Purpose: The purpose of this paper is to define the relative optimal incentive contract to effectively encourage employees to improve work efficiency while actively implementing innovative behavior.
Design/methodology/approach: This paper analyzes a two staged incentive contract coordinated with efficiency and innovation in Critical Chain Project Management using learning real options, based on principle-agent theory. The situational experiment is used to analyze the validity of the basic model.
Finding: The two staged incentive scheme is more suitable for employees to create and implement learning real options, which will throw themselves into innovation process efficiently in Critical Chain Project Management. We prove that the combination of tolerance for early failure and reward for long-term success is effective in motivating innovation.
Research limitations/implications: We do not include the individual characteristics of uncertain perception, which might affect the consistency of external validity. The basic model and the experiment design need to improve.
Practical Implications: The project managers should pay closer attention to early innovation behavior and monitoring feedback of competition time in the implementation of Critical Chain Project Management.
Originality/value: The central contribution of this paper is the theoretical and experimental analysis of incentive schemes for innovation in Critical Chain Project Management using the principal-agent theory, to encourage the completion of CCPM methods as well as imitative free-riding on the creative ideas of other members in the team
