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This paper studies the variation in returns to digital retail entrepreneurship across locations in a large online marketplace. Digital platforms enable access to knowledge, resources, and customers across long geographic distances, rendering costs and barriers to business activities less constrained by the local environment. Digital entrepreneurs outperform in rural and low-wage urban areas with lower turnover rates. In slack labor markets, more unemployed individuals cannot find jobs in the wage sector due to job rationing. Digital platforms absorb this excess supply of high-quality labor, which results in a substantial premium in aggregate revenues across digital retailers in locations with slack labor markets. Consistent with this mechanism, the job turnover rate in the local labor market positively moderates local wage's impact on digital retailers' aggregate revenues. In tighter labor markets where workers move between the wage sector and self-employment more frequently, returns to different earnings options converge faster. Our results imply that digital platforms particularly benefit individuals in slack labor markets where local earnings opportunities are limited and workers change jobs less frequently. Our results suggest a close connection between the health of local labor markets and the aggregate returns to digital entrepreneurship in a given region. [ABSTRACT FROM AUTHOR]

The benefits to data analytics and machine learning have been distributed unevenly across firms around the world. Research on IT productivity points to intangible capital as a key driver of value creation from innovation in computing. We argue that a crucial component of intangible capital is organization-wide technological architecture, which is idiosyncratic and difficult to measure. We use a novel survey instrument to quantify large corporations' data architecture capabilities by their closeness to "best practices" of frontier digital companies. Using the prevalence of third-party maintenance as a proxy for legacy servers before 2016 and an instrument for data architecture coherence, we find that improving data architecture coherence leads to more intensive machine learning capabilities and substantially higher productivity growth in the subsequent three-year period. Legacy servers reduce data architecture coherence particularly at corporations with complex software systems, consistent with the hypothesis that costs of digital transformation are greater when workers need to develop more complicated co-invention processes to interact with technical systems. [ABSTRACT FROM AUTHOR]