Uber’s early entry decisions in the US

ABSTRACT

Early entry decisions of the firm are crucial to its success. Ride-sharing businesses developed due to technology and government regulation. With the advent of the ride-sharing technology, firms like Uber, Lyft, etc. were faced with the decision of which markets to enter first. For this paper, a model is developed of a profit-maximizing firm constrained from entering all markets simultaneously. The entry decision of Uber into the 50 most populous US metropolitan statistical areas (MSA) is examined. The results suggest Uber’s entry decision was constrained and affected by both revenue potential and regulation in the local taxi industry.

KEYWORDS:

• Constrained entry
• uber
• regulation
• ride sharing

JEL CLASSIFICATION:

• L10
• L20

Acknowledgments

The author would like to thank the referees for many useful comments. The author would like to thank the Charles Koch Foundation for support for this research. The author would also like to thank James Mozur for research assistance. Of course, any remaining errors in this paper are the author’s alone.

Disclosure statement

No potential conflict of interest was reported by the author.

Notes

¹ The constraints on a business may be financial, bureaucratic or other. Regardless of which constraint or constraints are binding, a constrained business must decide where to enter first.

² This paper focused on Uber rather than other ride-sharing companies because Uber is the market originator and market leader.

³ An example of an indirect regulation would be one that impacts fuel costs for taxicabs but is not directly aimed at the industry. Price as a proxy for regulation can capture such indirect regulation while looking only at regulations directly aimed at the taxi industry may miss the indirect part of regulation.

⁴ Swofford (1999) discusses that dynamic profit concerns might affect the decision of a profit-maximizing firm in the face of potential resale of it product.

⁵ Uber offers a number of different products so entry is taken to be when Uber offered any product in a market.

⁶ The medium fare is a typical 5-mile radius including an initial charge and a per miles charge, but exclude tolls and surcharges.

⁷ Kalnins and Lafontaine (2013) found that further distance to firm headquarters was associated with shorter longevity.

⁸ Uber left the top 50 MSA Austin market after a regulatory dispute. Since this paper is not concerned with exit, as it is trying to predict entry into markets and Uber did enter that market, the Austin observation was kept in the data set.

⁹ Uber has multiple products. We called entry when they offered the first product in an MSA.

¹⁰ These other results are available from the author upon request.

¹¹ These data were provided by Dean Stansel. See deanstansel.com and Stansel (2031).

¹² The results of the basic model with median family income are qualitatively similar to those presented in Table 4. Those results are available from the author upon request.

¹³ Both public transportation variables, miles and trips, were tried in the various specifications. The results again remain very similar and are available from the author upon request.

¹⁴ Median MSA age was tried in place of percentage of the population 25 to 44 and median age was never statistically significant in any model tested.

Additional information

Funding

This work was supported by the Charles Koch Foundation [Summer Research Grant].