Efficient Resource Allocation Contracts to Reduce Adverse Events.

On online platforms, goods, services, and content providers, also known as agents, introduce adverse events. The frequency of these events depends on each agent's effort level. In "Efficient Resource Allocation Contracts to Reduce Adverse Events," Liang, Sun, Tang, and Zhang study continuous-time dynamic contracts that utilize resource allocation and monetary transfers to induce agents to exert effort and reduce the arrival rate of adverse events. They devise an iterative algorithm that characterizes and calculates such contracts and specify the profit-maximizing contract for the platform, also known as the principal. In contrast to the single-agent case, in which efficiency is not achievable, they show that efficient and incentive-compatible contracts, which allocate all resources and induce agents to exert constant effort, generally exist with two or more agents. Additionally, they also provide efficient and incentive-compatible dynamic contracts that can be expressed in closed form and are therefore easy to understand and implement in practice. Motivated by the allocation of online visits to product, service, and content suppliers in the platform economy, we consider a dynamic contract design problem in which a principal constantly determines the allocation of a resource (online visits) to multiple agents. Although agents are capable of running the business, they introduce adverse events, the frequency of which depends on each agent's effort level. We study continuous-time dynamic contracts that utilize resource allocation and monetary transfers to induce agents to exert effort and reduce the arrival rate of adverse events. In contrast to the single-agent case, in which efficiency is not achievable, we show that efficient and incentive-compatible contracts, which allocate all resources and induce agents to exert constant effort, generally exist with two or more agents. We devise an iterative algorithm that characterizes and calculates such contracts, and we specify the profit-maximizing contract for the principal. Furthermore, we provide efficient and incentive-compatible dynamic contracts that can be expressed in closed form and are therefore easy to understand and implement in practice. Funding: Y. Liang acknowledges support from the National Key R&D Program of China [Grant 2020AAA0103801] and the National Natural Science Foundation of China [Grant 71872095]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/opre.2022.2322. [ABSTRACT FROM AUTHOR]