2020-01-08 | Chong Zhang: Information asymmetry and innovative policy design on digital platforms
The talk will discuss two research papers on complex managerial problems with information asymmetry on digital platforms.
The talk will be mostly focused on “Signaling Quality with Return Insurance: Theory and Empirical Evidence”. In this paper, we focus on quality issues on online shopping platforms as an adverse selection problem between sellers and customers and examine the impact of an innovative return policy, return insurance, emerging on various shopping platforms such as Taobao.com and JD.com. Return insurance is underwritten by an insurer and can be purchased by either a retailer or a consumer. Under such insurance, the insurer partially compensates consumers for their hassle cost associated with product return. We analyze the informational role of return insurance when product quality is the retailer’s private information, consumers infer quality from the retailer’s price and insurance adoption, and the insurer strategically chooses insurance premiums. We show that return insurance can be an effective signal of high quality. When consumers have little confidence about high quality and expect a significant gap between high and low qualities, a high-quality retailer differentiates itself from a low-quality retailer solely through its adoption of return insurance. We confirm, both analytically and empirically with a data set consisting of over 10,000 sellers on JD.com, that return insurance is more likely adopted by higher-quality sellers under information asymmetry. Furthermore, compared to free return (i.e., retailers directly compensate for consumers’ product-return hassles), return insurance is a stronger signal of quality, due to the role of the third party, the insurer. Despite its capability to signal quality, return insurance is costly for the retailer. Particularly, both high-quality and low-quality retailers are sometimes strictly worse off due to the option of purchasing insurance. Nevertheless, return insurance can improve consumer surplus and reduce product returns. Its profit advantage to the insurer is most pronounced under significant information asymmetry.
In addition, the talk will briefly discuss another paper on moral hazard issues between platforms and product/service producers. In “Dynamic Contract for Efficient Resource Allocation”, we consider a dynamic mechanism design problem where a principal (e.g., a platform) allocates a fixed amount of resource (e.g., online traffic) to one or multiple agents (e.g., retailers), who are more efficient in terms of welfare generation. However, the agents may trigger Poisson processes of adverse events (e.g., counterfeit goods), of which the arrival rates depend on the effort processes exerted by the agents. The efficient contract, therefore, focuses on utilizing monetary transfers as well as resource allocation strategies to induce effort from the agents while maximizing social welfare. We formulate both a single-agent model and a multi-agent model as infinite-horizon stochastic optimal control problems. The analytical solution to the single-agent model is endowed with an intuitive structure and is easy to implement. The multi-agent model, on the other hand, is more complex to analyze. Surprisingly, we find out that efficient resource allocation is always possible following some incentive compatible mechanisms, and we devise an iterative algorithm to calculate such mechanisms as well as the associated utilities of the agents. The results offer perspicuous economic explanations and insights. We also characterize in an easy-to-implement analytical form one of such incentive compatible efficiency inducing mechanisms.
Chong Zhang is a final year PhD candidate in Management Science and Engineering at School of Economics and Management, Tsinghua University. Before joining Tsinghua, she received her B.S. in Industrial Engineering at Beihang University. She is broadly interested in platform operations, information economics, and dynamic mechanism design. Her current research integrates both theoretical modeling and data analysis to study complex managerial problems with information asymmetry on digital platforms.