Working Papers

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Data Governance, Interoperability and Standardization: Organizational Adaptation to Privacy Regulation (with M. Iansiti)

Abstract: The increasing availability of data can afford dynamic competitive advantages among data-intensive corporations, but governance bottlenecks hinder data-driven value creation and increase regulatory risks. We analyze the role of two technological features of data architecture that facilitate internal data governance – Application Programmatic Interfaces (APIs) that publish interdepartmental data and standardization of identity and access management (IAM) software – in shaping large data-intensive corporations’ adaptation to privacy regulation. Using annual establishment data for the largest U.S. financial services corporations and the enforcement of the General Data Protection Regulation (GDPR) in 2018 as a natural experiment, we show that internal data APIs and standardization of IAM software significantly mitigate establishments’ revenue loss and IT budget reduction in response to GDPR enforcement. Compliance costs measured by IT hiring increased substantially after GDPR enforcement only for firms without internal data APIs. Our findings highlight the importance of interoperability and standardization as technical conditions that facilitate dynamic integrative capability, allowing large data-intensive corporations to ensure proper data governance and adapt to privacy regulation.

Local Labor Market Frictions and Platform-Dependent Entrepreneurship (with Y. Lyu)

Abstract: This paper examines the relationship between local labor market conditions and platform-based entrepreneurs' performance. Drawing on the labor market frictions perspective, we hypothesize that local job scarcity induces high-ability individuals to sort into self-employment, increasing the share of high-quality entrepreneurs entering digital platform-based entrepreneurship. Combining data from a large online marketplace with official labor market statistics across U.S. states, we show that entrepreneurial businesses entering the platform in low vacancy rate locations achieve superior revenue performance. We also show that the vacancy rate positively moderates the relationship between local wages and entrepreneurial revenues. Finally, those entering platform-based entrepreneurship in low vacancy labor markets are more likely to multi-home and have a business partner, consistent with choosing founding strategies associated with being higher quality.

Sampling Bias in Entrepreneurial Experiments (with R. Koning and R. Nanda)

Abstract: Using data from a prominent online platform for launching new digital products, we document that ‘sampling bias’—defined as the difference between a startup’s target customer base and the actual sample on which early ‘beta tests’ are conducted—has a systematic and persistent impact on the venture’s success. Specifically, we show that products with a female-focused target market launching on a typical day, when nine in ten users on this platform are men, experience 45% less growth a year after launch than those for whom the target market is more male-focused. By isolating exogenous variation in the composition of beta testers unrelated to the characteristics of launched products on that day, we find that on days when there are unexpectedly more women beta testers on the platform—reducing the amount of sampling bias for female-focused products—the gender-performance gap shrinks towards zero. Our results highlight how sampling bias can lead to fewer successfully commercialized innovations for consumers who are underrepresented among early users.