报告题目：Mergers between on-demand service platforms: The impact on consumer surplus and labor welfare
报 告 人：芦涛（Erasmus University Assistant Professor）
主 持 人：傅科（中山大学岭南学院 教授）
This paper studies the impact of mergers between on-demand service platforms on consumer surplus and labor welfare. We analyze a game-theoretical model in which customers choose between platforms based on prices and expected waiting times, and agents base decisions about which platform to work for on wages and the probability of getting jobs. Driven by these two features, we find that mergers between on-demand service platforms have several welfare implications that have not been documented by previous research. While a merger reduces competition, we show that customers may benefit from a merger due to the risk-pooling effect and reduced waiting times; moreover, if customers are sufficiently sensitive to delay, this benefit can spill over to the labor force via cross-side network externalities. We further establish that a win-win-win outcome, in which merging firms, customers and agents are all better off, can always be achieved if the merged platform commits to certain ratios between prices and wages. This implies that antitrust agencies can enforce restrictions on the payout ratios to protect both consumers and agents. Finally, we illustrate our main insights by implementing our model in numerical experiments calibrated using real data from large on-demand ride-sharing platforms.
Tao Lu is an assistant professor at the Department of Technology and Operations Management, Rotterdam School of Management, Erasmus University. He holds a Ph.D. degree from the Department of Industrial Engineering and Logistics and Technology, Hong Kong University of Science and Technology. His research interests lie in the areas of supply chain management, ocean transport logistics, operations in the sharing economy. His work has been published (or forthcoming) in leading journals such as Manufacturing and Service and Operations Management, Operations Research and Production and Operations Management.