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Uncertainty, Risk, and the Efficiencies of the Principal and the Agent: A Chance Constrained Data Envelopment Analysis Approach

机译:委托人和代理人的不确定性,风险和效率:机会约束数据包络分析方法

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摘要

In a principal-agent relationship, although the principal (e.g., the investor) can control the inputs and decide the motivated payments to the agent (e.g., the top management team), she cannot have the ability to decide how many outputs she can be rewarded. Since the motivated payments the agent gains from the principal are closely related to the uncertain outputs, they also have the characteristic of uncertainty. Furthermore, the attitudes and behaviors of both parties, such as risk attitude of the principal/agent on the uncertainty of outputs/motivated payments, can have significant influence on the efficiencies of two parties and consequently affect the enthusiasm and effort of the agent. To address this issue, chance constrained data envelopment analysis (DEA) approach is proposed. Based on this stochastic approach, the measures of the principal's efficiency, the agent's efficiency, and the agent's effort level are provided. A case study of 16 China listed real estate companies validates our models and shows that the uncertainties of outputs and payments have significant influences on the efficiencies of the principal and the agent and the effort of the agent as well.
机译:在委托人-代理人关系中,尽管委托人(例如,投资者)可以控制投入并决定向代理人(例如,最高管理团队)支付的报酬,但她无法确定自己可以取得多少产出奖励。由于代理人从委托人那里获得的激励性报酬与不确定的产出密切相关,因此它们也具有不确定性的特征。此外,双方的态度和行为,例如委托人/代理人对产出/激励性付款不确定性的风险态度,可能对双方的效率产生重大影响,从而影响代理人的热情和努力。为了解决这个问题,提出了机会约束数据包络分析(DEA)方法。基于这种随机方法,提供了委托人效率,代理效率和代理工作水平的度量。对16家中国上市房地产公司的案例研究验证了我们的模型,并表明产出和付款的不确定性对委托人和代理人的效率以及代理人的工作力有重大影响。

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  • 来源
    《Mathematical Problems in Engineering》 |2018年第14期|8373614.1-8373614.13|共13页
  • 作者单位

    Nanjing Audit Univ, Sch Business, Yushan West Rd 86, Nanjing 211815, Jiangsu, Peoples R China;

    Univ Sci & Technol China, Sch Management, 96 Jinzhai Rd, Hefei 230026, Anhui, Peoples R China;

    Univ Sci & Technol China, Sch Management, 96 Jinzhai Rd, Hefei 230026, Anhui, Peoples R China;

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