Ridesharing platform, Uber has been increasing the gender diversity of its workforce, which was 56.5 percent male and 43.5 percent female as of 31 December 2023. The above figures only refer to staff that are employed directly by Uber, and do not include drivers.

This statistic illustrates the distribution of Uber employees in the United States from 2017 to 2020, sorted by ethnicity. In 2020, 37.2 percent of U.S. Uber's employees were of Asian ethnicity. The majority of employees were white.

This statistic shows the rideshare vehicle of choice among Uber and Lyft drivers in the United States as of February 2018. During the survey, **** percent of the respondents stated that they drive a Toyota vehicle.

Ridesharing Industry statistics: The ridesharing industries are different companies that include transportation networks and ride-hailing services that provide one-way transportation commonly termed as e-taxis or app-taxis. The well-known and biggest ride-sharing companies are Uber and Lyft. The overall market share of the ridesharing industry in 2022 has accounted for around $95.09 billion to $100.55 billion and is expected to reach a CAGR of 17.2% by the end of 2029 with $305 billion. Currently, ridesharing applications are mostly used across the world, especially in urban areas and almost 36% of Americans are using these apps in their daily life. The following Statistics from several aspects will provide light on why Ridesharing Industry is becoming so popular. Editor’s Choice In the United States, almost 36% of people are the part of Ridesharing Industry in 2022. The top two companies in this industry are Uber and Lyft in the U.S. The Ridesharing market size of North America increased by 68% by the end of 2022 with $13.6 billion. In the U.S. 2022, the share of sales rideshare market of Uber was 71% and Lyft's was 29%. By the end of 2026, the global market share of ridesharing is expected to be $185.1 billion. The monthly services of ridesharing applications were around 26%. This industry mainly includes the Taxi segment and Ride-hailing transportation sector. As of 2023, this U.S. industry has projected to reach $71.78 billion and expects annual growth of 1.07% by the end of 2027 with a $74.91 billion market volume. Currently, 28.1% is the user penetration of this industry in the U.S. As of January 2022, the average sales per customer of Uber were $72 and Lyft was $66.

In the third quarter of 2025, *** million people used the Uber app at least once per month. This is a **** percent increase compared to the third quarter of 2024 or a **** percent increase compared to the previous quarter. Uber is one of the most popular ride-sharing apps in the world. Based in San Francisco, their global net revenue amounted to ***** billion U.S. dollars in 2024. Contributing to their revenue are the 11.3 billion rides that were delivered via the Uber app that year. In 2024, Uber generated ***** billion U.S. dollars in gross bookings worldwide. U.S. ride-sharing market The ride-sharing market has experienced a giant surge in recent years. The ride-sharing market allows for consumers in need of a ride to instantly call for one via their smartphone and GPS satellites. This is comparable to a taxi service but can in some cases be significantly cheaper. However, drivers for these apps do not usually hold the same licensing requirements as taxi drivers. Uber and Lyft are the two largest companies in this sector, although Uber continues to outperform Lyft. In 2023, Uber's reported global revenue was more than eight times that of Lyft, which recorded *** billion U.S. dollars in revenues. As of the third quarter of 2025, Uber's user base has reached *** million users, indicating continued growth in the ride-sharing market.

I developed this dataset as an entry for the Data School Down Under challenge. It is based on a realistic trips profile I extracted from my own real dataset of trips I did as an Uber driver, as well as demographic data, drive times data (from TomTom) and Uber fares data. The trips are assigned to days of 2021, and represent a sample of all Uber trips in Sydney.

Key Taxi App StatisticsTop Taxi AppsTaxi App Market SizeTaxi Revenue by AppTaxi App UsersTaxi App Market Share USTaxi App Market Share UKTaxi App Market Share IndiaIn a wave of entrepreneurship in...

Recruiting and retaining drivers is seen by industry watchers as a tough battle for XYZCab. Churn among drivers is high and it’s very easy for drivers to stop working for the service on the fly or jump to Uber depending on the rates.

As the companies get bigger, the high churn could become a bigger problem. To find new drivers, XYZCab is casting a wide net, including people who don’t have cars for jobs. But this acquisition is really costly. Losing drivers frequently impacts the morale of the organization and acquiring new drivers is more expensive than retaining existing ones.

You are working as a data scientist with the Analytics Department of XYZCab, focused on driver team attrition. You are provided with the monthly information for a segment of drivers for 2019 and 2020 and tasked to predict whether a driver will be leaving the company or not based on their attributes like • Demographics (city, age, gender etc.) • Tenure information (joining date, Last Date) • Historical data regarding the performance of the driver (Quarterly rating, Monthly business acquired, grade, Income)

Column Profiling: 1. MMMM-YY : Reporting Date (Monthly) 2. Driver_ID : Unique id for drivers 3. Age : Age of the driver 4. Gender : Gender of the driver – Male : 0, Female: 1 5. City : City Code of the driver 6. Education_Level : Education level – 0 for 10+ ,1 for 12+ ,2 for graduate 7. Income : Monthly average Income of the driver 8. Date Of Joining : Joining date for the driver 9. LastWorkingDate : Last date of working for the driver 10. Joining Designation : Designation of the driver at the time of joining 11. Grade : Grade of the driver at the time of reporting 12. Total Business Value : The total business value acquired by the driver in a month (negative business indicates cancellation/refund or car EMI adjustments) 13. Quarterly Rating : Quarterly rating of the driver: 1,2,3,4,5 (higher is better)

Over ***** quarters of Lyft drivers in United States and Canada were members of racial minorities in 2024. Over a third of Lyft drivers identified as Hispanic or Latin American, while just under a quarter identified as Black or African American or Canadian. Lyft operates ride-sharing services in the United States and Canada.

Context

UBER collects thousands of data points on each and every ride but it only shares a tiny part of this data with its drivers. A driver can get weekly statements from his/her personal dashboard on UBER's website. This way a driver has an opportunity to check each ride that has been made with detailed info on the earnings.

Content

Not only each weekly statement includes a unique ID and exact time of each ride but it also shows a complex structure of driver fares. Besides basic components like time, distance, and tips, driver's fares can also include promotions, surge charges, long pick-up fees, reimbursements, and many more. You can see detailed descriptors of each feature below.

Inspiration

My initial research question was simple: "Is there a difference in riders' tipping behavior like tip size and frequency on different weekdays?" But after spending some time digging into this problem it became clear that tipping is a much broader scientific field with lots of research. However, most researches were made way before services like Uber appeared and were mainly focused on tipping behavior in restaurants which obviously differs a lot. Here's one of the recent researches by former Uber and Lyft employees on tipping behavior: "The Driver’s of Social Preferences: Evidence from a Nationwide Tipping Field Experiment" by Chandar, et. al (2019)

Other research question could be: Why certain people tip and others don't? Are riders more likely to tip as the fare of the trip increses? Is that true that late-night rides are tipped more often? Can we predict the size or frequency of the tip based on the fare data only?

This statistic shows the share of ride-hailing services drivers in the United States as of January 2017, by ethnicity. During the survey, 7.1 percent of the respondents stated that they are Hispanic or Latino.

The global Ridesharing Services market is poised for substantial expansion, projected to reach an estimated $XX billion by 2025, exhibiting a robust Compound Annual Growth Rate (CAGR) of XX% during the forecast period of 2025-2033. This growth is primarily fueled by a confluence of evolving consumer preferences, increasing urbanization, and the pervasive adoption of smartphones. As city populations swell and traffic congestion intensifies, the demand for convenient, cost-effective, and on-demand transportation solutions offered by ridesharing platforms continues to surge. Technological advancements, including enhanced GPS accuracy, seamless in-app payment systems, and sophisticated algorithms for driver-rider matching, further underpin this market's upward trajectory. The convenience of booking a ride with a few taps on a mobile device has revolutionized personal mobility, making ridesharing a preferred alternative to traditional taxi services and private vehicle ownership for a growing demographic. The market is characterized by a dynamic competitive landscape and evolving consumer behaviors across various age segments and device types. Mobile terminals are the dominant interface for accessing ridesharing services, reflecting the ubiquitous nature of smartphones. While younger demographics (18-34) represent a significant user base, the appeal is broadening across older age groups (35-64) as the services become more accessible and trusted. Geographically, the Asia Pacific region is emerging as a major growth engine, driven by large populations, rapid urbanization, and the presence of key players like Didi Chuxing and Grab. North America and Europe remain mature yet steadily growing markets, with ongoing innovation and consolidation. However, challenges such as regulatory hurdles in certain regions, driver supply fluctuations, and intense price competition from established and emerging players will continue to shape the market's future.

TLC Trip Record Data The yellow and green taxi trip records include fields capturing pick-up and drop-off dates/times, pick-up and drop-off locations, trip distances, itemized fares, rate types, payment types, and driver-reported passenger counts. The data used in the attached datasets were collected and provided to the NYC Taxi and Limousine Commission (TLC) by technology providers authorized under the Taxicab & Livery Passenger Enhancement Programs (TPEP/LPEP). The trip data was not created by the TLC, and TLC makes no representations as to the accuracy of these data.

The For-Hire Vehicle (“FHV”) trip records include fields capturing the dispatching base license number and the pick-up date, time, and taxi zone location ID (shape file below). These records are generated from the FHV Trip Record submissions made by bases. Note: The TLC publishes base trip record data as submitted by the bases, and we cannot guarantee or confirm their accuracy or completeness. Therefore, this may not represent the total amount of trips dispatched by all TLC-licensed bases. The TLC performs routine reviews of the records and takes enforcement actions when necessary to ensure, to the extent possible, complete and accurate information.

The online car-hailing platform market is experiencing robust growth, driven by increasing smartphone penetration, urbanization, and the rising preference for convenient and affordable transportation solutions. The market, valued at approximately $200 billion in 2025, is projected to exhibit a Compound Annual Growth Rate (CAGR) of 15% from 2025 to 2033, reaching an estimated value exceeding $700 billion by 2033. Key growth drivers include the expanding adoption of ride-sharing apps across various demographics, technological advancements like AI-powered route optimization and surge pricing, and the increasing integration of electric vehicles within the car-hailing ecosystem. The market is segmented by operating system (Android and iOS) and platform type (full-time and part-time). Full-time platforms dominate due to their established brand recognition and comprehensive service offerings. Geographic expansion, particularly in emerging markets with rapidly growing populations and increasing disposable incomes, represents a significant opportunity for growth. However, challenges remain, including regulatory hurdles in different regions, intense competition among established players and new entrants, and concerns regarding driver compensation and platform safety. The competitive landscape is dominated by global players such as Uber, Lyft, and Didi Chuxing, but regional players and smaller niche operators also play significant roles. The industry is also facing increasing pressure to improve transparency and address issues related to pricing and driver welfare. The future trajectory of the online car-hailing market is poised for continued expansion, although the pace of growth may fluctuate based on economic conditions and regulatory frameworks. Innovation within the sector, including the introduction of autonomous vehicles and advanced logistics solutions, is likely to reshape the landscape in the coming years. Companies are likely to focus on enhanced user experiences, personalized services, and strategic partnerships to maintain a competitive edge. Market expansion into underserved areas and the development of sustainable transportation options will be crucial for long-term success. The strategic acquisition of smaller, specialized companies will likely shape the future market consolidation and dominance of a few key players. Furthermore, addressing the environmental impact of the industry through initiatives like promoting electric vehicle adoption will become increasingly important.

The Mexico ride-hailing market, valued at $3.34 billion in 2025, is poised for substantial growth, exhibiting a Compound Annual Growth Rate (CAGR) of 5.02% from 2025 to 2033. This expansion is driven by several factors. Increasing urbanization in Mexico leads to higher demand for convenient and efficient transportation alternatives, especially in major metropolitan areas. The rising adoption of smartphones and readily available internet access further fuels the market's growth by facilitating easy access to ride-hailing apps. Furthermore, the growing middle class with increased disposable income contributes to higher spending on convenient transportation solutions. The preference for ride-hailing services over traditional taxis, particularly among younger demographics, also significantly impacts market expansion. Competitive pricing strategies employed by various players, coupled with innovative features like ride-sharing options and diverse vehicle choices (two-wheelers, passenger cars), contribute to the market's dynamism. However, regulatory hurdles and concerns regarding driver safety and compensation could act as potential restraints on market growth. The segmentation of the market, encompassing various service types (e-hailing, car-sharing, car rental), booking channels (online, offline), and vehicle types, indicates a market ripe for further specialization and tailored offerings. The market's projected growth from 2025-2033 necessitates a strategic approach for companies operating within it. Companies like Uber, Lyft, Didi Chuxing, and local players need to adapt to the unique characteristics of the Mexican market. This requires understanding local regulations, cultural preferences, and competitive landscapes. Focusing on technological innovation, improving user experience, and enhancing driver welfare will be key factors for success. Diversification of service offerings catering to specific market segments (e.g., focusing on intercity travel for tourists or intracity transportation for commuters) will also present significant opportunities for revenue generation and market share expansion. The forecast period should see a steady increase in market value, driven by the factors mentioned above. Effective risk management strategies to address the challenges posed by regulations and safety concerns will be crucial to maintain a sustainable growth trajectory. This report provides a detailed analysis of the dynamic Mexico ride-hailing market, covering the period 2019-2033, with a focus on the pivotal year 2025. We delve into the market's size, segmentation, growth drivers, challenges, and future prospects, offering invaluable insights for investors, businesses, and policymakers. Keywords: Mexico ride-hailing market, Mexico e-hailing, Mexico car sharing, ride-sharing Mexico, Mexico transportation market, Mexico mobility market, peer-to-peer ride-sharing Mexico. Recent developments include: February 2024: The ride-share platform inDrive collaborated with the financial technology firm R2 to offer loans to its drivers in Mexico., July 2023: Hoop Carpool, the shared mobility startup, raised USD 1.3 million in investment funds in a round led by Ship2B Ventures through BSocial Impact Fund, with additional support from Banco Sabadell, FEI, AXIS, and 4Founders Capital., June 2022: International Finance Corporation (IFC) invested USD 15 million in BlaBlaCar to support the shared-travel platform's growth in Mexico and Brazil., February 2022: Beat, the ride-hailing app, introduced Beat Zero, a new innovative service with a private fleet of fully electric cars operated by hired drivers, to ensure an amazing transportation experience from pick up to drop off.. Key drivers for this market are: Growing Tourism Industry in Australia. Potential restraints include: Varying Government Regulations on Taxi Services. Notable trends are: Online Booking Channel is Expected to Drive the Market Growth.

Financial overview and grant giving statistics of New Vision Taxi Drivers Association Of Miami Inc

Descriptive statistics of socio-demographic characteristics.

The Australia Taxi Market Report is Segmented by Service Model (Traditional Metered Taxi, Platform-Integrated Metered Taxi, and Shared/Shuttle), Booking Channel (App/Online, and More), Vehicle Body Style (Sedan, and More), Vehicle Class (Economy, and More), End User (Corporate, and More), Fuel Type (Petrol, LPG, and More), and States/ Territory. The Market Forecasts are Provided in Terms of Value (USD).

Definitions of socio-demographic characteristics.

Graph and download economic data for Employed full time: Wage and salary workers: Taxi drivers and chauffeurs occupations: 16 years and over: Men (LEU0254628600A) from 2000 to 2019 about taxi, occupation, full-time, males, salaries, workers, 16 years +, wages, employment, and USA.