Lifting Growth Barriers for New Firms: Evidence from an Entrepreneur Training Experiment with Two Million Online Businesses

Expansion of e-commerce presents new opportunities for small and medium enterprises (SMEs) to enter broader markets at lower costs, but the new entrants face barriers to growth after entry. To facilitate the new entrants to overcome these barriers, we implement a training program as a randomized controlled experiment with over two million new sellers on a large e-commerce platform. The training focuses on practical skills specific to online business operations. Treated new sellers with access to the training earn higher revenues. These sellers improve marketing skills and attract more consumers to their online stores. Leveraging detailed consumer-seller matched search and browsing data, we find that consumers have higher purchase probability overall when they encounter new sellers regardless of treatment status. In the cases of purchases, consumers choose treated new sellers over incumbents; moreover, doing so does not lower the quality of their purchases. We use a structural model to characterize consumer demand and recover sellers’ underlying quality. Both treated and control new sellers have a higher quality compared to incumbents. The training increases new sellers’ likelihood of being encountered by consumers, which improves the matching quality between consumers and sellers. The counterfactual exercise shows that training leads to a higher consumer surplus and the platform’s total sales due to market expansion. The platform could increase profits in both the short and the long run because of the training.


Zhengyun (Patricia) Sun a Ph.D. candidate in the Department of Economics specializing in development economics and applied microeconomics. Her research seeks to understand how digital technology affects firms and individuals in developing countries. She is currently focused on small and medium enterprises in the e-commerce market and investigated the growth barriers faced by new entrants and the impacts of adopting data-driven decision-making for the firms and the platform. She has previously worked on the influence of digital technology in education and agriculture. She earned B.A. in Applied Mathematics, Economics and Geography at UC Berkeley with highest honors in 2014.


Speaker(s) Ms Zhengyun (Patricia) SUN
PhD Candidate, Department of Economics, Harvard University
Date 18 Jan 2021 (Monday)
Time 12:00 noon
Venue Online Via ZOOM (link will be sent via email)

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