Platform effects on traditional public transportation

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	DOI: 10.1257/aer.p20161002		DOI: 10.1257/aer.p20161002
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	Article Link: https://doi.org/10.1257/aer.p20161002		Article Link: https://doi.org/10.1257/aer.p20161002

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Revision as of 18:48, 4 December 2023

Context Statement: Uber's on-demand, personalized transportation has significantly impacted urban mobility, influencing traditional public transport systems' perception and usage. However, it has also raised concerns about viability, affordability, and adaptability.

Disruptive Change in the Taxi Business: The Case of Uber. The American Economic Review

Cramer, J., & Krueger, A. B. (2016). Disruptive Change in the Taxi Business: The Case of Uber. The American Economic Review, 106(5), 177–182.

DOI: 10.1257/aer.p20161002

Article Link: https://doi.org/10.1257/aer.p20161002

• Context

• Overview

Since the 1950s, the US has seen an increase in occupational licensing, with restrictions affecting roughly one-third of workers in the private sector. Ride-sharing firms like Uber and Lyft are giving the taxi business unprecedented competition. Uber drivers have a 30% greater capacity utilization rate than taxi drivers and work around half as many hours a week as drivers of limos and taxis. Uber's larger scale, flexible labor supply model, inefficient taxi rules, and more efficient matching technology are some of the factors that have contributed to this increased utilization rate.

The purpose of the study is to compile information on the capacity utilization rates of Uber and taxi drivers in various cities. The information is obtained from aggregated data from Seattle and Los Angeles as well as micro-level daily data on the work hours and time of taxi drivers. Individual-level data on drivers' work hours and the number of hours they had a fare-paying passenger in their car can be used to calculate the capacity utilization rate. The same days of the week and proximity to the Boston Marathon are reflected in the data for Uber drivers. Because they make up the largest and fastest-growing group of Uber drivers, the study focuses on UberX drivers. Based on Uber's administrative database for drivers in five cities, the information is presented. Because the cab data comes from a year earlier than the Uber data and covers a time before Uber made major inroads into the industry, the study also takes timing into account.

With the exception of New York, all five cities' UberX drivers had substantially greater capacity utilization rates than taxi drivers, according to the report. While taxi drivers in Boston had passengers in their cars anywhere from 32% of the time to nearly half of the time in New York City, UberX drivers spend around half of their working hours with passengers in their cars. In addition, UberX drivers have a greater mileage-based capacity utilization rate (Fm) than taxi drivers. In terms of the percentage of miles driven with a passenger in the car, UberX drivers in Seattle outperform taxis by 41%. UberX drivers in San Francisco had a greater utilization rate than taxi drivers at all hours, with the narrowest margin between 4 and 8 pm. The variations in the mean capacity utilization rates are not caused by a small number of drivers.

For a variety of reasons, UberX drivers may attain better capacity utilization rates than taxi drivers. These include ineffective taxi licensing laws, Uber's flexible labor supply model, its bigger scale, network efficiencies from scale, and its more effective driver-passenger matching technology. UberX drivers who put in at least seven hours a day had nearly comparable occupancy rates in New York, Seattle, and Los Angeles. This implies that the entry and exit of UberX drivers during the day balances the market, such that the utilization rate remains constant for all drivers, regardless of how long they work. In New York City, UberX drivers' usage rate is 3.5 percent greater than that of taxi drivers', indicating that the little variation in capacity usage rate may be explained by variations in driver-passenger matching technology. The results have an impact on for-hire drivers' productivity because UberX drivers may charge 28% less per hour than taxi drivers while still making the same money.

• Strengths and Weaknesses
• Assessment

Uber, Public Transit, and Urban Transportation Equity: A Case Study in New York City

• Context
• Overview
• Strengths and Weaknesses
• Assessment

The Sharing Economy in Social Media: Analyzing Tensions Between Market and Non-market Logics

• Context
• Overview
• Strengths and Weaknesses
• Assessment