非独立并联生产系统的DEA效率评价研究

对复杂生产系统进行效率评价,是改善其生产效率的基础.针对非独立并联结构生产系统的效率评价问题开展研究.首先,将两阶段非独立并联生产系统等价为先并联后串联结构的混联生产系统;其次,将混联生产系统的整体效率定义为各串联子系统效率的乘积,而各个串联子系统的效率则定义为内部各并联子系统效率的加权和,并给出了对应的DEA效率评价模型;最后,有关定理和算例分析证实了该模型能更合理地评价此类生产系统的技术效率,能够更大程度地挖掘系统整体性能改善的潜力.     

A network DEA quantity and quality-orientated production model: An application to Australian university research services

The motivation for this analysis is the recently developed Excellence in Research for Australia (ERA) program developed to assess the quality of research in Australia. The objective is to develop an appropriate empirical model that better represents the underlying production of higher education research. In general, past studies on university research performance have used standard DEA models with some quantifiable research outputs. However, these suffer from the twin maladies of an inappropriate production specification and a lack of consideration of the quality of output. By including the qualitative attributes of peer-reviewed journals, we develop a procedure that captures both quality and quantity, and apply it using a network DEA model. Our main finding is that standard DEA models tend to overstate the research efficiency of most Australian universities.     

A study of DEA models without explicit inputs

In performance evaluations, data without explicit inputs (such as index data, pure output data) are widely used. To directly use such data, this paper presents a study on building DEA models without explicit inputs, so-called DEA-WEI models, which are applicable to the evaluation applications where inputs are not directly considered. We provide an axiom foundation of these kinds of models, and further discuss how to incorporate value judgments of decision makers into these DEA-WEI models. Several such models are derived. Finally, applications of the DEA-WEI models are presented.     

Estimation of portfolio efficiency via DEA

Traditional DEA models and nonlinear (diversification) DEA models are often used in performance evaluation of portfolios. However, the diversification models are usually very complicated to compute except the very basic models. And the classic DEA models still need to be further justified and tested, since it is not clear whether they are over-linearised according to the diversification models. The existing studies on performance evaluation via the classic DEA models generally focus on the selection of inputs and outputs. In this work, we investigate theoretical foundation of DEA models for portfolios from a perspective of sampling portfolio. We show the classic DEA provides an effective and practical way to approximate the portfolio efficiency (PE). We further verify this approach through different portfolio models with various frictions and bounds on the market. Through the comprehensive simulations carried out in this study, we show that with adequate data sets, the classic DEA models can effectively sample portfolios to take into account sufficient diversification, and thus can be used as an effective tool in computing the PE for their performance assessments. This study can be viewed as a justification of the classic DEA performance assessments and the way to introduce other efficiency notions (like allocation efficiency, scale efficiency, etc) into assessment of portfolios.     

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。     

A fair evaluation of certain stage in a two-stage structure: revisiting the typical two-stage DEA approaches

The efficiency of decision processes with a two-stage structure has been studied by some modified versions of Data Envelopment Analysis (DEA) methodology, such as the relational or centralized model, and the non-cooperative model. After revisiting the rationale of the centralized model provided by the literature, we find that some unfairness exist in its efficiency evaluation of certain stage. This unfairness leads to the usual underestimation of the overall efficiency by the centralized model. Furthermore, because the independent DEA model for one stage ignores its relation and coordination with the other stage and the two-stage system, externalities between these members may arise and lead to the seeming contradiction in efficiencies derived by independent DEA models for the stages and the black box system. Therefore, we argue that the efficiency of certain stage in the context of a two-stage structure should be reevaluated instead of simply using the independent DEA model. A sequence of leader-follower procedures, with data adjustment on intermediates, is proposed to eliminate the externalities and to ensure a fair evaluation. We find that, after this data adjustment, the reevaluation of the second stage for a given Decision Making Unit (DMU) yields the same result as obtained by the standard DEA model regarding the two-stage as a black box. Moreover, some explicit relations are established between the black box model, the centralized model, and the non-cooperative model. Two typical examples taken from the literature illustrate our main results. Our findings also imply that more emphasis should be placed on the game theoretic DEA approach to model the efficiency evaluation of two-stage processes.     

数据包络分析中变量分类研究评述

数据包络分析的研究历史与研究者对于变量特性的认知历史是紧密联系在一起的。在数据包络分析的早期研究中,所有的投入或者产出变量都被视为可数量化、可自由处置、单角色的等。研究者逐渐认识到有些变量是不可数量化的、非自由处置的、双角色的,因此,不同目的的DEA模型被提出并加以研究。本文对数据包络分析中有关变量分类的研究进行系统性评述。     

Time-staged outputs in DEA

This paper examines the issue of handling outputs in DEA that occur at different stages in time. As a backdrop for the research we examine a data set involving the evaluation of efficiencies of business schools. The data focuses explicitly on a particular institution, namely the business school ENCSH (Escuela de Negocios, Ciencias Sociales y Humanidades) at ITESM (Instituto Tecnologico y de Estudios Superiores Monterrey) in Mexico. This school of business is evaluated relative to 41 peer institutions in the USA, using data envelopment analysis as the principal evaluation instrument. Using internships and jobs as outputs, and various quality measures as inputs, we demonstrate that this problem setting gives rise to the phenomenon of time-staged outputs. Specifically, the two outputs occur at different points in time, meaning that one of them plays a dual role. While this problem might potentially be viewed as a type of network DEA model, we demonstrate that a modification of the conventional DEA methodology is a more appropriate structure to handle this situation.     

考虑环境属性约束的平行结构DEA模型

针对平行结构DEA模型在构造虚拟参考单元时没有考虑任何约束可能存在低估效率的情况,通过加入决策单元的环境属性对现有的平行结构模型进行了改进,从而在组合为虚拟参考单元的子决策单元之间添加必要的约束,使得模型所得的效率值更具现实意义。最后,将改进后的平行结构模型应用于中国各省份污染治理效率评价问题,从实证角度验证了模型的合理性和有效性。     

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.     

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.     

Developing a supplier selection system through integrating fuzzy AHP and fuzzy DEA: a case study on an auto lighting system company in Taiwan

Supplier selection plays a very important role in supply chain management. This study intends to develop a novel performance evaluation method, which integrates both fuzzy analytical hierarchy process (AHP) method and fuzzy data envelopment analysis (DEA) for assisting organisations to make the supplier selection decision. Fuzzy AHP method is first applied to find the indicators’ weights through expert questionnaire survey. Then, these weights are integrated with fuzzy DEA. We use α -cut set and extension principle of fuzzy set theory to simplify the fuzzy DEA as a pair of traditional DEA model. Finally, fuzzy ranking using maximising and minimising set method is able to rank the evaluation samples. A case study on an internationally well-known auto lighting OEM company shows that the proposed method is very suitable for practical applications.     

基于DEA/AR博弈交叉效率方法的学术期刊评价研究

学术期刊的评价问题是期刊研究领域的重要课题之一.传统数据包络分析方法在评价多维指标下的期刊绩效时都是基于“自评”模式.由于未能考虑“他评”,造成评价结果容易被夸大等问题.本文在非合作博弈框架下基于数据包络分析/保证域博弈交叉效率方法研究期刊的投入产出绩效评价问题,并选取17种中国科技核心期刊为例展开分析.研究发现:1)某些具有很高行业影响力的期刊,虽然具有较高的产出值,但是刊文量较多,导致实际评价结果不够理想;2)指标权重的偏好变化会使得期刊评价值出现增加、不变和减少三种情况;3)期刊在自引频次上存在着过度、适度和不足三种情形.相关评价结果可为期刊工作者在提升期刊竞争力方面提供决策参考.     

金融监管对商业银行产品创新影响——基于两阶段DEA模型的研究

以金融监管为视角,从银监会政策发布到各商业银行设计理财产品产生收益,其政策效应过程是有衔接分阶段性的。本文运用两阶段的数据包络分析(Data Envelopment Analysis, DEA)方法,将监管环境下银行理财产品的运营过程分为创新产品设计与创新产品市场表现两个阶段,得到了2004年至2014年间我国银行业的创新效率,结果显示第一阶段的银行业产品创新效率和第二阶段的理财产品市场表现效率基本上呈现出正相关的关系,且金融监管对商业银行产品创新的影响效果有一定的滞后性。此外,通过计算出历年银行业创新效率投入指标的改进值,找出了效率非有效的年份与最佳效率的年份在投入产出上的差距,并从监管者的角度和银行操作层面为针对银行产品创新的监管改进提供了政策建议。     

A Bayesian approach to statistical inference in stochastic DEA

Stochastic DEA can deal effectively with noise in the non-parametric measurement of efficiency but unfortunately formal statistical inference on efficiency measures in not possible. In this paper, we provide a Bayesian approach to the problem organized around simulation techniques that allow for finite-sample inferences on efficiency scores. The new methods are applied to efficiency analysis of the Greek banking system for the period 1993–1999. The results show that the majority of the Greek banks operate close to best market practices.     

基于DEA方法的中国商业银行综合效率的研究

根据数据包络方法(DEA)的非阿基米德模无穷小C2R模型,结合中国大陆商业银行的投入和产出的特点,建立了综合考虑银行盈利能力与风险控制能力的投入产出指标体系和中国商业银行综合效率的评价模型.基于4家国有独资银行样本、14家国有银行和股份制银行的混合样本两种情况,分别评测出了各家银行综合效率值.给出了低效率银行的人员数、固定资产净值、营业支出,所有者权益、机构个数等投入的冗余率和营业收入、新增存款总额、新增贷款总额、资本收益率、不良贷款率等指标的产出不足率.论文的创新和特色一是运用不良贷款率反映银行产出的质量,改变了现有研究忽略贷款质量差异的弊端.二是通过定量分析找出具体银行效率不高的真正原因,有针对性地提出了提高银行效率的宏观对策和具体对策.三把14家国有银行与股份制银行合并起来进行评价和比较,又显示出了两种银行组织方式下银行间的真实差距.     

The performance evaluation of regional R&D investments in China: An application of DEA based on the first official China economic census data

R&D (Research and Development) activities represent the basic core of corporate science and technology activities, and play a crucial role in enhancing the ability of companies to achieve rapid and sustainable growth. In recent years, the total R&D investments in China have increased significantly and the proportion of the industrial investments in R&D activities relative to national R&D investments has increased rapidly. In order to investigate the effectiveness of these R&D investments, we utilize Data Envelopment Analysis (DEA) models to evaluate the relative efficiencies of 30 regional R&D investments using the First Official China Economic Census Data in 2004. Our investigation and study indicate the following: (1) Only six provinces are global technical efficient and the performance of regional R&D investments in China needs to improve dramatically. (2) Increasing returns to scale have not yet occurred in any province. Constant returns to scale have prevailed in most provinces in the Western region, and decreasing returns to scale have prevailed in most provinces in the Eastern and Central regions. (3) There are no direct relationships between global technical efficiency and the amount of R&D investment. The Western region has the highest average radial efficiency score, followed by the Eastern region, and then by the Central region. (4) The Eastern region has advantages in local technical efficiency, the Western region has advantages in scale efficiency, while the Central region has neither technical efficiency advantages nor scale efficiency advantages. Suggestions are proposed to improve efficiencies of regional R&D investments.     

基于DEA技术的华东地区建筑业生产效率研究

利用DEA方法对2007年华东地区的建筑业生产效率进行详细分析发现,江西、安徽及山东均处于规模递增阶段,特别是安徽和山东,存在较大的投入冗余及产出不足;进一步分析安徽的生产效率增长情况发现,其经历了由高速增长到低速增长的转变,而这种生产效率增长仅来自技术进步,未获得任何规模经济;最后,得出安徽及山东建筑业发展方向主要为如何实现现有资源的整合及优化,通过鼓励企业资产兼并与重组,提高单个企业的资源利用效率,最终实现建筑业的规模经济。     

Performance evaluation based on multiple attributes with nonparametric frontiers

Performance rating and comparison of a group of entities is frequently based on the values of several attributes. Such evaluations are often complicated by the absence of a natural or obvious way to weight the importance of the individual dimensions of the performance. This paper proposes a framework based on nonparametric frontiers to rate and classify entities described by multiple performance attributes into ‘performers’ and ‘underperformers’. The method is equivalent to Data Envelopment Analysis (DEA) with entities defined only by outputs. In the spirit of DEA, the weights for each attribute are selected to maximize each entity’s performance score. This approach, however, results in a new linear program that is more direct and intuitive than traditional DEA formulations. The model can be easily understood and interpreted by practitioners since it conforms better to the practice of evaluating and comparing performance using standard specifications. We illustrate the model’s use with two examples. The first evaluates the performance of employees. The second is an application in manufacturing where multiple quality attributes are used to assess and compare performance of different manufacturing processes.     

Performance measurement and classification data in DEA: Input-oriented model

This paper presents an improved efficiency measurement tool by modifying the existing data envelopment analysis methodology to permit the incorporation of expert knowledge. A previous paper examined the inclusion of such knowledge within the additive model. This information appeared in the form of a binary classification of a subset of the decision making units under study (e.g. good versus poor performers). In the current paper, we extend this logic to the input-oriented radial projection model. We demonstrate that the inclusion of this and other forms of expert judgment can improve the performance of the DEA tool in the sense that the efficiency scores are more in line with expert/management beliefs.