经理长期与短期报酬优化组合激励的探讨

论文对经理长期报酬和短期报酬的优化组合激励问题进行了探讨。通过分析建立了组合激励的两阶段模型,求解模型得到了最优报酬组合。结合构成最优报酬组合各参数的含义,探讨了它们对最优报酬组合的影响。最后给出了主要的结论。     

经理人股票期权无效性的动态非合作博弈分析

大量学者从不同角度对经理人股票期权的有效性提出了质疑.本文基于现有理论和经验研究成果,分析股票期权收益的重要因素--继任经理人员的努力类型,对股票期权激励效果的影响,构建了经理人员股票期权激励合约的新框架,并建立经理人员之间的非合作动态博弈模型,有效解释了股票期权激励无效的内在原因.     

关于经理股权激励机制的探讨

对经理股权报酬和非股权报酬的优化组合激励问题进行了探讨。通过分析建立了组合激励的两阶段博弈模型,通过博弈分析和优化分析得到了经理最优薪资报酬组合和最优股权配置比例。结合构成股权配置比例的各参数的含义,探讨了它们的变化对最优股权配置比例的影响,指出了经理股权配置比例设计工作中应该注意的一些问题。     

不公平厌恶偏好、股权结构与管理层薪酬激励效果--一个实验分析

传统经济学理论建立在自利的人性假设之上,但事实上在许多情形下,公平意识会影响人的行为。以薪酬激励合约为中介,构建不同产权基础的公司与不同经理人员特质的内生配置模型,把不公平厌恶偏好的异质性纳入到配置模型中,以310位企业经理人员作为实验对象,通过一组独裁者博弈实验和两组策略博弈实验共9014次分配决策,检验被试几种主要类型的社会偏好,从中甄别出经理人员不公平厌恶偏好的相对强度,结合调查问卷的数据证实经理人员不公平厌恶偏好、努力水平、公司股权结构和公司绩效之间由薪酬激励契约联结起来的内生配置关系。研究结果表明,具有不同公平性偏好的行为人对于等额的薪酬不公平的反应有所不同,从而影响合约的履行效果,控制权收益对薪酬的浮动部分具有替代效应,产生反向的激励效应,替代程度越大,反向激励效果越大。     

业绩的隐性激励与经理报酬契约的改进

本文认为经营业绩对经理有隐性激励作用是完全有可能的,将业绩的隐性激励作用引入经理的效用函数后建立了对经理的最优报酬激励模型,并通过对模型进行求解得到改进的最优报酬契约。通过分析给出了主要结论。     

经理激励问题的若干扩展研究

本文在建立包括经理努力程度、能力状态和环境变量的经理业绩与激励合同线性模型的基础上,进行两个方面的扩展,通过引入观测变量和假设努力程度与能力状况对业绩的贡献可分离,得出了计算结果并进行了分析.     

经理声誉考虑、任务关联性和长期报酬激励的效果研究

为研究如何激励经理努力提高企业未来业绩,假设经理承担着两项任务:声誉激励其提高企业当前业绩,报酬激励其提高未来业绩;在多任务委托代理模型框架下,本文研究了声誉和长期报酬对经理提高未来业绩的激励效果.本文把企业业绩分为当期业绩和长期(即未来)业绩,并假设委托人目标是长期企业业绩最大化,而不是当期业绩最大化.同时本文对经理努力成本函数的假设有重大改进:给出了经理长期和短期努力的具体的成本函数形式,考虑了两种任务即努力间的关联性情况,假设长期努力和当期努力有不同的成本系数.目前相关模型的成本函数最多只能满足以上三个条件中的前两个.因此,运用本文多任务委托代理模型分析得出的结论更明确、直观,并且更符合实际.本文发现,经理不同努力的成本、两项任务之间的关联性对经理的努力行为选择有重要的影响,要激励经理提高企业长期业绩,应该减少经理长期努力的成本或者弱化当期激励.     

完全信息下的激励-努力动态博弈分析

本文运用博弈论的理论,建立了企业线性业绩模型和线性激励模型前提下的企业股东与经理激励-努力博弈分析模型,分析了完全信息条件下的股东与经理激励-努力动态博弈均衡,对求解获得企业经理努力变量、企业股东激励变量和经理业绩分享系数量变的取值、变化范围及其相互关系进行了范围广泛的分析,力图为企业激励机制的设计与研究提供借鉴。     

管理者激励组合的理论探讨

本文主要对管理者实施非物质激励和激励组合进行的研究.首先,论文分析了非物质激励的作用,并提出了计量非物质激励的模型.随后,管理者组合激励模型被建立.在进行了静态分析的基础上,论文对组合激励模型中有关参数的变化含义进行了深入分析,说明了组合激励的意义在于在一定物质条件和激励成本约束下,管理者的效用可以达到最优化.文章最后给出了主要结论.     

激励在企业高层经理人员中的运用

人才竞争是现代企业关注的焦点,企业高层经理人员是现代企业的核心人物,他的决定性作用意味着降低经营成员的激励而导致的效率损失高于降低生产成员激励而导致的效率损失,由于企业高层经理人员活动的重要性和不易监督性,对其的激励就成为一个非常重要并棘手的问题。这表明应当采取一些有效措施来对企业高层经理人员进行激励。     

Acquisition and Disclosure of Operational Information*

We study a firm's strategy for acquisition and disclosure of operational information by establishing linkages among information quality, managerial self‐interest, and production planning. We develop a multistage model in which a manager of a publicly traded firm first receives private information about the product demand and then uses it to make production and disclosure decisions. We consider two prevalent disclosure models employed in the accounting literature: all‐or‐nothing and cheap‐talk models. In the all‐or‐nothing model, it is assumed that any disclosure must be truthful, but the manager can strategically withhold information. We show that the manager commits to acquire the value‐added operational information if (i) the managerial self‐interest in the interim share price is low or (ii) the managerial self‐interest in the interim share price is high, but the fixed disclosure cost is either sufficiently low or sufficiently high. We demonstrate that the firm is better off if the production level is observable to the financial market because multidimensional signaling reduces costs. In the cheap‐talk model, we assume that the manager's disclosure may not be truthful. We show that the manager's incentive to acquire value‐added operational information increases along with the penalty cost for misleading investors. Therefore, a high penalty cost for misleading investors can encourage the manager to obtain more precise information, which in turn improves the firm's cash flow.     

Combining Judgmental and Statistical Forecasts: An Application to Earnings Forecasts

This study investigated the accuracy of combinations of statistical and judgmental forecasts of annual accounting earnings. Combined forecasts were generated as equally weighted (i.e., simple averages) and unequally weighted combinations of individual forecasts from time-series models of quarterly and annual earnings (statistical forecasts) and security analysts' forecasts of quarterly and annual earnings (judgmental forecasts). The effect of the number of individual forecasts combined on the accuracy of the combined forecasts was also examined. The empirical results indicated that, on the average, combined forecasts were more accurate than individual forecasts. The results also indicated that although analysts' forecasts are based on a wider information set, the accuracy of their forecasts could be improved by combining them with forecasts generated from statistical models. Even if the best individual forecast could be identified in advance, gains in accuracy could be achieved by using combinations of two other forecasting methods. Several of the combined forecasts were superior to the most accurate individual forecast. Forecasts combined by using unequal weights derived from a regression model proved more accurate than equally weighted combinations. Forecasting accuracy improved and the variability of accuracy across different combinations decreased as the number of forecasts in the combination increased.     

Corporate Managers' Reactions to Assertive Social Skills Exhibited by Males and Females

While a number of investigators have suggested that assertiveness is an important interpersonal skill for both males and females in work-related settings, few studies have empirically evaluated how corporate managers react to assertiveness exhibited by others. The current study examined whether managers react differently to identical assertive responses made by females versus by males, and also compared manager reactions to several different types of verbal content in assertive responses. The procedure consisted of presenting managers with taped vignettes that showed either a male or female model handling several work-related conflicts assertively. The portrayed models were either directly assertive, assertive but moderating their assertion with an empathic comment to the antagonist in the situation, or assertive but tempering the response with a self-effacing comment. Based on interpersonal evaluation ratings completed later by the managers, self-effacing assertive models of both sexes were rated unfavorably relative to either directly assertive or empathic-assertive models. Empathic comments preceding an assertive response resulted in more favorable manager reactions on several criteria. Finally, on almost all measures, assertive behavior exhibited by females was evaluated as positively as the same behavior exhibited by males. Implications for assertive training of males and females in the business setting are considered.     

On the Use of Buy Up as a Model of Customer Choice in Revenue Management

We consider settings in which a revenue manager controls bookings over a sequence of flights. The revenue manager uses a buy‐up model to select booking limits and updates estimates of the model parameters as data are accumulated. The buy‐up model we consider is based upon a simple model of customer choice, wherein each low‐fare customer who is not able to purchase a low‐fare ticket will, with a fixed probability, “buy up” to the high fare, independent of everything else. We analyze the evolution of the parameter estimates (e.g., the buy‐up probability) and chosen booking limits in situations where the buy‐up model is misspecified, that is, in situations where there is no setting of its parameters for which its objective function gives an accurate representation of expected revenue as a function of the booking limit. The analysis is motivated by the common situation in which a revenue manager does not know precisely how customers behave but nevertheless uses a parametric model to make decisions. Under some assumptions, we prove that the booking limits and parameter estimates converge and we compare the actual expected revenue at the limiting values with that associated with the booking limits that would be chosen if the revenue manager knew the actual behavior of customers. The analysis shows that the buy‐up model often works reasonably well even when it is misspecified, and also reveals the importance of understanding how parameter estimates of misspecified models vary as functions of decisions.     

The Impact of Imperfect Processes on Production Run Times

This paper investigates the interaction between the economics of production and imperfections in the production process. Specifically, this paper is the first to devise a model in an attempt to provide managers with guidelines to choose the appropriate production run times to buffer against both the production of defective items and stoppages occurring due to machine breakdowns. In addition to providing several structural properties of the model, we show that a manager will always incur a cost penalty when (s)he uses the results of two oft‐cited models‐the EMQ (Economic Order/Manufacturing Quantity) and the NR‐E (No‐Resumption, Exponential machine breakdown)‐to determine production run times.     

Improving the accuracy and operational predictability of project cost forecasts: an adaptive combination approach

Conducting an early warning forecast to detect potential cost overrun is essential for timely and effective decision-making in project control. This paper presents a forecast combination model that adaptively identifies the best forecast and optimises various combinations of commonly used project cost forecasting models. To do so, a forecast error simulator is formulated to visualise and quantify likely error profiles of forecast models and their combinations. The adaptive cost combination (ACC) model was applied to a pilot project for numerical illustration as well as to real world projects for practical implementation. The results provide three valuable insights into more effective project control and forecasting. First, the best forecasting model may change in individual projects according to the project progress and the management priority (i.e. accuracy, outperformance or large errors). Second, adaptive combination of simple, index-based forecasts tends to improve forecast accuracy, while mitigating the risk of large errors. Third, a post-mortem analysis of seven real projects indicated that the simple average of two most commonly used cost forecasts can be 31.2% more accurate, on average, than the most accurate alternative forecasts.     

A Systematic Approach to Determining the Identifiability of Multistage Carcinogenesis Models

Multistage clonal expansion (MSCE) models of carcinogenesis are continuous‐time Markov process models often used to relate cancer incidence to biological mechanism. Identifiability analysis determines what model parameter combinations can, theoretically, be estimated from given data. We use a systematic approach, based on differential algebra methods traditionally used for deterministic ordinary differential equation (ODE) models, to determine identifiable combinations for a generalized subclass of MSCE models with any number of preinitation stages and one clonal expansion. Additionally, we determine the identifiable combinations of the generalized MSCE model with up to four clonal expansion stages, and conjecture the results for any number of clonal expansion stages. The results improve upon previous work in a number of ways and provide a framework to find the identifiable combinations for further variations on the MSCE models. Finally, our approach, which takes advantage of the Kolmogorov backward equations for the probability generating functions of the Markov process, demonstrates that identifiability methods used in engineering and mathematics for systems of ODEs can be applied to continuous‐time Markov processes.     

Predictive Modeling and Categorizing Likelihoods of Quarantine Pest Introduction of Imported Propagative Commodities from Different Countries

The present study investigates U.S. Department of Agriculture inspection records in the Agricultural Quarantine Activity System database to estimate the probability of quarantine pests on propagative plant materials imported from various countries of origin and to develop a methodology ranking the risk of country–commodity combinations based on quarantine pest interceptions. Data collected from October 2014 to January 2016 were used for developing predictive models and validation study. A generalized linear model with Bayesian inference and a generalized linear mixed effects model were used to compare the interception rates of quarantine pests on different country–commodity combinations. Prediction ability of generalized linear mixed effects models was greater than that of generalized linear models. The estimated pest interception probability and confidence interval for each country–commodity combination was categorized into one of four compliance levels: “High,” “Medium,” “Low,” and “Poor/Unacceptable,” Using K‐means clustering analysis. This study presents risk‐based categorization for each country–commodity combination based on the probability of quarantine pest interceptions and the uncertainty in that assessment.     

基金管理者报酬的线性模型研究与实证分析

探讨了四种跟踪组合回报率与目标回报率间偏差的线性模型 ,线性偏差比传统的二次型偏差更能准确描述投资者的风险态度 ,用线性规划给出了明确的优化方案 ,并对上海证券 A股各分类资产组合作出了实证分析和比较 ,得出为达不同的投资目标投资者确定投资组合及基金管理者报酬的各种优化模型 .