The “Ubernomics” of ridesourcing: the myths and the reality

ABSTRACT

This paper looks at the economics of ridesourcing (or app-based ride-hailing) with a particular focus on the US. It brings together the rather dispersed literature on the subject focusing on the economic characteristics of the underlying industry and sets this within the broader context of transportation economics. In particular, it sorts out the realities of ridesourcing from some of myths that were perpetrated in its early days and, in many cases, still persist. It considers some of the empirical evidence that has emerged regarding the key parameters that determine the way Uber and the like operate, and the welfare implications of this, together with comments on some of the regulatory reactions to the new transportation platform. It concludes by suggesting some ways in which recent developments in economic could move forward our understanding of the industry as technologies and markets change.     

The utilisation and user characteristics of Uber services in London

ABSTRACT

Ridesourcing services such as Uber are nowadays a common feature within available transport options of many cities around the world (E.g. London & San Francisco). There has been much publicity about the potential impacts of ridesourcing services and how (or if) they should be managed or regulated without an objective understanding of who uses these services and why, as well as its current and future implications for public transport (PT).

Ridesourcing is part of a broader tech-driven, mobile app-based sharing phenomenon – the ‘sharing economy’ – which has disrupted traditional market models and industries, for example, the transport industry, where new players such as Uber have emerged and have quickly become part of the urban transport landscape. Uber has been at the forefront in disrupting the transport sector since its first launch in 2010 (San Francisco, USA). Since its launch, Uber has generated extensive media coverage and debate among policymakers, transport planners and transport authorities on how these services are affecting traditional transport modes such as buses and taxis. However, without objective empirical data – in terms of impacts on trip making characteristics, PT ridership and congestion – policymakers and transport regulators are yet to fully understand the real impacts ridesourcing services are having on the transport network.

This paper is part of broader research that aims to provide insights and empirical-based evidence on how Uber services are used (UberX and Uberpool) in London. A comprehensive survey was undertaken using a detailed questionnaire, issued to UberX and Uberpool users in London to gather detailed data on who uses the Uber services, why they use it and what are the trip purposes, in order to understand Uber user demographics and what effects (if any) Uber services are having on PT usage and trip making characteristics in London. The final findings provide important insights on Uber user demographics, trip purposes, types of trips replaced, impact on car ownership and why travellers use Uber services.     

Taxi apps,regulation, and the market for taxi journeys

This paper attempts to provide a starting point for discussion on how smartphone-based taxi applications (‘apps’) have changed the market for taxi journeys and the resulting implications for taxi market regulation. The paper focuses on the taxi apps and their impact on taxi markets. It provides a brief history of taxi regulation before outlining the underlying economic rationales of its current form in many parts of the world, characterised as the “QQE” framework (quantity, quality and economic controls on operators). It argues that current regulation assumes that taxi markets are subject to three sets of problems that require correction by regulatory intervention, namely: those associated with credence goods, problems related to open access and those resulting from transactions occurring in a thin market. It is then proposed that taxi apps solve both the credence good and thin market problems whilst largely mitigating the problems associated with open access. The paper then presents some potential problems for taxi apps, namely the potential for instability on supply and demand sides, collusion and monopoly. It also discusses concerns about driver background checks and safety. The paper concludes by arguing that instead of restricting the growth of the taxi market, regulators should focus on reducing the likelihood of monopoly and collusion in a taxi market led by apps.     

Exploring the influence of built environment on Uber demand

Ride-sourcing services have made significant changes to the transportation system, essentially creating a new mode of transport, arguably with its own relative utility compared to the other standard modes. As ride-sourcing services have become more popular each year and their markets have grown, so have the publications related to the emergence of these services. One question that has not been addressed yet is how the built environment, the so-called D variables (i.e., density, diversity, design, distance to transit, and destination accessibility), affect demand for ride-sourcing services. By having unique access to Uber trip data in 24 diverse U.S. regions, we provide a robust data-driven understanding of how ride-sourcing demand is affected by the built environment, after controlling for socioeconomic factors. Our results show that Uber demand is positively correlated with total population and employment, activity density, land use mix or entropy, and transit stop density of a census block group. In contrast, Uber demand is negatively correlated with intersection density and destination accessibility (both by auto and transit) variables. This result might be attributed to the relative advantages of other modes – driving, taking transit, walking, or biking – in areas with denser street networks and better regional job access. The findings of this paper have important implications for policy, planning, and travel demand modeling, where decision-makers seek solutions to shape the built environment in order to reduce automobile dependence and promote walking, biking, and transit use.