The expansion of e-commerce presents new opportunities for SMEs to enter broader markets at lower costs, but the new entrants face barriers to growth after entry. To help the new entrants to overcome these growth barriers, we implement a large-scale business training program as a randomized controlled experiment. The training focuses on practical skills specific to online business operations and reached over two million new sellers on a large e-commerce platform. Treated new sellers with access to the training earn higher revenues and attract more consumers to their sites. These sellers become more engaged in marketing and improve their customer service. Leveraging detailed consumer-seller matched search and browsing data, we find that consumers have higher purchase probability when they encounter new sellers regardless of treatment status. When making 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 the training leads to higher consumer surplus and sellers’ total revenues. As the operator of the online marketplace, the platform could earn more profits in both the short and the long run because of the training.

Download

©2020 by Yizhou Jin.