Various types of incentive systems are widely used by many companies and organizations for better performances. However, despite the demand for the fair incentive systems, those systems in academia have not been well established and fairly operated. Using an example of a professor evaluation system, we examine two main problems of the existing incentive systems in academia - ignoring the input aspect and focusing only on the short-term performance. By applying the super-efficiency DEA and considering multi-period output, we show that the input factors and the time trend of outcomes need to be incorporated for the fair evaluation of professors and their research performance.
All Science Journal Classification (ASJC) codes
- Computer Science Applications
- Artificial Intelligence