우버의 전략과 그 시사점: 양면시장 이론과 운송서비스업을 중심으로 = Uber’s Strategy and Its Implications: Focusing on Two-sided Market Theory and Transportation Service Aspects

다국어 초록 (Multilingual Abstract)

Based on two-sided market theory and digital matching firms perspectives, we have addressed Uber’s strategy and its implications. Uber is a digital matching firm that provides a technology platform called Uber Service that links between the driver market and the client market. The essence of Uber’s strategy is to maximize the cross-network effects of these two markets. Uber has been trying to increase both the driver pool and the availability of transportation services in the driver market in order to boost the demand in the client market, which is in turn supposed to result in sales growth.
The cross-network effects have been possible thanks to the existence information asymmetry for Uber’s favor. The information asymmetry exists because of the nature of transportation service itself and the common features of digital matching firms. The information asymmetry has allowed Uber to influence its drivers as if they were its own employees without triggering any significant bureaucratic costs. The endeavors to influence its drivers (or driver-partners in Uber’s terminology) based on information asymmetry have constituted Uber’s strategies for sales expansion and firm growth.
To increase the supply of drivers Uber has resisted reasonable social demands and violated laws if necessary. For example, the company has lobbied against the tightening of background security checks of its potential drivers in the pretext of offering more opportunities for those under-privileged members of society so that they can earn more money. At the same time, to increase the rate of acceptance of service requests from the client, Uber has limited the supply of information on the requested service to its drivers. All of these efforts are geared toward increasing cross-network effects.
Uber’s efforts to increase the supply of drivers and services to enhance cross-network effects culminate in the strategy of surge pricing. which is made possible thanks to Uber’s price-setting market power and information asymmetry. Uber charges higher prices for certain location during certain time-span reflecting higher demands by the client. Prior studies have shown that surge pricing is credited with less waiting time for the client and higher income for the driver. But some drivers are quite sceptical about surge pricing, questioning the veracity of the demand.
‘Earn extra income during your free time’ has been a major claim by Uber in motivating a potential pool of drivers to sign up for the service. We have tried to derive drivers’ average income to see whether it is the case. Unlike prior studies that have relied on nominal income, we have incorporated conventional expenses in the equation to calculate actual income. For average drivers who worked in San Francisco area in the U.S., the actual income was not as impressive as claimed by the company. We believe that the calculation itself is rather rudimentary, but the outcome has implications for understanding drivers’ behaviors.
In the discussion, we have addressed theoretical and practical implications. We have discussed the implications of information asymmetry and market failure on the employee side on the theory of a firm. We also discussed the broad implications of Uber’s strategies on the transportation services and hospitality industry.

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