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Author Xiaoli Wu ♦ Ruiqing Zhao ♦ Wansheng Tang
Sponsorship IEEE Computational Intelligence Society
Source IEEE Xplore Digital Library
Content type Text
Publisher Institute of Electrical and Electronics Engineers, Inc. (IEEE)
File Format PDF
Copyright Year ©1993
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword Contracts ♦ Incentive schemes ♦ Linear programming ♦ Numerical models ♦ Mathematical model ♦ Medical services ♦ Measurement uncertainty ♦ principal-agent problem ♦ Credibility measure ♦ fuzzy agency model ♦ incentive scheme ♦ incomplete information
Abstract Principal-agent problems exist in all walks of social life, and agency theory is an essential approach to dealing with them under incomplete information. Due to incomplete information, it is necessary for the principal to design an optimal incentive scheme to induce the agent to choose the action which is the best possible for maximizing his own utility. In order to depict the incomplete information, the approach based on probability measure was provided in the literature. However, the Ellsberg paradox indicates that probability measure is not always appropriate to describe the vagueness and ambiguity in practical agency problems. Alternatively, this paper employs a fuzzy variable to characterize incomplete information in the agent's ability and applies a method based on credibility measure to deal with optimal contracting problems. With this in mind, a class of novel fuzzy agency models is developed. Under some particular assumptions, the sufficient and necessary conditions for optimal contracts are proven by the variational method, and the proposed work is supported with some numerical examples that illustrate the validity. Finally, three comparative results are presented to demonstrate the main innovations and the contributions to agency theory made by this work.
Description Author affiliation :: Inst. of Syst. Eng., Tianjin Univ., Tianjin, China
ISSN 10636706
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2015-01-01
Publisher Place U.S.A.
Rights Holder Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Volume Number 23
Issue Number 4
Size (in Bytes) 400.85 kB
Page Count 14
Starting Page 909
Ending Page 922

Source: IEEE Xplore Digital Library