The Top 7 International Ride-Sharing Apps
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We Can Go Anywhere': Understanding Independence Through a Case Study
‘We can go anywhere’: Understanding independence through a case study of ride-hailing use by people with visual impairments in metropolitan India VAISHNAV KAMESWARAN, University of Michigan JATIN GUPTA, University of Michigan JOYOJEET PAL, University of Michigan SILE O’MODHRAIN, University of Michigan TIFFANY C. VEINOT, University of Michigan ROBIN N. BREWER, University of Michigan AAKANKSHA PARAMESHWAR, University of Michigan VIDHYA Y, Microsoft Research India JACKI O’NEILL, Microsoft Research India Ride-hailing services have received attention as part of the growing work around the sharing economy, but the focus of these studies has largely been on drivers. In this paper, we examine how ride-hailing is transforming the transportation practices of one group of passengers - people with visual impairments in metropolitan India. Through a qualitative study consisting of interviews and observations, we examined the use and impact of these services on our target population, who otherwise contend with chaotic, unreliable, and largely inaccessible modes of transportation. We found that ride-hailing services positively affects participants’ notions of independence, and we tease out how independence for our participants is not just about ‘doing things alone, without help’ but is also situated, social and relative. Furthermore, we show how accessibility, in the case of ride-hailing in India, is a socio-technical and collaborative achievement, involving interactions between the passenger, the driver, and the technology. CCS Concepts: • Human-centered computing → Empirical studies in accessibility; 85 Additional Key Words and Phrases: Accessibility, social accessibility, collaborative accessibility, independence, stigma, social interactions, ridesharing, Uber, Ola, blind users ACM Reference Format: Vaishnav Kameswaran, Jatin Gupta, Joyojeet Pal, Sile O’Modhrain, Tiffany C. -
Ws2018-Transportation-Services-21St
Just what do we actually know about household spending on transportation services and how are they changing in the 21st Century? Jonathan R. Peters, Ph.D. The College of Staten Island & The CUNY Graduate School David A. King, Ph.D. Arizona State University Cameron E. Gordon, Ph.D. University of Canberra Nora Tabori Santiago, MUA The CUNY High Performance Computing Center Bureau of Labor Statistics 2018 Consumer Expenditure Surveys (CE) Microdata Users’ Workshop Washington, DC July 20, 2018 How did we (Transportation Finance Folks & Urban Planners) wind up here at the BLS? Part III (2014, 2017 & 2018) Why are we interested in tracking the cost of transport services and fees? The Changing US Portfolio of Travel • Look at aspects of travel costs that are changing. • How are these costs reflected in the CEX? • How are these cost measured through other methods? • How are these costs spread across income groups? • How can we plan to measure future costs? Ola Cabs - India Sidecar - DOA Uber Trips Origins in “New York” – From Uber Data Obtained From Uber by NYC Taxi and Limousine Commission for April – October 2014 US Households Without a Vehicle Rank City % car-free 1 New York City 56% 2 Washington, DC 38% 3 Boston 37% 4 Philadelphia 33% 5 San Francisco 31% 6 Baltimore 31% 7 Chicago 28% 8 Detroit 26% U.S. Average = 9.22% Household Modes of Travel • Private Automobile • Shared Vehicle – Carpool / Fampool • Shared Vehicle – Taxi, Jitney, Lyft, Uber • Walking • Bicycle • Mass Transit – Commuter Rail, Metro, Bus, Ferry • Air Travel • Non-Travel – Online Shopping / Video Meetings • And Lodging - AirBNB versus Hotels Changing Households • Households used to travel a lot to get goods and services. -
How Transportation Network Companies Could Replace Public Transportation in the United States Matthew L
University of South Florida Scholar Commons Graduate Theses and Dissertations Graduate School November 2017 How Transportation Network Companies Could Replace Public Transportation in the United States Matthew L. Kessler University of South Florida, [email protected] Follow this and additional works at: http://scholarcommons.usf.edu/etd Part of the Civil Engineering Commons, Public Policy Commons, and the Urban Studies and Planning Commons Scholar Commons Citation Kessler, Matthew L., "How Transportation Network Companies Could Replace Public Transportation in the United States" (2017). Graduate Theses and Dissertations. http://scholarcommons.usf.edu/etd/7045 This Thesis is brought to you for free and open access by the Graduate School at Scholar Commons. It has been accepted for inclusion in Graduate Theses and Dissertations by an authorized administrator of Scholar Commons. For more information, please contact [email protected]. How Transportation Network Companies Could Replace Public Transportation in the United States by Matthew L. Kessler A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science in Engineering Science Department of Civil and Environmental Engineering College of Engineering University of South Florida Co-Major Professor: Steven E. Polzin, Ph.D. Co-Major Professor: Abdul. R. Pinjari, Ph.D. Xuehao Chu, Ph.D. Martin D. Hanlon, Ph.D. Date of Approval: October 23, 2017 Keywords: TNC, Supplantment, Transit Agency, Ride-sourcing, Smartphone app Copyright © 2017, Matthew L. Kessler DEDICATION This page is dedicated in memory of my beloved uncle, Joel “Jerry” Kessler, my grandparents: Miriam Sylvia and William Berkowitz, Gertrude and Sam Kessler. Lifelong friend MariaLita Viafora, and a special friend, Michael R. -
Online Platforms for Exchanging and Sharing Goods
CASE STUDY ONLINE PLATFORMS FOR EXCHANGING AND SHARING GOODS by Anders Fremstad 2/2/2015 A project of EXECUTIVE SUMMARY Americans own huge and underutilized stocks of consumer goods, including furniture, appliances, tools, toys, vehicles, and lodging. Websites like Craigslist, Couchsurfing, and NeighborGoods have lowered the transaction costs associated with acquiring secondhand goods and sharing underused goods, which may help us take advantage of this excess capacity. Indeed, advocates of the so-called sharing economy argue that technology can facilitate peer-to-peer transactions that enable us to save money, build community, and reduce environmental burdens. This case study evaluates the economic, social, and environmental effects of three online platforms. Craigslist provides an online market for local secondhand goods such as vehicles, furniture, appliances, and electronics. Couchsurfing matches travelers with hosts around the world who welcome guests into their homes. NeighborGoods helps people borrow and lend household goods free of charge. Together these case studies provide an overview of the role of online platforms as future economy initiatives. The economic benefits to these three platforms are significant, and likely to grow over time. Americans posted hundreds of millions of secondhand goods for sale on Craigslist in 2014, increasing access to affordable used goods. Couchsurfing has helped provide its members with millions of nights of free lodging, substantially reducing the cost of travel. While NeighborGoods has not achieved the scale of Craigslist or Couchsurfing, online platforms for sharing household goods could save Americans significant sums of money, especially if they can facilitate widespread ride-sharing and car-sharing. Online platforms may particularly improve the livelihoods of poor Americans. -
Pdf (Arguing That the Sharing Economy Is a Consequence of Moore’S Law and the Internet)
Notre Dame Law Review Volume 94 | Issue 1 Article 7 11-2018 The hS aring Economy as an Equalizing Economy John O. McGinnis Northwestern University Pritzker School of Law Follow this and additional works at: https://scholarship.law.nd.edu/ndlr Part of the Law and Economics Commons, Law and Politics Commons, and the Law and Society Commons Recommended Citation 94 Notre Dame L. Rev. 329 (2018). This Article is brought to you for free and open access by the Notre Dame Law Review at NDLScholarship. It has been accepted for inclusion in Notre Dame Law Review by an authorized editor of NDLScholarship. For more information, please contact [email protected]. \\jciprod01\productn\N\NDL\94-1\NDL107.txt unknown Seq: 1 19-NOV-18 13:05 THE SHARING ECONOMY AS AN EQUALIZING ECONOMY John O. McGinnis* Economic equality is often said to be the key problem of our time. But information technol- ogy dematerializes the world in ways that are helpful to the ninety-nine percent, because informa- tion can be shared. This Article looks at how one fruit of the information revolution—the sharing economy—has important equalizing features on both its supply and demand sides. First, on the supply side, the intermediaries in the sharing economy, like Airbnb and Uber, allow owners of housing and cars to monetize their most important capital assets. The gig aspect of this economy creates spot markets in jobs that have flexible hours and monetizes people’s passions, such as cooking meals in their home. Such benefits make these jobs even more valuable than the earnings that show up imperfectly in income statistics. -
GLOBAL RIDESHARING VENDORS Request Full Research
COMPETITIVE ASSESSMENT JULY 10, 2018 Request Full Research CA-1238 GLOBAL RIDESHARING VENDORS INTRODUCTION Ridesharing services have grown at breakneck speeds over the past decade as an increasing number of people are using these services and bypassing conventional taxi services and other forms of public transport. The end goal for current ridesharing services is to disrupt and displace the much larger consumer vehicle ownership market through enhancement of their current services as well as the future application of driverless technology. This study analyzes and compares the strength of the current leading ridesharing providers worldwide through an analysis of their innovation programs, strategies, and implementation achievement, as measured through verifiable metrics. A ridesharing service is defined by ABI Research as any company that allows independent drivers to operate on the company’s mobility platform to provide on-demand transportation to the user. This study will also include ride-hailing providers—companies that do not utilize private drivers but instead partner with local taxi providers to provide on-demand transportation to the user. In addition, a global market share evaluation is also provided in the report and compares each vendor’s share of global ridesharing passenger trips. The vendors assessed in this report are Cabify, Careem, Curb, DiDi Chuxing, Easy Taxi, Gett, Go-Jek, Grab, Kakao Mobility Corporation, Lyft, MyTaxi, Ola Cabs, Taxify, and Uber. METHODOLOGY OVERVIEW After individual scores are established for innovation and implementation, an overall company score is established using the Root Mean Square (RMS) method: The resulting overall scores are then ranked and used for percentile comparisons. The RMS method, in comparison with a straight summation or average of individual innovation and implementation values, rewards companies for standout performance. -
Sharing and Tourism: the Rise of New Markets in Transport
SHARING AND TOURISM: THE RISE OF NEW MARKEts IN TRANSPORT Documents de travail GREDEG GREDEG Working Papers Series Christian Longhi Marcello M. Mariani Sylvie Rochhia GREDEG WP No. 2016-01 http://www.gredeg.cnrs.fr/working-papers.html Les opinions exprimées dans la série des Documents de travail GREDEG sont celles des auteurs et ne reflèlent pas nécessairement celles de l’institution. Les documents n’ont pas été soumis à un rapport formel et sont donc inclus dans cette série pour obtenir des commentaires et encourager la discussion. Les droits sur les documents appartiennent aux auteurs. The views expressed in the GREDEG Working Paper Series are those of the author(s) and do not necessarily reflect those of the institution. The Working Papers have not undergone formal review and approval. Such papers are included in this series to elicit feedback and to encourage debate. Copyright belongs to the author(s). Sharing and Tourism: The Rise of New Markets in Transport Christian Longhi1, Marcello M. Mariani2 and Sylvie Rochhia1 1University Nice Sophia Antipolis, GREDEG, CNRS, 250 rue A. Einstein, 06560 Valbonne France [email protected], [email protected] 2University of Bologna, Via Capo di Lucca, 34 – 40126, Bologna, Italy [email protected] GREDEG Working Paper No. 2016-01 Abstract. This paper analyses the implications of sharing on tourists and tourism focusing on the transportation sector. The shifts from ownership to access, from products to services have induced dramatic changes triggered by the emergence of innovative marketplaces. The services offered by Knowledge Innovative Service Suppliers, start-ups at the origin of innovative marketplaces run through platforms allow the tourists to find solutions to run themselves their activities, bypassing the traditional tourism industry. -
How Are Startups Shaping the Future of Road Mobility? ROAD MOBILITY STARTUPS ANALYSIS 2018
How are startups shaping the future of road mobility? ROAD MOBILITY STARTUPS ANALYSIS 2018 1 1 FOREWORD Startups can further enhance the mobility offer Tesla, Uber, Blablacar. Most in doing for passenger transport, Europeans would acknowledge to the point of being now a leading that these 3 startups have alternative to buses, trains and revolutionized the world of road short-haul aircraft. passenger transport over the last 10 years. Tesla, Uber and Blabacar - and their counterparts in other parts of By launching a company with the world - are no longer startups. global ambitions in this industry, Are there new startups that will the likes of which had not been herald market re-alignments of the seen since the creation of Honda in magnitude of these 3 companies? 1948, Tesla shook well-established If so, in which domains? How are car manufacturers. It opened the they going to do it? door to a new generation of cars: To answer these questions, we electric, connected, autonomous. studied 421* startups associated with on-road mobility. The world of taxis was halted, even blocked. By relying on This study of 421 startups allowed smartphones, Uber dynamised us to highlight 3 major groups: the situation and somewhat satisfied - not without criticism - / Startups that contribute to the the shortage of affordable private emergence of a new generation of driver services in some cities. cars; / Those which conceive mobility not The sharing economy is simple through means, but as a service; (...on paper): exploit the over- / Those that mix the future of the capacity that one person has in vehicle and new types of services to order to make it available to all. -
How Uber Won the Rideshare Wars and What Comes Next
2/18/2020 How Uber Won The Rideshare Wars and What Comes Next CUSTOMER EXPERIENCE | HOW UBER WON THE RIDESHARE WARS AND WHAT COMES NEXT How Uber Won The Rideshare Wars and What Comes Next How Uber won the first phase of the rideshare war and how cabs, competitors, and car companies are battling back. BY ELYSE DUPRE — AUGUST 29, 2016 VIEW GALLERY https://www.dmnews.com/customer-experience/article/13035536/how-uber-won-the-rideshare-wars-and-what-comes-next 1/18 2/18/2020 How Uber Won The Rideshare Wars and What Comes Next View Gallery In 2011, two University of Michigan alums Adrian Fortino and Jahan Khanna partnered with venture capitalist Sunil Paul to revolutionize how people got from point A to point B quickly without having to do much. The company was Sidecar, and the idea was simple: “We're going to replace your car with your iPhone,” Fortino explains. Sidecar did not lack competition. Around this time, the taxi industry was experimenting with new ways to make it easier for individuals to summon cars. And entrepreneurs, frustrated with wait times, imagined new ways to hire someone to drive them around. Multiple companies formed to solve this need, including one that is now considered a global powerhouse: Uber. By the time Sidecar went into beta testing in February 2012, Uber, or UberCab as it was originally known when it was founded in 2009, had raised at least $37.5 million at a $330 million post-money valuation, according to VentureBeat. Lyft followed shortly after when it went into beta in mid 2012, boasting more than $7 million in funding, according to TechCrunch's figures. -
Efficienciesandregulato
EFFICIENCIES AND REGULATORY SHORTCUTS: HOW SHOULD WE REGULATE COMPANIES LIKE AIRBNB AND UBER? Benjamin G. Edelman* & Damien Geradin** CITE AS: 19 STAN. TECH. L. REV. 293 (2016) ABSTRACT We explore the regulation of new software platforms that connect consumers with informal service providers for transportation, short-term rentals, and more. These platforms tend to be in tension with existing regulatory frameworks which typically require licensing, certification, and insurance. In one view, some of these requirements are outdated or protectionist, benefiting incumbents more than consumers. Others counter that the rules embody important values and protect both customers and the public at large. We explore these disagreements with an eye for how the regulatory framework might allow the key efficiencies these platforms provide, while assuring protection for customers and avoiding harm to noncustomers. * Associate Professor, Harvard Business School. [email protected] ** Professor of Law, Tilburg University and George Mason University School of Law. Founding partner, EDGE Legal. [email protected] 293 294 STANFORD TECHNOLOGY LAW REVIEW [Vol. 19:293 TABLE OF CONTENTS I. INTRODUCTION ................................................................................................. 294 II. EFFICIENCIES ..................................................................................................... 296 A. Main efficiencies from software platforms ........................................................ 296 1. Reducing transaction costs ...................................................................... -
Operation Analytics: Uber and Ola Logistics Optimization
Goel Rashi et al.; International Journal of Advance Research and Development (Volume 3, Issue 10) Available online at: www.ijarnd.com Operation analytics: Uber and ola logistics optimization Rashi Goel, Pushti Jain, Rajat Singhal, Riddhi Jhunjhunwala, Ritika Doshi Student, SVKM's Narsee Monjee Institute of Management Studies, Mumbai, Maharashtra ABSTRACT Uber and Ola both are one of the most fastest growing firms in the taxi aggregator industry. However, both run through very different operations and working logistics in terms of driver and rides, route optimization, area connectivity, and availability. With this paper, we aim to draw a comparison between daily working and logistics optimization of both Uber and Ola, so as to understand the workings and the shortcomings of both the firms on whole. For this purpose, we have used mathematical and analytical tools of operations research. Keywords— Uber, Ola, Logistics optimalization, Route optimization, Operations research 1. INTRODUCTION Operational research (or) is an analytical method of troubleshooting and decision-making which is useful in managing organizations. In operational research, problems are divided into basic components and then resolved in the steps defined by mathematical analysis. Uber Technologies Inc. A peer-to-peer ridesharing, taxi cab, food distribution, bicycle-sharing, and transport network company (headquartered in San Francisco, California) with operations in 785 metropolitan areas worldwide (operating in the form of recovery) TNC. [1]. Its platforms can be accessed through its websites and mobile apps. Uber has been prominent in the shared economy, so as a result changes in industries are called Uberisation. Renters have been quoted as saying that they will pay before the ride request. -
Sharing and Caring Countries Report
Sharing and Caring COST ACTION CA16121 Member Countries Report on the Collaborative Economy May 2018 3 Table of Contents PREFACE .................................................................................................................................. 6 AUSTRIA ................................................................................................................................... 8 BELGIUM ................................................................................................................................ 11 BOSNIA & HERZEGOVINA ................................................................................................. 15 BULGARIA ............................................................................................................................. 16 CYPRUS .................................................................................................................................. 19 CROATIA ................................................................................................................................ 19 ESTONIA ................................................................................................................................. 21 FINLAND ................................................................................................................................ 25 FRANCE .................................................................................................................................. 27 GERMANY .............................................................................................................................