UBERWORLD

• Principal investigator: Bilgehan Uzunca
• Research group: Esade Entrepreneurship Institute (EEI)
• Funding body: MICINN-MCIU

About the project

As the poster child of disruptive technology platforms, Uber has been transforming the fundamental issues in strategy. Its competitive approach incorporates direct and indirect interference via application of big data, machine learning and algorithmic management, as well as its corporate ownership structure, mobilization and lobbying when managing market and non-market participants, including drivers, riders, incumbent taxi companies, local/national governments, shareholders, and other ride-hailing platforms. Within this research program, we aim to look at how Ubers strategies are shaped at different levels (i.e., individual, firm, country) as well as the performance implications of these strategies that shape its environment (i.e., driver manipulation/satisfaction, competitive dynamics, ban/exit decisions, and scaling up globally).

For the individual level, we extrapolate the power and knowledge asymmetries and no employment contracts between Uber and its drivers and investigate how the company resorts to behavioral strategies and algorithmic management, including nudging i.e., liberty-preserving approaches that steer people in particular directions when managing this large, disaggregated workforce. The use of nudges is seldom analyzed in the platform governance literature, and we aim to develop and conduct a survey and an experiment among Uber drivers to understand whether nudging is an effective form of platform governance.

For the firm level, we will look at internationalization strategies of Uber and its corporate ownership structure. Ubers strategies to scaleup globally has been influenced from fragmented/local network effects, which allowed regional ride-hailing platforms, such as Grab (Singapore), Ola (India) and Didi (India), to reach critical masses with lower prices. Furthermore, common ownership of Softbank in all these companies (30% Grab, 25% Ola, 20% Didi, 16.3% Uber) presents itself as a unique and underexplored type of external friction that can influence competitive dynamics. Interestingly, following Softbanks investment in Uber, the company abruptly decided to exit Southeast Asian markets after selling its regional units in exchange for significant stakes in these local competitors. To test our predictions about competitive interference of common owners, we will familiarize ourselves with and analyze the Common Ownership Dataset provided by Backus, Conlon, & Sinkinson (2020).

For the country level, we aim to study how collectively organized incumbents challenge the entry of firms with disruptive business models in regulated markets. We suggest that the tactics incumbents’ resort to as part of their non-market strategy are not all equally effective in controlling competition, and that some tactics and frames are more likely to force new entrants out of the market. In particular, we plan to look at the effect of different types of taxi protests, such as lawsuits, strikes, public demonstrations and violence, as well as how taxi companies frame their grievance in these protests, e.g., regulation, unfair competition, tax avoidance, or labor issues in order to get Uber banned from the market. We have started collecting a novel dataset of anti-Uber protests in 22 European countries in the period 2013-17, and we would like to expand this dataset towards 2021 as many developments and ban decisions have taken place in several European countries.