并联决策单元的动态DEA效率评价研究

具有并联决策单元内部结构的系统是一类具有代表性的复杂生产系统,其内部结构已不再是传统观念的黑箱,而是由多个并联(平行)的生产单位组成.在已有并联决策单元DEA效率评价方法的基础上加入时间维度,增加规划问题的约束条件,推演出该种复杂系统的动态DEA效率评价指标,并以中国14家商业银行的数据进行实证.研究结果表明,2005年至2008年没有一家银行的动态效率指数为0,这说明中国银行系统的生产效率并没有达到最优;中国商业银行的地区效率基本遵循沿海地区-中部地区-西部地区依次递减的态势,此规律在中国国有银行中的体现更为明显;影响银行效率改进的主要原因是各银行本身的差异,而不是不同经济区域之间的环境差别.     

基于理想决策单元参照求解策略的DEA交叉效率评价模型

在已有关于DEA交叉效率评价模型中,激进型模型和仁慈型模型会因评价结果不一致而导致实际应用中难以对它们予以抉择的难题;中立型模型虽在形式上规避了前述问题,但其本身存在着理论偏差。针对上述问题,基于TOPSIS的理想点构造方法,提出了一种关于DEA交叉效率评价的新模型,即基于理想决策单元参照求解策略的DEA交叉效率评价模型。该模型不仅具有理论的严谨性,可以规避激进型模型与仁慈型模型之间的选择难题,而且相对于它们而言能够更好地坚持DEA最有利于被评价决策单元的基本思想。数值模拟分析表明新模型具有解决实际问题的较好适用性。     

基于可变权重的DEA效率评价模型

传统DEA模型将投入、产出权重视为固定变量。为了更合理地对决策单元的效率进行评价,本文研究了如何将有关投入、产出变量的权重的更多信息融入效率评价模型,提出了可变权重的概念,给出了一种基于可变权重的DEA效率评价模型。本文模型是CCR模型的推广。在有关权重信息可得的前提下,本文模型较之CCR模型中效率评价上更为合理。但是,如何准确度量投入、产出权重并将其函数化,是本文方法应用的难点。一个算例分析演示了本文模型。     

并联结构决策单元的DEA效率评价研究

对复杂生产系统进行效率评价,是改善其运作性能的重要工具.并联结构生产系统是一类有代表性的复杂生产系统,现有研究已经提出了若干针对并联结构生产系统的效率评价问题.然而,现有研究均未考察并联生产系统的前沿生产能力.本文分析了并联生产系统的前沿生产能力,提出了评价并联生产系统的乘数模型和包络模型,证明了这两个模型与有关文献的等价性.与传统CCR模型相比较,本文模型具有更强的鉴别能力,可更大程度挖掘系统整体性能改善的潜力.最后,一个农业评价的实证研究验证了有关结论.     

决策单元交叉效率的自适应群评价方法

传统交叉效率评价方法因决策单元偏好权重不唯一而难以操作,因交叉效率有效性分值平均化集结而难以被接受。目前的学者通常围绕决策单元指标权重的确定性分配方法、交叉效率有效性分值的去平均化集结等分别开展研究。本文将交叉效率评价方法中自评互评相结合的评价模式看作群决策过程,即每个决策单元既是一个被评对象,又是一个决策"专家",提出了一种决策单元交叉效率的自适应群评价方法,将决策单元偏好权重的确定和交叉效率有效性分值的去平均化集结作为同一个决策过程,根据每个决策单元的评价结果与群体评价结果的接近程度,同步迭代调整决策单元的"专家"权重和决策单元自评产生的、并提供给其他被评价决策单元的一组确定的偏好指标权重。实验验证与实例运用分析表明,该方法收敛效果良好,能得到客观稳定的决策单元交叉效率有效性分值及排序。     

综合模型C2WY中增减决策单元与DEA有效性

本文针对最一般的综合 DEA 模型 C²WY,讨论了当增加(或减少)一个或多个决策单元时,DEA 有效决策单元集合的变化。这里,我们充分利用在研究没有增加(或减少)决策单元之前,评价原有决策单元的有效性时得到的信息,给出了 DEA 有效性变化的一些充分条件、必要条件,以及决策单元的 DEA 有效性没有变化的充分必要条件。     

Max-min DEA模型及效率讨价还价均衡解

建立一类新的DEA模型,即Max-min DEA模型.该模型通过最大化最小效率单元的效率,结合了自评与互评的思路,在一定程度上克服了仅仅采用自评思想的经典DEA模型的缺陷.文中Max-min均衡模型问题在于保护“弱小”单元的同时,有可能损害其它单元的效率.为克服该问题,文章通过Nash讨价还价模型求解Max-min均衡模型与CCR模型的讨价均衡解.最后用算例进行了演示计算.     

两阶段生产系统的DEA效率评价模型

数据包络分析(DEA)作为一种数学规划方法,已经被广泛用来评价一个决策单元相对于其它决策单元的效率。经典的DEA模型把决策单元看作一个“黑箱”,对决策单元的内部运行机制不作深入的研究。本文以一个两阶段生产系统为例,从生产系统的内部过程出发,提出一个基于DEA的模型以合理评估该决策单元的相对效率。本文提出的模型实质上是一类特殊的网络DEA模型,其评价原理有别于已有的研究成果,但确实有助于管理者确定生产过程(如供应链)的非有效来源及其效率改进方向。     

只有输出的广义样本区间DEA模型

在应用多个绩效指标综合评价决策单元有效性时，决策者常常把这些决策单元与另外预先指定的标准（样本单元）进行比较。由于客观事物的复杂性和不确定性导致样本单元和决策单元的指标信息有时必须用区间数的形式给出。针对区间数指标信息的综合评价问题，本文通过分解的方法讨论样本单元和决策单元指标信息为区间数时用广义DEA模型评价决策单元有效性的方法，并相应地构建了只有输出的广义区间DEA模型。同时，对模型的含义、求解以及性质等进行了分析。之后，探讨了该方法在决策单元有效性分类和排序中的应用。最后，通过实例表明该方法的可行性和有效性。     

基于DEA的商业银行效率实证研究

使用混合数据,采用数据包络分析的基本模型及其各种改进模型,对我国 12家商业银行 2001年和2002年的效率进行分析,计算了各商业银行的效率值以及广义效率值;提出了投入-产出导向的基于可变规模收益的超有效数据包络分析模型,并使用该模型计算了各家银行的广义纯技术效率值,从而实现了对各家银行按总效率和纯技术效率进行完全排序,揭示出了各家银行的相对竞争优势;计算了各家银行的规模效率,并分析了其规模报酬状况;对各家银行的效率、纯技术效率状况做了两年的对比分析.     

基于DEA的新证券上市定价基准与投资价值研究

本文针对新证券上市定价存在的问题,提出了基于DEA的新证券上市价值实现程度评价和基准价格评估模型及相应的研判准则,并对我国基金市场进行了实证检验,结果表明这一方法是可行的。     

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.     

On the need for reform of the Portuguese judicial system – Does Data Envelopment Analysis assessment support it?

The Portuguese judicial system has attracted considerable criticism in recent years and demands for reforms have gained prominence. By using the Data Envelopment Analysis technique and focusing on the performance of 223 Portuguese first instance courts during the period of 2007–2011, this research has found evidence that supports some of this criticism and justifies the calls for reforms, better performance and accountability of the judicial system. In particular, our results found a sector with considerable scope for improvement with less than 16% of the 223 courts analysed making an efficient use of their resources in each year and with only one third of the courts being considered efficient in at least one of the five years assessed. Whilst the results suggest that improvement can be achieved with better case management, scale factors also seem to play an important role in explaining inefficiency, with most of the inefficient courts being smaller than optimal and with smaller courts being, on average, less efficient than larger ones. The existence of a statistically significant relationship between courts׳ efficiency and size was confirmed by the Mann–Whitney test. These results indicate considerable scope for improvement and that some of the planned reforms are timely and seem well targeted. However, the results also suggest that efficiency increases matching peers׳ best practices are not enough to sustainably reduce the prevailing judicial backlog and length of court proceedings in a considerable number of courts. Major changes in the capacity and/or functioning of the Portuguese judicial system might also be required.     

Evaluating productive performance: A new approach based on the product-mix problem consistent with Data Envelopment Analysis

We propose a new approach to estimate technical coefficients from a set of Decision Making Units (DMUs) under the assumption that their production plans are set by process engineers through Linear Programming (LP) techniques. The idea behind this approach is that most manufacturing and agricultural firms routinely resort to LP-based modeling in their decision making processes in order to plan output production and, therefore, this particularity should be taken into account when estimating their technical efficiency. A usual model of LP for these sectors is the so-called product-mix problem, which we relate to a standard Data Envelopment Analysis (DEA) model in terms of the Directional Distance Function. In this paper, we finally show how to estimate the technical coefficients of a sample of Andalusian farms in Spain and how this information can be seen as a complement to the usual by-products associated with estimating technical efficiency by DEA.     

The determination of the least distance to the strongly efficient frontier in Data Envelopment Analysis oriented models: Modelling and computational aspects

Determining the least distance to the efficient frontier for estimating technical inefficiency, with the consequent determination of closest targets, has been one of the relevant issues in recent Data Envelopment Analysis literature. This new paradigm contrasts with traditional approaches, which yield furthest targets. In this respect, some techniques have been proposed in order to implement the new paradigm. A group of these techniques is based on identifying all the efficient faces of the polyhedral production possibility set and, therefore, is associated with the resolution of a NP-hard problem. In contrast, a second group proposes different models and particular algorithms to solve the problem avoiding the explicit identification of all these faces. These techniques have been applied more or less successfully. Nonetheless, the new paradigm is still unsatisfactory and incomplete to a certain extent. One of these challenges is that related to measuring technical inefficiency in the context of oriented models, i.e., models that aim at changing inputs or outputs but not both. In this paper, we show that existing specific techniques for determining the least distance without identifying explicitly the frontier structure for graph measures, which change inputs and outputs at the same time, do not work for oriented models. Consequently, a new methodology for satisfactorily implementing these situations is proposed. Finally, the new approach is empirically checked by using a recent PISA database consisting of 902 schools.     

资源约束型两阶段生产系统的DEA效率评价模型

经典的数据包络分析(DEA)模型将决策单元看作"黑箱",忽视决策单元的内部过程,必然会高估决策单元的效率。本文研究了一种资源约束型两阶段生产系统的DEA效率评价方法,针对此类生产过程的内部过程,研究其内部运行机制对整体效率的影响。本文提出的模型实质上是一类特殊的网络DEA模型,其评价原理有别于已有的研究成果,但更有助于管理者确定生产过程的非有效来源及其效率改进方向。实例证实本文方法的合理性。     

对W-B乘子置信域约束构造方法的改进及模型

Wong和Beasley针对数据包络分析(DEA)给出的乘子约束方法(W-B方法)常常会导致相应的模型没有可行解问题。指出了该问题出现的根源在于W-B方法在使用权重重要性概念时存在着逻辑不一致,并提出了一种构造乘子置信域(AR)约束的改进方法及相应的DEA/AR模型。改进方法及模型具有能够克服W-B方法所常常出现的某些乘子置信约束之间相互矛盾问题等三方面优点。经实例应用,验证了所提出的改进方法及相应的DEA/AR模型是切实可行的。     

A DEA Framework to Assess the Efficiency of the Software Requirements Capture and Analysis Process*

In this paper a theoretical framework to assess the efficiency of the Requirements Capture and Analysis (RCA) process in software development is introduced. Although it is widely recognized that successful implementation of the first stages of the software development process is critical for the overall development process, RCA efficiency assessments have not been given much attention. The presented theoretical framework to assess RCA efficiency follows a production approach to model the early stages of a software project. An approach based on Data Envelopment Analysis that utilizes the proposed framework to isolate the effects of exogenous factors, such as the environment or the type of project, on the project's RCA efficiency is also presented. Finally, the applicability of the methodology through an exploratory empirical study is demonstrated, and managerial implications are discussed.     

Exploring the efficiency of Mexican universities: Integrating Data Envelopment Analysis and Multidimensional Scaling

National policy initiatives require the expenditure of large amounts of resources over several years. It is common for these initiatives to generate large amounts of data that are needed in order to assess their success. Educational policies are an obvious example. Here we concentrate on Mexico׳s “Educational Modernisation Programme” and try to see how this plan has affected efficiency in teaching and research at Mexico׳s universities. We use a combined approach that includes traditional ratios together with Data Envelopment Analysis models. This mixture allows us to assess changes in efficiency at each individual university and explore if these changes are related to teaching, to research, or to both. Using official statistics for 55 universities over a six year period (2007–2012), we have generated 12 ratios and estimated 21 DEA models under different definitions of efficiency. In order to make the results of the analysis accessible to the non-specialist we use models that visualise the main characteristics of the data, in particular scaling models of multivariate statistical analysis. Scaling models highlight the important aspects of the information contained in the data. Because the data is three-way (variables, universities, and years) we have chosen the Individual Differences Scaling model of Carroll and Chang. We complete the paper with a discussion of efficiency evolution in three universities.