知识网络中基于公平偏好的代理人筛选模型

Jing Chen, Xin Gu, Shaobo Wu
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摘要

本文将代理人筛选模型与F-S不公平厌恶模型相结合,研究了公平偏好对知识网络中代理人能力筛选契约设计的影响。我们认为具有公平偏好的委托人会降低信息租金以提高其效用。如果有效代理人具有公平偏好,委托人会通过增加低效代理人的产出来提高信息租金,但信息租金最终的增减取决于委托人效用函数的陡峭程度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Agents Screening Model Based on Fairness Preference in Knowledge Networks
The article combines agents screening model with F-S unfairness aversion model to investigate the influence of fairness preference on agents’ competence screening contracts design in knowledge networks. We suggest that principal with fairness preference will cut down information rent to increase his utility. If efficient agents possess fairness preference, principal will increase the output of inefficient agents to raise information rent, but the information rent ultimately increases or decreases depending on the steep of principle′s utility function.
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