论实物期权估价模型在公司价值评估中的适用性

本文首先将主要的公司价值评估理论和模型进行了梳理和比较,结合各模型的特点对其适用范围进行了划分。在此基础上分析实物期权估价模型的适用性,认为它是不确定条件下对公司进行投资决策时可以科学准确地反映公司价值的模型。     

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。     

关于世博交通限行问题的讨论

为了量化“限行”前后对上海交通拥堵产生的影响,我们引入车辆平均速度和拥挤度作为衡量指标,使抽象的效果具体化,因此我们建立了交通流模型和拥挤度模型来分别求解这两个值。 通过拟定的极小化出行分布函数,我们得出各路段初始交通流量;其次,根据上层出行分布问题下层随机用户平衡模型结合迭代,从而得到最优化选择后各路段交通流量;然后以上海世博为背景,运用交通生成模型得到各区人们出行数量。根据北京奥运期间实行的“单双号”限行措施,对比世博期间限行前后各区之间的交通量,并依所计算的平均速度与拥挤度估计限行措施所带来的影响。我们分析了上海交通的主要拥挤原因和影响因素,并且对于现行有关政策进行了效果评估。基于主要影响因素,提出了有关政策,并且通过模型的建立和实际应用,分别证明了上述缓解交通拥挤状况的正确性和可行性。     

基于系统动力学的ERP应用效果分析

本文在分析了ERP系统对企业运营所产生的影响,以及各影响因素之间的相互作用和关系的基础上,结合运营管理流程建立了主要影响因素的系统动力学模型。然后以某一生产企业为例,利用模型对其ERP应用的效果进行仿真计算,对相关运营指标的仿真结果进行了分析和说明,并总结了ERP系统是如何体现其对企业运营管理的影响和作用。     

质量成本各要素关系研究及模型建立

文章主要针对质量成本各组成部分间的关系以及质量成本与质量水平间的关系做深入分析研究。文章通过建立系统动力学仿真模型来研究不同质量水平下质量成本各组成部分间的关系;质量成本与质量水平的关系研究则利用灰色系统理论解决历史数据不足够多的情况下质量成本与质量水平间的关系,并通过灰色线性回归组合模型建立质量成本与质量水平间的关系模型。首先,文章分析讨论质量成本各组成部分间的三种关系模型;其次,为更进一步深入讨论不同质量水平下质量成本各组成部分间关系,文章建立质量成本各组成部分间的系统动力学模型;再次,文章采用灰色系统模型GM(1,1)与线性相关模型相组合的组合模型并结合新陈代谢处理方法建立一种更为优化的质量成本与质量水平间的关系模型;最后,文章通过案例研究证明质量成本灰色线性回归组合模型的准确性。     

小团队内部知识共享的绩效评估

本文针对小团队的特点,从知识的获取、应用、传播和可持续发展等四个方面,分析了影响小团队内部知识共享绩效的主要因素,构建了绩效评估的递阶层次结构模型。给出了各评价因素的测度方法,并运用层次分析法确定了各因素的权值。最后给出了一个评价实例,表明该方法具有良好的实用性。     

成都市地铁二号线运营安全评价研究

本文首先在对地铁运营特点、地铁常见事故等分析的基础上,确定了地铁运营中的主要风险因素,构建了地铁运营安全评价指标体系。然后引入云模型理论对评价指标等级进行云化,确定各指标对应的安全等级和评价层各评价对象对应的安全等级。最后以成都市地铁二号线为例进行安全评价案例分析,取得了理想的效果,并根据评价结果制定出针对性的安全控制措施。     

河南省大学生创业环境实证分析

本文主要参考五维度模型建立了河南省大学生创业环境评价体系,我们利用菲尔德法及相关统计分析方法分析了大学生所认为的创业环境各要素的重要程度以及要素现状,并对重要程度和现状进行对比,最终得出河南省创业环境的总体评价     

强制性与自主性治理:法律、公司特征的交互效应

本文采用一个企业家模型揭示了法律环境、公司特征对强制性和自主性治理的影响,并利用公司治理自查报告构建了强制性和自主性治理指数,实证分析了法律、公司特征的影响。结果表明二者会交互的影响公司治理,各分指数的回归证实了法律在公司治理中重要而稳健的作用,但影响各治理机制的因素存在差异,我们认为这主要是由于推动治理的主体不同造成的,强制性治理主要由董事会主导,而自主性治理则由股东实施。     

现代知识管理流派研究

基于已有的研究，归纳了知识管理的五个流派即学习流派、过程流派、技术流派、智力资本流派和战略流派，详细论述了各流派的形成过程、学科基础、代表人物、主要观点、典型模型，以及贡献和不足等，最后简略分析了各流派互补和融合的发展趋势。     

供应链提前期风险空间传递机理与控制策略

针对供应链结构特性,本文分析了供应链提前期风险在链状供应链上的空间传递机理;根据风险因素作用的特点,将提前期风险划分为节点企业自身提前期风险、物流延期风险和传递风险。在此基础上,构建了供应链提前期风险空间传递模型和供应链提前期风险控制机理框架,并提出了关键的控制策略;最后通过算例分析验证了模型的有效性。     

Risk Migration and Scientific Advance: The Case of Flame-Retardant Compounds

It is a common experience that attempts to mitigate a risk lead to new risks, and that risks formerly thought to be of one kind become another kind as technical knowledge evolves. This phenomenon of risk migration suggests that we should take processes over time, rather than specific risks or specific technologies, as a unit of analysis. Several of our existing models of the social management of risks-such as that of social risk amplification-are process models of a kind but are still oriented around the playing out of a particular event or issue. A case study of risk in a group of flame-retardant compounds was used as the basis of a grounded, exploratory analysis of migration processes, the phenomena that influence them, and their consequences. This illustrated how migration naturally occurs from risks that are understood, in which risk bearers have at least some agency, to risks that are not understood and not capable of being influenced by risk bearers. It illustrated how the simultaneous improvement in measuring technology, which detects potential toxins at increasingly small concentrations, combines with intuitive models that ignore concentration to produce conditions likely to generate anxiety. And it illustrated how pressure groups and commercial interests exploit this effect. It also showed how migration makes precautionary action problematic, and how more generally it tends to undermine a society's capacity to cope with risk.     

Taxonomic Analysis of Perceived Risk: Modeling Individual and Group Perceptions Within Homogeneous Hazard Domains

Previous studies of risk perception have typically focused on the mean judgments of a group of people regarding the riskiness (or safety) of a diverse set of hazardous activities, substances, and technologies. This paper reports the results of two studies that take a different path. Study 1 investigated whether models within a single technological domain were similar to previous models based on group means and diverse hazards. Study 2 created a group taxonomy of perceived risk for only one technological domain, railroads, and examined whether the structure of that taxonomy corresponded with taxonomies derived from prior studies of diverse hazards. Results from Study 1 indicated that the importance of various risk characteristics in determining perceived risk differed across individuals and across hazards, but not so much as to invalidate the results of earlier studies based on group means and diverse hazards. In Study 2, the detailed analysis of railroad hazards produced a structure that had both important similarities to, and dissimilarities from, the structure obtained in prior research with diverse hazard domains. The data also indicated that railroad hazards are really quite diverse, with some approaching nuclear reactors in their perceived seriousness. These results suggest that information about the diversity of perceptions within a single domain of hazards could provide valuable input to risk-management decisions.     

Dimensions of Risk Perception for Financial and Health Risks

This study of 29 MBA students compares two models of risk perception for both financial and health risk stimuli. The first, inspired by Luce and Weber's Conjoint Expected Risk (CER) model, uses five dimensions: probability of gain, loss and status quo, and expected benefit and harm. The second, inspired by the Sovic et al. psychometric model, employs seven dimensions: voluntariness, dread, control, knowledge, catastrophic potential, novelty, and equity. The CER-type model provided a better fit for most subjects and stimuli. Adding the psychological risk dimensions from the Slovic et al. model explained only modestly more variance. Relationships between the dimensions of the two models are described and the construction of a hybrid model explored.     

Landslide Risk Models for Decision Making

This contribution presents a quantitative procedure for landslide risk analysis and zoning considering hazard, exposure (or value of elements at risk), and vulnerability. The method provides the means to obtain landslide risk models (expressing expected damage due to landslides on material elements and economic activities in monetary terms, according to different scenarios and periods) useful to identify areas where mitigation efforts will be most cost effective. It allows identifying priority areas for the implementation of actions to reduce vulnerability (elements) or hazard (processes). The procedure proposed can also be used as a preventive tool, through its application to strategic environmental impact analysis (SEIA) of land-use plans. The underlying hypothesis is that reliable predictions about hazard and risk can be made using models based on a detailed analysis of past landslide occurrences in connection with conditioning factors and data on past damage. The results show that the approach proposed and the hypothesis formulated are essentially correct, providing estimates of the order of magnitude of expected losses for a given time period. Uncertainties, strengths, and shortcomings of the procedure and results obtained are discussed and potential lines of research to improve the models are indicated. Finally, comments and suggestions are provided to generalize this type of analysis.     

股票市场流动性风险计量模型研究

本文通过对流动性风险本质属性的探讨,提出了目标流动性的概念,建立了两个新的流动性风险计量模型模型,一是用流动性不足的均值测度流动性风险模型;一是包含流动性不足及其波动性的流动性风险综合测度模型。并以上海证券交易所上市的148只A股为样本进行实证检验,结果表明该模型能够科学计量股票流动性风险。     

An Integrated Physical Dispersion and Behavioral Response Model for Risk Assessment of Radiological Dispersion Device (RDD) Events

A radiological dispersion device (RDD) or "dirty" bomb is a conventional explosive wrapped in radiological material. Terrorists may use an RDD to disperse radioactive material across a populated area, causing casualties and/or economic damage. Nearly all risk assessment models for RDDs make unrealistic assumptions about public behavior in their health assessments, including assumptions that the public would stand outside in a single location indefinitely. In this article, we describe an approach for assessing the risks of RDD events incorporating both physical dispersion and behavioral response variables. The general approach is tested using the City of Pittsburgh, Pennsylvania as a case study. Atmospheric models simulate an RDD attack and its likely fallout, while radiation exposure models assess fatal cancer risk. We model different geographical distributions of the population based on time of day. We evaluate aggregate health impacts for different public responses (i.e., sheltering-in-place, evacuating). We find that current RDD models in use can be improved with the integration of behavioral components. Using the results from the model, we show how risk varies across several behavioral and physical variables. We show that the best policy to recommend to the public depends on many different variables, such as the amount of trauma at ground zero, the capability of emergency responders to get trauma victims to local hospitals quickly and efficiently, how quickly evacuations can take place in the city, and the amount of shielding available for shelterers. Using a parametric analysis, we develop behaviorally realistic risk assessments, we identify variables that can affect an optimal risk reduction policy, and we find that decision making can be improved by evaluating the tradeoff between trauma and cancer fatalities for various RDD scenarios before they occur.     

Ecological Risk Assessment,Prediction, and Assessing Risk Predictions

Ecological risk assessment embodied in an adaptive management framework is becoming the global standard approach for formally assessing and managing the ecological risks of technology and development. Ensuring the continual improvement of ecological risk assessment approaches is partly achieved through the dissemination of not only the types of risk assessment approaches used, but also their efficacy. While there is an increasing body of literature describing the results of general comparisons between alternate risk assessment methods and models, there is a paucity of literature that post hoc assesses the performance of specific predictions based on an assessment of risk and the effectiveness of the particular model used to predict the risk. This is especially the case where risk assessments have been used to grant consent or approval for the construction of major infrastructure projects. While postconstruction environmental monitoring is increasingly commonplace, it is not common for a postconstruction assessment of the accuracy and performance of the ecological risk assessment and underpinning model to be undertaken. Without this “assessment of the assessment,” it is difficult for other practitioners to gain insight into the performance of the approach and models used and therefore, as argued here, this limits the rate of improvement of risk assessment approaches.     

Tutorial: Parallel Computing of Simulation Models for Risk Analysis

Simulation models are widely used in risk analysis to study the effects of uncertainties on outcomes of interest in complex problems. Often, these models are computationally complex and time consuming to run. This latter point may be at odds with time‐sensitive evaluations or may limit the number of parameters that are considered. In this article, we give an introductory tutorial focused on parallelizing simulation code to better leverage modern computing hardware, enabling risk analysts to better utilize simulation‐based methods for quantifying uncertainty in practice. This article is aimed primarily at risk analysts who use simulation methods but do not yet utilize parallelization to decrease the computational burden of these models. The discussion is focused on conceptual aspects of embarrassingly parallel computer code and software considerations. Two complementary examples are shown using the languages MATLAB and R. A brief discussion of hardware considerations is located in the Appendix.     

期望效用视角下的风险对冲效率

与传统文献将风险下降比率作为风险对冲效率指标不同,本文引入期望效用理论来比较最小方差对冲策略、最小在险价值(VaR)对冲策略和最小条件在险价值(CVaR)对冲策略的对冲效率,从而将人们的风险态度同对冲策略选择联系起来,以实现不同风险态度的投资者选择不同风险对冲策略的目的。借用风险中性效用函数、二次效用函数和CARA效用函数,本文严格证明:在这三种对冲策略中,最小方差对冲策略过于保守,最小VaR对冲策略最为激进,风险厌恶程度大的投资者偏好最小方差对冲策略,风险中性投资者和风险厌恶程度小的投资者更偏好最小VaR对冲策略,最小CVaR对冲策略介于二者之间。