关于企业财务管理评价涵义的思考分析

这篇文章主要分析了在管理环节中的企业财务管理活动,以及对其内容与含义的评价与思考分析,并为我们梳理了企业管理评价与企业财务管理评价之间的关系,为以后展开财务管理评价做好准备。     

高校财务风险的系统分析与评价

为了解决目前缺乏规范有效的高校财务风险评价体系问题。构建了高校财务风险模糊系统评价模型。通过采用规范研究与实证分析相结合的方法,将模糊集理论与系统分析思想引入高校财务风险评价中,提出了高校财务风险的定义,分析了其特性和决定因素,构建了其评价原则与评价模型。实例应用证实了该评价体系具有良好的可行性与实用性．为高校财务风险的评价预警提供了新的路径和依据。     

关于企业内部控制评价的分析

内部控制评价是一项极具复杂性的工程,并且与企业内部的治理结构及业务流程有着密不可分的联系,本文首先分析了内部控制评价的意义,进而分析了内部控制评价的制约因素,最后就内部控制评价整合的有效性进行了探讨与研究。     

论我国中小商业银行信用评审与风险控制的模型构建

本文论述了我国中小商业银行在信用评审与风险控制中对企业财务报表的真伪鉴审与分析,对企业财务报表重点项目的分析与审查,对企业经营（偿债）能力的分析、评价与度量以及第一还款来源的评价与度量问题;创新提出了其他关联因素属性分析度量以及保证措施的风控度量模式与授信综合评价模型问题。     

项目可行性研究财务评价探讨

本文分析了项目可行性研究财务评价的内涵与特征,构建了评价指标体系,并具体了探讨了具体如何进行评价,提出了评价中需要注意的事项。     

房地产项目环评中的生态宜居性分析

本文分析了房地产项目环境影响评价现状,阐述了房地产项目环评中进行生态宜居性分析的目的和意义,探讨了生态宜居性分析的方法。通过对自然生态与人文生态两个基本因素的分析,筛选出了相关的评价因子和指标,提出了生态宜居性分析的评价指标体系,并简要介绍了灰色聚类评价法的具体评价步骤。     

地区工业行业经济状况的综合评价与分析

地区工业行业经济效益与效率的综合评价与分析是制定地区工业发展战略的重要依据。本文应用模型聚类方法与ＤＥＡ（数据包络分析）分类法从不同角度综合评价了地区工业行业的经济状况，并给出了１９９１年合肥地区３０个工业行业的具体评价与分析。本文的有关结论得到了应用部门的认可。     

中等职业学校课堂教学评价理论与实践研究

本文通过对中等职业学校课堂教学评价的观察，探讨了课程评价、学生评价、自我评价、督导评价、专家评价与课堂教学的关系。分析了课堂教学评价对课程改革的意义，提出了对有效课堂教学评价的思考。     

员工综合评价管理的问题与建议——以ZWXK多媒体网络有限公司为背景

本研究旨在了解员工综合评价管理相关理论,分析ZWXK评价管理方面的问题并提出改善建议。通过对员工综合评价管理涉及的几个重要理论进行了详细的文献分析,以定性研究的访谈法,将文献理论与访谈结果进行综合分析。选取ZWXK公司作为研究背景,将所文献中分析的评价理论与实际情况相结合,对员工综合评价管理方面存在的问题进行了全面的研究及论述,并给出解决建议。     

供应链风险灰色模糊综合评价研究

本文将灰色关联分析与模糊综合评价法相结合,建立基于灰色关联分析的模糊综合评价模型。通过实例对该模型和算法进行了验证,模型将主观判断与定量分析相结合,充分运用了历史数据,能有效、全面、系统的评价供应链风险。     

Article quality and publication impact via levels of analysis incorporation: An illustration with transformational/charismatic leadership

Calls for the inclusion of levels of analysis in theory building and testing have increased over the last 25 years. Through analysis of 539 published articles we assess the prevalence of incorporation of levels of analysis in theory/hypothesis formulation, measurement, data analysis, and subsequent theory–data alignment (i.e., article quality) within charismatic and transformational leadership research. Additionally, we examine the relationship between incorporation of levels of analysis into research and publication source quality, as reflected by journal impact factors or when not available, estimated journal impact factors. When controlling for the level of analysis within all articles, results revealed that increasing the complexity of the level of analysis (i.e., higher than individual level), increased the likelihood that measurement, analysis and alignment of theory and data would be presented at the appropriate levels of analysis. In contrast, for articles with published impact factors, when controlling for the level of analysis, results revealed that increasing the complexity of the level of analysis (i.e., higher than individual level) decreased the likelihood that measurement, analysis and alignment of theory and data would be presented at the appropriate levels of analysis.     

The quality and use of regulatory analysis in 2008

This article assesses the quality and apparent use of regulatory analysis for economically significant regulations proposed by federal agencies in 2008. A nine-member research team used a six-point (0-5) scale to evaluate regulatory analyses according to criteria drawn from Executive Order 12866 and Office of Management and Budget Circular A-4. Principal findings include: (1) the average quality of regulatory analysis, though not high, is somewhat better than previous regulatory scorecards have shown; (2) quality varies widely; (3) biggest strengths are accessibility and clarity; (4) biggest weaknesses are analysis of the systemic problem and retrospective analysis; (5) budget or "transfer" regulations usually receive low-quality analysis; (6) a minority of the regulations contain evidence that the agency used the analysis in significant decisions; (7) quality of analysis is positively correlated with the apparent use of the analysis in regulatory decisions; and (8) greater diffusion of best practices could significantly improve the overall quality of regulatory analysis.     

A Methodology for Grouping Source Terms for Consequence Calculations in Probabilistic Risk Assessments

The individual plant analyses in the U.S. Nuclear Regulatory Commission's reassessment of the risk from commercial nuclear power plants (NUREG-1150) consist of four parts: systems analysis, accident-progression analysis, source-term analysis, and consequence analysis. Careful definition of the interfaces between these parts is necessary for both information flow and computational efficiency. This paper describes the procedure used to define the interface between the source-term analysis and the consequence analysis. This interface is accomplished by forming groups of source terms with similar properties and then performing one set of MACCS calculations for each group.     

Ethics, Decision Analysis, and Public Risk

In any analysis of a decision problem involving public risks, ethical implications are introduced. In some cases, these ethical implications may be introduced simply because an analysis is being done. Additional ethical implications may be inherently part of the methodology being utilized or introduced into the specific analysis of the decision problem. In this paper, we investigate where and how ethical implications enter when using the methodology of decision analysis to examine problems involving public risks. We conclude that the methodology of decision analysis is sufficiently robust to allow for numerous different ethical viewpoints to be accounted for in any specific analysis. Stated alternatively, decision analyses of public risks can be conducted in a manner consistent with utilitarianism, deontological theories, libertarianism, egalitarianism, and so forth. However, any specific analysis has embedded within it numerous ethical implications. This suggests that the careful ethical scrutiny of analyses involving the methodology of decision analysis should be placed on the specific application and not on the methodology per se or on the fact that an analysis is undertaken.     

AN APPROACH FOR IMPROVED INTERPRETATION OF MULTIVARIATE ANALYSIS *

This paper proposes a method, canonical rotation analysis, which facilitates the substantive interpretation of results in multivariate analysis. Canonical rotation analysis is developed as a model which integrates multivariate least squares approaches and the varimax rotation criterion. The generalized applicability of the model to canonical correlation, multiple discriminant analysis, and multivariate analysis of variance is developed. The advantages and limitations of canonical rotation analysis are discussed and illustrated in the context of an industrial marketing research problem.     

Estimation of Error and Bias in Bayesian Monte Carlo Decision Analysis Using the Bootstrap

Bayesian Monte Carlo (BMC) decision analysis adopts a sampling procedure to estimate likelihoods and distributions of outcomes, and then uses that information to calculate the expected performance of alternative strategies, the value of information, and the value of including uncertainty. These decision analysis outputs are therefore subject to sample error. The standard error of each estimate and its bias, if any, can be estimated by the bootstrap procedure. The bootstrap operates by resampling (with replacement) from the original BMC sample, and redoing the decision analysis. Repeating this procedure yields a distribution of decision analysis outputs. The bootstrap approach to estimating the effect of sample error upon BMC analysis is illustrated with a simple value-of-information calculation along with an analysis of a proposed control structure for Lake Erie. The examples show that the outputs of BMC decision analysis can have high levels of sample error and bias.     

Decision Analysis and Risk Management Decision Making: Issues and Methods

This paper provides an overview of decision analysis and its use in risk management decision making. The paper discusses the distinctive characteristics of decision analysis and compares these characteristics with those of its principal alternative—cost–benefit analysis. The paper also discusses each of the steps in a decision analysis and the strengths and limitations of the method.     

Rethinking Vulnerability Analysis and Governance with Emphasis on a Participatory Approach

This article draws on vulnerability analysis as it emerged as a complement to classical risk analysis, and it aims at exploring its ability for nurturing risk and vulnerability governance actions. An analysis of the literature on vulnerability analysis allows us to formulate a three‐fold critique: first, vulnerability analysis has been treated separately in the natural and the technological hazards fields. This separation prevents vulnerability from unleashing the full range of its potential, as it constrains appraisals into artificial categories and thus already closes down the outcomes of the analysis. Second, vulnerability analysis focused on assessment tools that are mainly quantitative, whereas qualitative appraisal is a key to assessing vulnerability in a comprehensive way and to informing policy making. Third, a systematic literature review of case studies reporting on participatory approaches to vulnerability analysis allows us to argue that participation has been important to address the above, but it remains too closed down in its approach and would benefit from embracing a more open, encompassing perspective. Therefore, we suggest rethinking vulnerability analysis as one part of a dynamic process between opening‐up and closing‐down strategies, in order to support a vulnerability governance framework.     

随机条件下房地产开发的最优时机选择及其可达性问题研究

实物期权框架下的房地产投资相关研究长期忽视了对投资时机可达性问题的研究、忽视了对收益流与成本流相关性问题的探讨.有鉴于此,本文在房地产价格与建安成本二重随机性以及二者具有相关性的条件下,运用期权分析技术建模研究了房地产开发商的最优时机选择问题及最优时机的可达性问题.同时,文章对研究结果作了可达性分析、比较静态分析、数值分析、经济含义分析与政策含义分析,并对结论做了定性的实证检验.     

CONDITIONAL RISK ANALYSIS

This paper introduces conditional risk analysis as a new approach to extend the standard risk analysis method of Hertz. An exercise in profit planning is used to illustrate the special features of conditional risk analysis: total risk measurement, risk decomposition, factor outcome analysis and variable significance analysis. Mathematical expressions are presented for performing the various analyses.