A Model of Direct-to-Consumer Live Selling
Professor D.J. Wu
Ernest Scheller Jr. Chair in Innovation, Entrepreneurship Commercialization
Professor of Information Technology Management
The Scheller College of Business, Georgia Institute of Technology
Our study investigates an emerging e-commerce model for small businesses, where the entrepreneur acts as both an online influencer and a direct-to-consumer (DTC) live seller. We consider how a streamer, facing limited cognitive capacity of its followers, allocates the communication bandwidth between two competing activities: educating consumers about product categories (which builds informed consumers) versus describing specific products (which enables precise product-consumer matching). This trade-off shapes market outcomes by interacting with observational learning within the streamer’s follower group and urgency associated with the live selling format.
Our analysis yields four insights. First, a streamer benefits from observational learning within its follower group only if its product quality is not too high. Second, observational learning can raise total consumer surplus. Third, educating consumers allows streamers to charge premiums for products with moderate quality but may reduce overall consumer surplus. Finally, expanding the follower group is not always optimal for the streamer even if costless, although effective education makes expansion more attractive. The findings carry implications for seller strategy, platform design, and consumer protection in this rapidly growing online selling format.
Key words: E-Commerce, Live Streaming, Live Selling, Online Influencer, Real Time Retailing, Entrepreneurs
D. J. Wu holds the Ernest Scheller Jr. Chair in Innovation, Entrepreneurship, and Commercialization. He is a Professor of IT Management and the Area Chair of IT Management at the Scheller College of Business, Georgia Institute of Technology. He earned his undergraduate degree in Computer Science and Technology from Tsinghua University and obtained his Ph.D. from the Wharton School, University of Pennsylvania.
Dr. Wu’s research interests include the economics of digital innovation and transformation, digital business model innovations, platform ecosystems, enterprise information technology, and artificial intelligence and machine learning. His recent work has been published in leading academic journals such as Management Science, Information Systems Research, Manufacturing and Service Operations Management, MIS Quarterly, and Production and Operations Management. In 2023, he was recognized as a Distinguished Fellow by the INFORMS Information Systems Society.
Currently, Prof. Wu serves as a Department Editor for Information Systems at Management Science. He is also a Co-Editor for the Management Science Special Issue on the Human-Algorithm Connection and the Special Issue on Analytical Creativity at Information Systems Research. Previously, he served as a Senior Editor for Information Systems Research (2018–2020) and as President of the INFORMS Information Systems Society (2019–2021).
