This project will examine the availability and pricing patterns of ride-sharing services in a major metropolitan area in the US. We examine how the strategies chosen by competitors impact market outcomes, with a focus on understanding differentiating factors in services. One objective will be to map out how competitive intensity varies across micro-geographies, and the degree to which different external factors contribute to these strategies and outcomes. A second objective is to understand how the phenomenon of driver clustering impacts performance of ride-sharing platforms.
The undergraduate student(s) will help obtain data, organize and structure the data, and perform preliminary statistical analyses. The student(s) will also help with a general literature review. The skills required will be familiarity with some programming. The student(s) will learn how to use and manage very large datasets. The student(s) will also learn how to obtain data from a variety of Internet sources, connect elements in database, conduct a literature review, perform statistical analyses (e.g., regression analysis) and interpret results of such analyses. These skills will be valuable preparation for a research project in any area of economics and statistics, and especially a senior essay or thesis.