带有外部选项的薪酬合同设计与运营决策

发布时间：2018-01-03 21:43

本文关键词：带有外部选项的薪酬合同设计与运营决策　出处：《天津大学》2016年博士论文　论文类型：学位论文

【摘要】：随着社会经济的快速发展,科学技术的不断进步,企业迎来重大发展机遇的同时也面临着诸多挑战,如环境污染加剧,盲目投资加重,研发投入不足,员工压力剧增,人才流失严重等问题亟待解决.本文探讨了员工存在外部选项(企业外部的就业机会)情况下,企业如何设计薪酬合同和制定相关的运营决策,如污染防治决策、跨期投资决策、研发投入决策和员工分配决策等.主要工作包括:研究了带有外部选项的高管薪酬设计与污染防治决策问题,其中高管的污染防治能力(私人信息)影响着外部选项和实施污染防治策略的决定.基于委托代理理论建立了高管薪酬合同与污染防治决策模型,应用最优控制方法分别求解固定与可变外部选项情形下的委托代理模型,获得了最优薪酬合同与污染防治策略,并探讨了外部选项对于薪酬合同和污染防治策略的影响.研究了存在在职搜寻行为下的高管薪酬设计与跨期投资决策问题,其中高管的在职搜寻努力水平影响其外部选项,跨期投资项目收益为高管的私人信息.为防止高管进行在职搜寻并使其努力工作,公司需要制定最优的薪酬合同和跨期投资策略.基于委托代理理论构建了高管薪酬合同与跨期投资决策模型,应用最优控制方法分别求解有无在职搜寻行为的模型,获得了最优薪酬合同和投资策略.研究了非对称信息下高管薪酬设计与企业研发投入问题,其中高管决定研发投入,且研发项目收益为其私人信息.构建了关于薪酬合同与研发投入决策的两期委托代理模型,应用极大值原理求解该模型,获得了最优薪酬合同与研发投入策略,并分别探讨了非对称信息和可变外部选项对最优薪酬激励和研发投入的影响.研究了考虑工作满意度时员工的工作分配问题,构建了多周期劳动力规划模型,其中假设员工为有限理性人,以外部选项为参照点,应用展望理论刻画了员工关于加班时间的工作满意度水平.依据模型特点,设计了基于逼近方法的联合作战算法,并与混合粒子群算法进行比较.数值实验说表明了方法的有效性.
[Abstract]:With the rapid development of social economy and the continuous progress of science and technology, enterprises are facing many challenges, such as environmental pollution, blind investment and insufficient R & D investment. This paper discusses how to design the salary contract and make the relevant operation decisions under the situation of the employees' external options (the employment opportunities outside the enterprise) and other problems such as the sharp increase of employee pressure and the serious brain drain. Such as pollution control decision, intertemporal investment decision, R & D investment decision and employee allocation decision, etc. The main work includes: the executive compensation design and pollution control decision with external options are studied. The ability of executives to prevent and control pollution (private information) affects the decision of external options and the implementation of pollution control strategy. Based on the principal-agent theory, the executive compensation contract and pollution control decision-making model is established. Applying the optimal control method to solve the principal-agent model with fixed and variable external options, the optimal compensation contract and pollution prevention strategy are obtained. The effects of external options on compensation contracts and pollution prevention strategies are also discussed. The executive compensation design and intertemporal investment decisions with on-the-job search behavior are studied. Among them, the level of in-service search efforts of senior executives affects their external options, and the income of intertemporal investment projects is the private information of the executives, to prevent them from conducting on-the-job searches and to make them work hard. The company needs to make the optimal compensation contract and intertemporal investment strategy. Based on the principal-agent theory, this paper constructs the executive compensation contract and intertemporal investment decision-making model. The optimal compensation contract and investment strategy are obtained by applying the optimal control method to solve the model with or without on-the-job search behavior, and the problem of executive compensation design and enterprise R & D investment under asymmetric information is studied. The executives decide the R & D investment, and the R & D project income is its private information. A two-period principal-agent model about salary contract and R & D investment decision is constructed, and the maximum value principle is applied to solve the model. The optimal compensation contract and R & D investment strategy are obtained. The effects of asymmetric information and variable external options on the optimal salary incentive and R & D investment are discussed respectively. The employee is assumed to be a limited rational person with external options as the reference point, and the level of employee job satisfaction about overtime is described by applying the prospect theory, according to the characteristics of the model. A joint combat algorithm based on approximation method is designed and compared with the hybrid particle swarm optimization algorithm.
【学位授予单位】：天津大学
【学位级别】：博士
【学位授予年份】：2016
【分类号】：F272.92

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