Title | ||
---|---|---|
Optimal revenue-sharing contract based on forecasting effort for uncertain agency problem. |
Abstract | ||
---|---|---|
This paper discusses an optimal contracting problem between a principal and an agent by establishing an uncertain agency model. Compared with the existing work, this research focuses on the risk cost caused by the wrong investment in a task based on an inaccurate assessment about the potential output. To avoid it, the principal authorizes the professional agent to make a more accurate assessment about the output in the light of his professional knowledge and experience, and then to show the principal the optimal amount invested in the task. Meanwhile, as an incentive for the agent to pay great forecasting effort to make the more accurate assessment about the output, the principal provides the agent with a revenue-sharing contract including a sharing ratio for him. On this view, this paper proposes the optimal revenue-sharing contract that provides guidance for the two participators to make their respective optimal decisions. Furthermore, the proposed work is supported with the numerical results by analyzing the evolutions of the optimal contract under various influencing factors. |
Year | DOI | Venue |
---|---|---|
2014 | 10.1007/s13042-014-0243-3 | Int. J. Machine Learning & Cybernetics |
Keywords | Field | DocType |
Agency theory, Uncertainty theory, Revenue-sharing contract, Forecasting effort | Actuarial science,Potential output,Revenue sharing,Incentive,Computer science,Operations research,Principal–agent problem,Professional knowledge,Uncertainty theory | Journal |
Volume | Issue | ISSN |
5 | 6 | 1868-808X |
Citations | PageRank | References |
4 | 0.42 | 15 |
Authors | ||
3 |
Name | Order | Citations | PageRank |
---|---|---|---|
Xiaoli Wu | 1 | 4 | 0.42 |
Yanfei Lan | 2 | 218 | 15.92 |
Haitao Liu | 3 | 11 | 1.56 |