":0">Henao, Alejandro. (2017). Impacts of Ridesourcing – Lyft and Uber – on Transportation including VMT, Mode Replacement, Parking, and Travel Behavior. University of Colorado, Denver. https://www.cpr.org/sites/default/files/cu-uber-lyft-study.pdf</ref> The study also found that TNCs takes more vehicle trips to move fewer people. The study found that it takes an average of 100 vehicle miles to transport a passenger 60.8 miles.<ref name=":0" /> A study of TNCs in New York City by Schaller (2017) found that TNCs accounted for the addition of 600 million miles of vehicular travel to the city's roadway network between 2013 and 2016.<ref name=":1">Schaller, Bruce (2017). Unsustainable: The Growth of App-Based Ride Services and Traffic, Travel and the Future of New York City. Schaller Consulting. http://www.schallerconsult.com/rideservices/unsustainable.pdf</ref> The study also found that in Manhattan, western Queens, and western Brooklyn, TNCs added an estimated seven percent to existing miles driven by all vehicles. Furthermore, VMT continued to increase in spite of the availability of pooled options because single-passenger trips still predominate, and most TNC customers are coming from public transit, walking, and biking.<ref name=":1" />

	A 2014 study of 380 TNC users (a 50.2 percent response rate) in San Francisco asked respondents about key trip characteristics, including trip purpose, origin and destination, and wait times.<ref name=":2">Rayle, Lisa, Danielle Dai, Nelson Chan, Robert Cervero, and Susan Shaheen. (2016). Just A Better Taxi? A Survey-Based Comparison of Taxis, Transit, and Ridesourcing Services in San Francisco. Transport Policy, Volume 45, pp. 168-178. <nowiki>http://dx.doi.org/10.1016/j.tranpol.2015.10.004</nowiki></ref> Most trips, 67 percent, were social or leisure in nature (such as trips to bars, restaurants, and concerts or visits to friends or family) in contrast to just 16 percent of trips that were work related. Of all trips reported, 47 percent originated somewhere other than home or work (e.g., restaurant, bar, gym), while 40 percent had a home-based origin. If TNCs were unavailable, 39 percent of respondents reported they would have taken a taxi, 33 percent would have taken public transportation, 8 percent would have walked, and 6 percent would have driven their own vehicles. Another 11 percent of respondents said they would have taken another mode.<ref name=":2" /> Respondents were asked if they still would have made the trip had TNC services not been available and, if so, how they would have traveled. Among respondents, 92 percent replied they still would have made the trip, suggesting that TNCs has an 8 percent induced travel effect.<ref name=":2" />		A 2014 study of 380 TNC users (a 50.2 percent response rate) in San Francisco asked respondents about key trip characteristics, including trip purpose, origin and destination, and wait times.<ref name=":2">Rayle, Lisa, Danielle Dai, Nelson Chan, Robert Cervero, and Susan Shaheen. (2016). Just A Better Taxi? A Survey-Based Comparison of Taxis, Transit, and Ridesourcing Services in San Francisco. Transport Policy, Volume 45, pp. 168-178. <nowiki>http://dx.doi.org/10.1016/j.tranpol.2015.10.004</nowiki></ref> Most trips, 67 percent, were social or leisure in nature (such as trips to bars, restaurants, and concerts or visits to friends or family) in contrast to just 16 percent of trips that were work related. Of all trips reported, 47 percent originated somewhere other than home or work (e.g., restaurant, bar, gym), while 40 percent had a home-based origin. If TNCs were unavailable, 39 percent of respondents reported they would have taken a taxi, 33 percent would have taken public transportation, 8 percent would have walked, and 6 percent would have driven their own vehicles. Another 11 percent of respondents said they would have taken another mode.<ref name=":2" /> Respondents were asked if they still would have made the trip had TNC services not been available and, if so, how they would have traveled. Among respondents, 92 percent replied they still would have made the trip, suggesting that TNCs has an 8 percent induced travel effect.<ref name=":2" />
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	==References==		==References==

	: [[Category:Market Response]] [[Category:First and Last Mile]]		: [[Category:Market Response]] [[Category:First and Last Mile]]
	<references />		<references />

Sashaheen: /* Intro */

2017-10-26T18:40:22Z

Intro

← Older revision		Revision as of 18:40, 26 October 2017
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	https://www.apta.com/resources/reportsandpublications/Documents/APTA-Shared-Mobility.pdf		https://www.apta.com/resources/reportsandpublications/Documents/APTA-Shared-Mobility.pdf
	</ref> concluded that TNCs ~~substitutes~~ more automobile trips than public transit trips, two other studies suggest that TNCs may cannibalize trips made by public transit and active modes (cycling and walking. Henao surveyed 311 passengers in the greater Denver metropolitan area over a four-month period and found that 34 percent of riders said they would have either taken public transit, biked, or walked instead of using TNCs.<ref name=":0">Henao, Alejandro. (2017). Impacts of Ridesourcing – Lyft and Uber – on Transportation including VMT, Mode Replacement, Parking, and Travel Behavior. University of Colorado, Denver. https://www.cpr.org/sites/default/files/cu-uber-lyft-study.pdf</ref> The study also found that TNCs takes more vehicle trips to move fewer people. The study found that it takes an average of 100 vehicle miles to transport a passenger 60.8 miles.<ref name=":0" /> A study of TNCs in New York City by Schaller (2017) found that TNCs accounted for the addition of 600 million miles of vehicular travel to the city's roadway network between 2013 and 2016.<ref name=":1">Schaller, Bruce (2017). Unsustainable: The Growth of App-Based Ride Services and Traffic, Travel and the Future of New York City. Schaller Consulting. http://www.schallerconsult.com/rideservices/unsustainable.pdf</ref> The study also found that in Manhattan, western Queens, and western Brooklyn, TNCs added an estimated seven percent to existing miles driven by all vehicles. Furthermore, VMT continued to increase in spite of the availability of pooled options because single-passenger trips still predominate, and most TNC customers are coming from public transit, walking, and biking.<ref name=":1" />		</ref> concluded that TNCs substitute more automobile trips than public transit trips, two other studies suggest that TNCs may cannibalize trips made by public transit and active modes (cycling and walking. Henao surveyed 311 passengers in the greater Denver metropolitan area over a four-month period and found that 34 percent of riders said they would have either taken public transit, biked, or walked instead of using TNCs.<ref name=":0">Henao, Alejandro. (2017). Impacts of Ridesourcing – Lyft and Uber – on Transportation including VMT, Mode Replacement, Parking, and Travel Behavior. University of Colorado, Denver. https://www.cpr.org/sites/default/files/cu-uber-lyft-study.pdf</ref> The study also found that TNCs takes more vehicle trips to move fewer people. The study found that it takes an average of 100 vehicle miles to transport a passenger 60.8 miles.<ref name=":0" /> A study of TNCs in New York City by Schaller (2017) found that TNCs accounted for the addition of 600 million miles of vehicular travel to the city's roadway network between 2013 and 2016.<ref name=":1">Schaller, Bruce (2017). Unsustainable: The Growth of App-Based Ride Services and Traffic, Travel and the Future of New York City. Schaller Consulting. http://www.schallerconsult.com/rideservices/unsustainable.pdf</ref> The study also found that in Manhattan, western Queens, and western Brooklyn, TNCs added an estimated seven percent to existing miles driven by all vehicles. Furthermore, VMT continued to increase in spite of the availability of pooled options because single-passenger trips still predominate, and most TNC customers are coming from public transit, walking, and biking.<ref name=":1" />

	A 2014 study of 380 TNC users (a 50.2 percent response rate) in San Francisco asked respondents about key trip characteristics, including trip purpose, origin and destination, and wait times.<ref name=":2">Rayle, Lisa, Danielle Dai, Nelson Chan, Robert Cervero, and Susan Shaheen. (2016). Just A Better Taxi? A Survey-Based Comparison of Taxis, Transit, and Ridesourcing Services in San Francisco. Transport Policy, Volume 45, pp. 168-178. <nowiki>http://dx.doi.org/10.1016/j.tranpol.2015.10.004</nowiki></ref> Most trips, 67 percent, were social or leisure in nature (such as trips to bars, restaurants, and concerts or visits to friends or family) in contrast to just 16 percent of trips that were work related. Of all trips reported, 47 percent originated somewhere other than home or work (e.g., restaurant, bar, gym), while 40 percent had a home-based origin. If TNCs were unavailable, 39 percent of respondents reported they would have taken a taxi, 33 percent would have taken public transportation, 8 percent would have walked, and 6 percent would have driven their own vehicles. Another 11 percent of respondents said they would have taken another mode.<ref name=":2" /> Respondents were asked if they still would have made the trip had TNC services not been available and, if so, how they would have traveled. Among respondents, 92 percent replied they still would have made the trip, suggesting that TNCs has an 8 percent induced travel effect.<ref name=":2" />		A 2014 study of 380 TNC users (a 50.2 percent response rate) in San Francisco asked respondents about key trip characteristics, including trip purpose, origin and destination, and wait times.<ref name=":2">Rayle, Lisa, Danielle Dai, Nelson Chan, Robert Cervero, and Susan Shaheen. (2016). Just A Better Taxi? A Survey-Based Comparison of Taxis, Transit, and Ridesourcing Services in San Francisco. Transport Policy, Volume 45, pp. 168-178. <nowiki>http://dx.doi.org/10.1016/j.tranpol.2015.10.004</nowiki></ref> Most trips, 67 percent, were social or leisure in nature (such as trips to bars, restaurants, and concerts or visits to friends or family) in contrast to just 16 percent of trips that were work related. Of all trips reported, 47 percent originated somewhere other than home or work (e.g., restaurant, bar, gym), while 40 percent had a home-based origin. If TNCs were unavailable, 39 percent of respondents reported they would have taken a taxi, 33 percent would have taken public transportation, 8 percent would have walked, and 6 percent would have driven their own vehicles. Another 11 percent of respondents said they would have taken another mode.<ref name=":2" /> Respondents were asked if they still would have made the trip had TNC services not been available and, if so, how they would have traveled. Among respondents, 92 percent replied they still would have made the trip, suggesting that TNCs has an 8 percent induced travel effect.<ref name=":2" />
Line 13:		Line 13:
	==References==		==References==

	: [[Category:Market Response]] [[Category:First and Last Mile]]		: [[Category:Market Response]] [[Category:First and Last Mile]]
	<references />		<references />

Tchsavvy at 18:29, 26 October 2017

2017-10-26T18:29:32Z

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	A 2014 study of 380 TNC users (a 50.2 percent response rate) in San Francisco asked respondents about key trip characteristics, including trip purpose, origin and destination, and wait times.<ref name=":2">Rayle, Lisa, Danielle Dai, Nelson Chan, Robert Cervero, and Susan Shaheen. (2016). Just A Better Taxi? A Survey-Based Comparison of Taxis, Transit, and Ridesourcing Services in San Francisco. Transport Policy, Volume 45, pp. 168-178. <nowiki>http://dx.doi.org/10.1016/j.tranpol.2015.10.004</nowiki></ref> Most trips, 67 percent, were social or leisure in nature (such as trips to bars, restaurants, and concerts or visits to friends or family) in contrast to just 16 percent of trips that were work related. Of all trips reported, 47 percent originated somewhere other than home or work (e.g., restaurant, bar, gym), while 40 percent had a home-based origin. If TNCs were unavailable, 39 percent of respondents reported they would have taken a taxi, 33 percent would have taken public transportation, 8 percent would have walked, and 6 percent would have driven their own vehicles. Another 11 percent of respondents said they would have taken another mode.<ref name=":2" /> Respondents were asked if they still would have made the trip had TNC services not been available and, if so, how they would have traveled. Among respondents, 92 percent replied they still would have made the trip, suggesting that TNCs has an 8 percent induced travel effect.<ref name=":2" />		A 2014 study of 380 TNC users (a 50.2 percent response rate) in San Francisco asked respondents about key trip characteristics, including trip purpose, origin and destination, and wait times.<ref name=":2">Rayle, Lisa, Danielle Dai, Nelson Chan, Robert Cervero, and Susan Shaheen. (2016). Just A Better Taxi? A Survey-Based Comparison of Taxis, Transit, and Ridesourcing Services in San Francisco. Transport Policy, Volume 45, pp. 168-178. <nowiki>http://dx.doi.org/10.1016/j.tranpol.2015.10.004</nowiki></ref> Most trips, 67 percent, were social or leisure in nature (such as trips to bars, restaurants, and concerts or visits to friends or family) in contrast to just 16 percent of trips that were work related. Of all trips reported, 47 percent originated somewhere other than home or work (e.g., restaurant, bar, gym), while 40 percent had a home-based origin. If TNCs were unavailable, 39 percent of respondents reported they would have taken a taxi, 33 percent would have taken public transportation, 8 percent would have walked, and 6 percent would have driven their own vehicles. Another 11 percent of respondents said they would have taken another mode.<ref name=":2" /> Respondents were asked if they still would have made the trip had TNC services not been available and, if so, how they would have traveled. Among respondents, 92 percent replied they still would have made the trip, suggesting that TNCs has an 8 percent induced travel effect.<ref name=":2" />

	==~~Further Reading~~==		==References==

	~~[http~~://www.trb.org/Main/Blurbs/173511.aspx Committee for Review of Innovative Urban Mobility Services. (2015) Between public and private mobility: examining the rise of technology-enabled transportation services. ''Transit Cooperative Research Program Special Report 319.'']		: [[Category:Market Response]] [[Category:First and Last Mile]]
			<references />
	~~: This TCRP report provides more background on the rise of shared mobility. It details regulatory issues such as labor, safety, insurance, and equity.~~

	[http://www.sciencedirect.com/science/article/pii/S0966692314001409 Martin, E. & Shaheen, S. (2014). Evaluating public transit modal shift dynamics in response to bikesharing: a tale of two U.S. cities. ''Journal of Transport Geography, 41.'']

	: This paper looks at the relationship between bikesharing and transit ridership. It finds that bikesharing increases bicycle ridership and reduces personal automobile use. Bikesharing can increase transit use in areas with less-intensive public transit networks and reduce transit use in areas with more-intensive ones.

	[http://www.uctc.net/research/papers/UCTC-FR-2014-08.pdf Rayle, L., Shaheen, S., Chan, N., Dai, D., & Cervero, R. (2014). App-based, on-demand ride services: comparing taxi and ridesourcing trips and user characteristics in San Francisco. ''University of California Transportation Center.'']

	: This white paper presents the results of a survey of ridesourcing users in San Francisco. The survey indicates that while ridesourcing can substitute for long public transit trips, it generally complements transit. [[Category:Market Response]] [[Category:First and Last Mile]]

Tchsavvy: Added additional impact studies.

2017-10-26T18:28:27Z

Added additional impact studies.

Show changes

Rabiabonour at 20:35, 24 January 2017

2017-01-24T20:35:32Z

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	[[Category:Market Response]]		[[Category:Market Response]]
			[[Category:First and Last Mile]]