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Soft Computing

, Volume 22, Issue 16, pp 5231–5246 | Cite as

The impacts of private risk aversion magnitude and moral hazard in R&D project under uncertain environment

  • Yiping Fu
  • Zhihua Chen
  • Yanfei Lan
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Abstract

The R&D project manager tends to misreport risk aversion magnitude and shirk under uncertain environment for acquiring information rent and risk premium, which brings a significant challenge for the firm when designing compensation contracts. We consider an agency problem where a firm employs a manager who has private information about his risk aversion magnitude and unobservable efforts to implement a R&D project through a menu of incentive contracts. Both the subjective assessments about the risk aversion degree and the project variability are characterized as uncertain variables. Within the framework of uncertainty theory and principal-agent theory, we investigate the impacts of information asymmetry on the optimal compensation contracts and the firm’s profits under four information structures. We demonstrate that, counterintuitive as it sounds, the manager’s optimal contract under full information is the same as that under pure adverse selection. Nevertheless, compared to the case under full information, the firm should distort the commission rate upwards under pure moral hazard and dual asymmetric information. We also show that when the manager’s efforts are observable, hidden information about the risk aversion magnitude has no effect on the firm’s profit. However, when unobservable, private risk aversion degree always brings about information rent and induces a loss for the firm’s profit. Finally, our study provides managerial recommendations on mitigating the adverse impacts caused by asymmetric information.

Keywords

Uncertainty theory Incentive contract New product development Information asymmetry 

Notes

Acknowledgements

This work was supported by the National Natural Science Foundation of China (Grant Nos. 71771166 and 71771165).

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

This article does not contain any studies with human participants or animals performed by any of the authors.

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2017

Authors and Affiliations

  1. 1.College of Management and EconomicsTianjin UniversityTianjinChina
  2. 2.College of Information Science and TechnologyHainan UniversityHaikouChina

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