Incentive Mechanism for University Teachers under Multi-task Principal-Agent Model
Lu Fang, Jiangshun Zhang, Dingti Luo · 2014
Currently universities have faced a popular realistic subject, that is, how to construct a reasonable salary incentive mechanism based on two tasks of teaching and scientific research for teachers. This paper builds a multi-task principal-agent model based on those tasks which are delegated to teachers by universities. Then, through in-depth analysis of the model, we explore the relationships among teachers' effort level, relative incentive intensity, tasks' uncertainty degree, and their risk aversion. The results show that, when teachers' risk aversion and tasks' uncertainty degree become bigger, their effort level will become lower. Secondly, the relative incentive intensity will reduce with the increase of the uncertainty of teaching task and the relative incentive intensity will increase with the increase of the uncertainty of scientific research task. Finally, teachers should be motivated differently according to tasks uncertainty and risk aversion.