科学研究

Zhuoran Lu is an Assistant Professor at Fudan University School of Management. He received his B.A. in economics from Tsinghua University and his Ph.D. in economics from UCLA. He is a microeconomic theorist, with interests in contract theory, information economics and industrial organization. His recent research studies the optimal pricing strategy for signaling goods, the optimal pricing and seeding strategies for smart products, and the incentive design for teams with network-based peer monitoring.

Motivated by the ever-increasing prevalence of agile teams, we consider a team incentive design problem where multiple agents are located on a network and work on a joint project. The principal seeks the cheapest mechanism to incentivize the agents to exert costly efforts. In our setting, the principal chooses the work sequence and the rewards to the agents upon success. Whereas the agents’ actions are hidden to the principal, they may be observed among the agents given the internal information that is determined by the network and sequence. We show that under complementarity, the transparency of the agents’ actions can reduce their incentive costs. Moreover, the effectiveness of transparency decreases as an action becomes more transparent. In the optimal sequence, the agents work sequentially, with more important agents working later. The agents in later stages effectively monitor their preceding peers and have higher incentive costs. When the team consists of multiple sub-teams, larger sub-teams are allocated towards both ends of the optimal sequence, and only a small fraction of the agents will serve as monitors. For several typical networks, simple algorithms are offered to explicitly characterize the optimum.