国家审计机关绩效的模糊综合评估

本文基于平衡计分卡理论构建了国家审计机关绩效评估指标体系,在采用层次分析法确定各指标权重的基础上,运用模糊综合评价的方法,对某国家审计机关的绩效进行了科学的评估,以期为我国国家审计机关绩效评估提供-种思路和方法,从而更好地提高审计机关的管理水平.     

基于BSC的高校教师绩效评估体系设计

本文根据高校教师绩效的特点,将平衡计分卡引入到高校教师绩效评估中,分析了平衡计分卡应用于高校教师绩效评估的可行性,将平衡计分卡中传统的四个维度转换为适合高校教师绩效评估的四个维度,构建基于平衡计分卡的高校教师绩效评估体系,为高校教师绩效评估提供借鉴和参考.     

基于BSC的公共文化服务评估指标体系构建研究——以东莞市厚街镇为例

本文将平衡计分卡的评估理念和技术引入到公共文化服务领域,构建公共文化服务的平衡计分卡框架,综合运用问卷调查、社会统计方法,结合实际,构建了体现新的文化发展观要求,符合新时期公共文化服务事业发展实际的绩效评估指标体系。     

基于平衡计分卡的高校教师绩效评估研究

高校教师绩效评估作为高校人力资源管理的关键,对于促进高校教师的个人发展,保障高校的整体发展等起到了至关重要的作用。但是,目前高校教师绩效评估还存在着很多问题,特别是评估方法不科学的问题正日益凸显,这对高校教师的发展、高校整体目标的实现产生了严重的影响。而于1992年提出的平衡计分卡可以在绩效评估中发挥很好的作用,很多世界500强企业和非营利性组织都已经应用了这一绩效评估工具。因此,本文在回顾了高校教师绩效评估和平衡计分卡相关知识的基础上,探讨了基于平衡计分卡的高校教师绩效评估的必要性,以及如何设计基于平衡计分卡的高校教师绩效评估体系,具有一定的理论价值和现实意义。     

基于平衡计分卡的教师绩效考核

本文以教师绩效考核背景，对现今教师绩效考核中存在的诸多问题进行简要分析，根据这些问题，将平衡计分卡的相关理论框架引入到教师绩效考核当中，用新的视角看待教师绩效考核。针对教师绩效改革的特点，对平衡计分卡原本的个别维度进行修改。使之更加适合教师的绩效考核，从而提出了基于平衡计分卡的教师绩效考核。     

基于平衡计分卡的企业绩效管理研究

随着信息化和全球化的发展,企业为了在国内国际竞争中生存,不得不加强绩效管理在发展战略中的作用。而以往常用的单一的财务评价体系难以满足企业绩效评价的需要,平衡计分卡应用而生,是目前理论与实务界都比较推崇的一种企业业绩评价方法。因此,本文将平衡计分卡应用到企业绩效管理当中,在综述目前国内外学者对此的研究现状的基础上,运用层次分析法确定各个评价指标的权重进而进行实证分析,将理论运用于实践。     

基于BSC的企业绩效评估方法综述

BSC(平衡计分卡)是一种战略管理工具,它把组织的战略和一整套的衡量指标联系起来,从而使企业战略得以有效实施。它改进了传统绩效评估仅限于评价财务指标的不足,用财务指标、客户指标、内部流程指标和学习与成长指标四个方面衡量和评价企业绩效。本文总结了BSC评估方法的不断发展和国内外对于平衡计分卡研究的主要的方向。     

构建基于平衡计分卡理论的政府绩效评估体系

<正>随着我国政府部门改革的深入发展,政府部门绩效管理、绩效评估逐步被人们所认识,各种相关理论也逐步被人们所熟知,平衡计分卡就是其中的一种。平衡计分卡原来是应用在企业的绩效评估体系,现在逐步被人们应用到政府的绩效管理体系中来。本文试就平衡计分卡在政府部门的应用进行分析。     

基于平衡计分卡的绩效预算分析

绩效预算是预算改革的方向,绩效评价体系是绩效预算的基础,文章借鉴平衡计分卡多维度评估组织业绩的作用,提出了以平衡计分卡为载体,构建高校项目绩效预算的思路。     

不确定环境下医生绩效的评价方法

本文首先采用关键绩效指标法,构建了医生绩效评价的指标体系,针对指标存在的不确定性特点,应用证据推理算法,建立了医生绩效评价模型,有效地融合了定量和定性信息,对医生绩效进行了综合评估。结果表明,该方法解决了评价指标不确定性的问题,大大提高了评价的准确性。可得结论,证据推理算法应用于医生绩效评价具有一定的可行性、实用性和推广价值。     

基于证据推理的不确定多属性决策方法

针对基本属性权重的不确定性,以及基本属性与广义属性评价集的不一致性等问题,提出一种基于证据推理的不确定多属性决策方法,将证据推理算法推广到更一般的决策环境中.根据决策矩阵的信息熵客观地获得属性的权系数;而对于基本属性与广义属性评价集不一致的情况,则通过对基本属性分布评价的模糊化及模糊变换,合理地实现到广义分布评价的统一形式;最后应用证据推理算法得到整个方案集的排序.实例结果表明,该方法是可行的、有效的.     

基于证据推理和广义Shapley值的扩展概率语言多属性群决策方法

扩展概率语言词集通过语言变量概率分布的调整能够转化为多种语言信息表示模型,是语言变量、不确定语言信息、扩展犹豫模糊语言词集、分布语言评估信息、概率语言词集等的一般化,具有较强的通用性和实用性,是处理不确定性信息的重要工具。鉴于此,本文针对扩展概率语言环境下的多属性群决策问题,提出基于证据推理和广义Shapley值的多属性群决策方法。首先,提出扩展概率语言词集的定义和相关基础理论。其次,将广义Shapley值和证据推理相结合用于专家信息融合,并将广义Shapley值和TODIM方法相结合用于备选方案排序。再次,提出基于灰色关联法的权重确定模型来处理专家/属性权重部分未知的情况。最后,以绿色供应商选择为例进行分析,通过对比分析验证所提方法的有效性和优越性。     

不完全确定信息的群体语言指派问题的求解方法

针对决策者权重和准则权重为不完全确定信息且评价语言值确定或位于二个标准语言值之间甚至缺失的多准则指派问题,提出了一种求解方法。首先利用证据推理算法计算得到各候选人完成各任务的优劣程度属于各个语言评价等级的信任度,并据此利用二元语义的Δ函数及其函数Δ-1将其集成为群体在所有准则下的综合评价矩阵,然后结合决策者权重和准则权重的不完全确定信息等构建非线性混合整数规则模型,并利用粒子群算法与匈牙利算法联合进行求解。最后实例说明该方法的可行性和有效性。     

Use of Fuzzy Evidential Reasoning in Maritime Security Assessment

Over the last few years, there has been a growing international recognition that the security performance of the maritime industry needs to be reviewed on an urgent basis. A large number of optional maritime security control measures have been proposed through various regulations and publications in the post-9/11 era. There is a strong need for a sound and generic methodology, which is capable of taking into account multiple selection criteria such as the cost effectiveness of the measures based on reasonable security assessment. The use of traditional risk assessment and decision-making approaches to deal with potential terrorism threats in a maritime security area reveals two major challenges. They are lack of capability of analyzing security in situations of high-level uncertainty and lack of capability of processing diverse data in a utility form suitable as input to a risk inference mechanism. To deal with such difficulties, this article proposes a subjective security-based assessment and management framework using fuzzy evidential reasoning (ER) approaches. Consequently, the framework can be used to assemble and process subjective risk assessment information on different aspects of a maritime transport system from multiple experts in a systematic way. Outputs of this model can also provide decisionmakers with a transparent tool to evaluate maritime security policy options for a specific scenario in a cost-effective manner.     

An Evidential Reasoning‐Based CREAM to Human Reliability Analysis in Maritime Accident Process

This article proposes a modified cognitive reliability and error analysis method (CREAM) for estimating the human error probability in the maritime accident process on the basis of an evidential reasoning approach. This modified CREAM is developed to precisely quantify the linguistic variables of the common performance conditions and to overcome the problem of ignoring the uncertainty caused by incomplete information in the existing CREAM models. Moreover, this article views maritime accident development from the sequential perspective, where a scenario‐ and barrier‐based framework is proposed to describe the maritime accident process. This evidential reasoning‐based CREAM approach together with the proposed accident development framework are applied to human reliability analysis of a ship capsizing accident. It will facilitate subjective human reliability analysis in different engineering systems where uncertainty exists in practice.     

Integrating the Data Envelopment Analysis and the Balanced Scorecard approaches for enhanced performance assessment

This article presents the development of a conceptual framework which aims to assess Decision Making Units (DMUs) from multiple perspectives. The proposed conceptual framework combines the Balanced Scorecard (BSC) method with the non-parametric technique known as Data Envelopment Analysis (DEA) by using various interconnected models which try to encapsulate four perspectives of performance (financial, customers, internal processes, learning and growth).The practical relevance of the conceptual model has been tested by using it to assess the performance of DMUs in a multinational company which operates in two business areas. Various models were developed with the collaboration of the directors of the company in order to conceive an appropriate and consensual framework, which may provide useful information for the company. The application of the conceptual framework provides structured information regarding the performance of each DMU (from multiple perspectives) and ways to improve it. By integrating the BSC and the DEA approaches this research helps to identify where there is room for improving organisational performance and points out opportunities for reciprocal learning between DMUs. In doing so, this article provides a set of recommendations relating to the successful application of DEA and its integration with the BSC, in order to promote a continuous learning process and to bring about improvements in performance.     

基于证据推理和前景理论的交叉效率排序方法研究

针对由交叉效率评价策略和交叉效率集结方法的多样性而造成评价结果不一致的问题,提出利用证据推理方法和前景理论,综合各个交叉效率评价策略的评价结果,实现对决策单元的统一评价。首先,分别将选用的交叉效率评价策略以及各个评价策略中的他评效率设置成一级指标和二级指标,依据算数平均和前景理论分别确定一、二级指标的权重;其次,依据他评效率确定二级指标置信度,利用证据推理方法将各个交叉效率评价策略的他评效率综合转换成决策单元被评价为有效的置信度。决策者可通过比较决策单元被识别为有效的置信度的大小来判断决策单元交叉效率的大小,进而实现对决策单元的排序;最后,通过案例验证和说明本文提出方法的有效性和实用性。     

An Integrated Risk Assessment Model of Township‐Scaled Land Subsidence Based on an Evidential Reasoning Algorithm and Fuzzy Set Theory

Land subsidence risk assessment (LSRA) is a multi‐attribute decision analysis (MADA) problem and is often characterized by both quantitative and qualitative attributes with various types of uncertainty. Therefore, the problem needs to be modeled and analyzed using methods that can handle uncertainty. In this article, we propose an integrated assessment model based on the evidential reasoning (ER) algorithm and fuzzy set theory. The assessment model is structured as a hierarchical framework that regards land subsidence risk as a composite of two key factors: hazard and vulnerability. These factors can be described by a set of basic indicators defined by assessment grades with attributes for transforming both numerical data and subjective judgments into a belief structure. The factor‐level attributes of hazard and vulnerability are combined using the ER algorithm, which is based on the information from a belief structure calculated by the Dempster‐Shafer (D‐S) theory, and a distributed fuzzy belief structure calculated by fuzzy set theory. The results from the combined algorithms yield distributed assessment grade matrices. The application of the model to the Xixi‐Chengnan area, China, illustrates its usefulness and validity for LSRA. The model utilizes a combination of all types of evidence, including all assessment information—quantitative or qualitative, complete or incomplete, and precise or imprecise—to provide assessment grades that define risk assessment on the basis of hazard and vulnerability. The results will enable risk managers to apply different risk prevention measures and mitigation planning based on the calculated risk states.     

Marine and Offshore Safety Assessment by Incorporative Risk Modeling in a Fuzzy-Bayesian Network of an Induced Mass Assignment Paradigm

The incorporation of the human element into a probabilistic risk-based model is one that requires a possibilistic integration of appropriate techniques and/or that of vital inputs of linguistic nature. While fuzzy logic is an excellent tool for such integration, it tends not to cross its boundaries of possibility theory, except via an evidential reasoning supposition. Therefore, a fuzzy-Bayesian network (FBN) is proposed to enable a bridge to be made into a probabilistic setting of the domain. This bridge is formalized by way of the mass assignment theory. A framework is also proposed for its use in maritime safety assessment. Its implementation has been demonstrated in a maritime human performance case study that utilizes performance-shaping factors as the input variables of this groundbreaking FBN risk model.     

科学基金项目立项评估:综合评价信息可靠性的多指标证据推理规则研究

公正合理的科研项目立项评估与选择是国家自然科学基金管理活动的关键环节。综合考虑科研项目的评估指标体系和选择流程,提出了利用历史评估准确性度量专家提供信息可靠性的方法,进而提出了一种系统性的基于证据推理规则的科学基金项目评估决策模型。该模型使用证据推理合成规则对多专家多指标评估信息进行集结。在集结过程中：充分考虑评估指标的权重以及评估等级的多样性;鉴于参与项目评估的专家具有不同的知识背景和经验,提出利用历史评估结果的准确性衡量专家提供的评价信息可靠性的方法;应用信度分布表征项目的整体评价结果,包含了更丰富的信息。国家自然科学基金项目评估的实例分析证明了该评估决策模型的有效性。