The Use of Data Envelopment Analysis with Probabilistic Assurance Regions for Measuring Hospital Efficiency

This paper uses Data Envelopment Analysis (DEA) for an estimation of the cost efficiency of 70 Danish hospitals. The analysis relates to a cost function based on 483 outputs in combination with a set of probabilistic assurance regions defined by the cost distributions for each output. It is demonstrated that the probabilistic assurance region approach allows for (i) a frontier estimation in the full output space, i.e., no fixed aggregation is required, and (ii) a controlling of the variation in heterogeneity of the output clusters, in casu Diagnosis Related Groups. The likelihood of the estimated efficiency score for a given hospital can be measured based on the sensitivity of the score w.r.t. the probability levels used in the specification of confidence intervals for the probabilistic assurance regions.     

On the Role of Weight Restrictions in Data Envelopment Analysis

This paper examines the role that weight restrictions play in Data Envelopment Analysis (DEA). It is argued that the decision to include a factor (input or output) in a DEA model represents an implicit judgement that the factor has a non-trivial weight. It therefore seems perverse to allow DEA to assign a trivial weight to that factor in assessing the efficiency of a unit. There is therefore a strong case for imposing restrictions on factor weights. However, many existing methods of weight restriction are in practice unwieldy. This paper proposes an alternative approach we term contingent weight restriction which is both practical and intellectually consistent with the DEA philosophy. The paper explores the implications of alternative methods of weight restriction using simulated data from a well known production process.     

Productive Efficiency of the Swine Industry in Hawaii: Stochastic Frontier vs. Data Envelopment Analysis

Improving productive efficiency is an increasingly important determinant of the future of the swine industry in Hawaii. This paper examines the productive efficiency of a sample of swine producers in Hawaii by estimating a stochastic frontier production function and the constant returns to scale (CRS) and variable returns to scale (VRS) output-oriented DEA models. The technical efficiency estimates obtained from the two frontier techniques are compared. The scale properties are also examined under the two approaches. The industry's potential for increasing production through improved efficiency is also discussed.     

数据包络分析在企业盈利能力评价中的应用

本文是基于数据包络分析(DEA)模型对房地产上市公司盈利能力的分析。并从综合效率,规模效率,技术效率,规模报酬四个方面对房地产进行综合评价。     

Lower Bound Restrictions on Intensities in Data Envelopment Analysis

We propose an extension to the basic DEA models that guarantees that if an intensity is positive then it must be at least as large as a pre-defined lower bound. This requirement adds an integer programming constraint known within Operations Research as a Fixed-Charge (FC) type of constraint. Accordingly, we term the new model DEA_FC. The proposed model lies between the DEA models that allow units to be scaled arbitrarily low, and the Free Disposal Hull model that allows no scaling. We analyze 18 datasets from the literature to demonstrate that sufficiently low intensities—those for which the scaled Decision-Making Unit (DMU) has inputs and outputs that lie below the minimum values observed—are pervasive, and that the new model ensures fairer comparisons without sacrificing the required discriminating power. We explain why the low-intensity phenomenon exists. In sharp contrast to standard DEA models we demonstrate via examples that an inefficient DMU may play a pivotal role in determining the technology. We also propose a goal programming model that determines how deviations from the lower bounds affect efficiency, which we term the trade-off between the deviation gap and the efficiency gap.     

DEA在仓库运作管理中的应用

数据包络分析能对决策单元的有效性进行评价。本文应用数据包络分析的C2R模型,对仓库的运作效率进行研究。选取某部的8个备件仓库为样本,基于C2R模型计算结果,得到一些有价值的仓库运作管理方面的信息。     

A Generalized Goals-achievement Model in Data Envelopment Analysis: an Application to Efficiency Improvement in Local Government Finance in Japan

Abstract

Data envelopment analysis (DEA) has become an established benchmark tool in efficiency strategies in both the public and the private sectors. The aim of this paper is to present and apply a newly developed, emerging from a blend of a Distance Friction Minimization (DFM) and a Goals Achievements (GA), model in DEA. The above-mentioned DFM-GA model is illustrated empirically by using a data set of efficiency indicators for cities in Hokkaido prefecture in Japan. In summary, this paper presents a practical policy instrument that may contribute to efficient decision making of both public and private actors.

Modèle généralisé de réalisation des objectifs dans l'analyse par la méthode d'enveloppe: application dans l'augmentation du rendement dans les finances des administrations régionales au Japon

RÉSUMÉ?La méthode d'enveloppe [data envelopment analysis (DEA)] est un étalon bien établi pour les stratégies d'efficacité tant dans le secteur public que dans le secteur privé. L'objectif de la présente communication est de présenter et d'appliquer un modèle de méthode d'enveloppe nouveau et ajusté. Le modèle DFM-GA susmentionné est illustré de façon empirique au moyen d'un ensemble d'indicateurs d'efficacité pour des villes de la préfecture d'Hokkaido, au Japon. En résumé, la présente communication présente un instrument de politique pratique qui pourrait contribuer à des prises de décision efficaces par des acteurs tant publics que privés.

Un modelo generalizado de logro de objetivos en el análisis envolvente de datos: aplicación a la mejora de la eficiencia en las finanzas de gobiernos locales de Japón

RÉSUMÉN?El análisis envolvente de datos (DEA) se ha convertido en una herramienta de referencia establecida en las estrategias de eficiencia, tanto en el sector público como privado. El objetivo de este trabajo es presentar y aplicar un modelo DEA ajustado y recién desarrollado. El modelo DFM-GA mencionado anteriormente se ilustra empíricamente utilizando un conjunto de datos de indicadores de eficiencia relacionados con ciudades de la prefectura de Hokkaido, Japón. En resumen, este trabajo presenta un instrumento práctico de política que puede contribuir a una toma de decisiones eficiente tanto de actores públicos como privados.

     

基于偏好DEA模型的区域高等教育资源配置结构效益评价

资源配置结构合理与否,直接关系到区域高等教育系统整体的规模、质量和效益。本文按照评价对象群体公认的合理的资源配置结构标准,对评价指标权重加以约束,利用带偏好锥的DEA模型评价了我国31个省市区高等教育资源配置的结构效益,系统分析了现阶段我国各省市区高等教育资源配置结构方面的薄弱环节。这对于优化区域高等教育资源配置结构、提升区域高等教育竞争力具有重要的实践价值。     

集成化供应链绩效评价的数据包络分析应用

利用数据包络分析（DEA）处理多输入多输出、无需考虑数据量纲影响的非参数统计估计的＂天然＂优势,并利用主成分分析法对参考绩效指标进行筛选,对多条供应链绩效进行横向评价,不但可以区分被评价者绩效水平的优劣,而且还可以得出处于尚未达到最优水平的被考评者应该优化的方向;同时对有效决策单元进行排序,获得所有被测评者绩效水平的总排序,从而体现了该方法在供应链绩效评价当中应用的优越性.     

高校科研管理绩效评价中数据包络分析模型研究

目前在高校科研管理绩效评价研究中使用了数据包络分析,但现有模型与高校科研现状有一定差距,在学科差异、学校差异和指标选取方面存在一定不足。本研究提议引入加权DEA模型、交互基准群DEA模型、非期望产出DEA模型加以完善。     

基于DEA模型的企业员工绩效考评研究

利用数据包络分析(DEA)方法对企业员工进行绩效考评,目的是真实、客观地反映员工的工作表现。本文提出运用只有输出(输入)和二次相对有效性的DEA模型对企业员工进行静态与动态的绩效考评,并结合实例进行实证研究,为人力资源管理提供了有价值的方法。     

Selecting Sites for New Facilities Using Data Envelopment Analysis

This paper develops a mathematical programming model for obtaining a best set of sites for planned facilities. The model is concerned with those situations where resource constraints are present. The specific setting for the paper involves the selection of sites for a set of retail outlets, wherein the ratio of aggregate outputs to inputs for the selected set is maximal among all possible sets that could be chosen. At the same time, the model guarantees that the only sets of stores allowable are those for which the available resources are used to the maximum extent possible.     

基于数据包络分析的供应链知识共享评价

供应链中的知识共享可以提高知识创新与运用的效率,使供应链节点企业间的知识水平达到协调与优化,从而提高供应链的整体绩效水平。讨论了使用数据包络分析(DEA)方法对供应链间的知识共享水平进行评价,并建立了评价的相关输入输出指标体系。     

Visualizing Efficiency and Reference Relations in Data Envelopment Analysis with an Application to the Branches of a German Bank

The interest in Data Envelopment Analysis (DEA) as a method for analyzing the productivity of homogeneous Decision Making Units (DMUs) has significantly increased in recent years. One of the main goals of DEA is to measure for each DMU its production efficiency relative to the other DMUs under analysis. Apart from a relative efficiency score, DEA also provides reference DMUs for inefficient DMUs. An inefficient DMU has, in general, more than one reference DMU, and an efficient DMU may be a reference unit for a large number of inefficient DMUs. These reference and efficiency relations describe a net which connects efficient and inefficient DMUs. We visualize this net by applying Sammons mapping. Such a visualization provides a very compact representation of the respective reference and efficiency relations and it helps to identify for an inefficient DMU efficient DMUs respectively DMUs with a high efficiency score which have a similar structure and can therefore be used as models. Furthermore, it can also be applied to visualize potential outliers in a very efficient way.JEL Classification: C14, C61, D24, M2     

Multicomponent Efficiency Measurement and Shared Inputs in Data Envelopment Analysis: An Application to Sales and Service Performance in Bank Branches

In most applications ofDEA presented in the literature, the models presented are designedto obtain a single measure of efficiency. In many instances however,the decision making units involved may perform several differentand clearly identifiable functions, or can be separated intodifferent components. In such situations, inputs, in particularresources, are often shared among those functions. This sharingphenomenon will commonly present the technical difficulty ofhow to disaggregate an overall measure into component parts.In the present paper, we extend the usual DEA structure to onethat determines a best resource split to optimize the aggregateefficiency score. The particular application area investigatedis that involving the sales and service functions within thebranches of a bank. An illustrative application of the methodologyto a sample of branches from a major Canadian bank is given.     

Testing Independence in Models of Productive Efficiency

Bootstrap methods for inference in nonparametric models of productive efficiency can be simplified, reducing computational burden, when the independence condition implicitly assumed in Simar and Wilson (1998) holds. This paper surveys nonparametric tests of independence that might be useful in this context.     

Using Simulation and Data Envelopment Analysis to Compare Assembly Line Balancing Solutions

This paper presents a technique for comparing the results of different assembly line balancing strategies by using Data Envelopment Analysis (DEA). Initially, several heuristics--which can be thought of as assembly line balancing strategies--were used to solve seven line-balancing problems. The resulting line balance solutions provided two pieces of information that were of particular interest: the number of workers needed and the amount of equipment needed. These two items were considered inputs for DEA. The different line balance solutions were then used as layouts for simulated production runs. From the simulation experiments, several output performance measures were obtained which were of particular interest and were used as outputs for DEA. The analysis shows that DEA is effective in suggesting which line balancing heuristics are most promising.     

参与方能力视角下的标准化建设项目绩效评价：一种数据包络方法

标准化建设项目的绩效往往并不＂标准＂,而参与方的经验能力是对各项目绩效进行比较与评价的最佳路径。以参与方能力为投入指标,绩效表现为产出指标,本文构建了用于对标准化建设项目绩效进行评价的数据包络模型,对项目的有效性进行评价与排序,并为无效项目的能力投入结构给出优化意见;同时,以上海通用别克汽车品牌4S店建设项目为例进行实证分析,具体展示了模型构建和分析优化的过程,可为其它项目提供借鉴。     

物流服务业生产效率测度研究

在分析物流服务业特点的基础上构建其测度指标体系,利用LISREL软件对测度指标进行验证性因子分析,验证各个测度指标与其所属影响因子的关联性,并对测度指标的有效性进行验证。其次,构建结构方程模型并计算测度指标的权重,分析物流服务业各影响因子及其与测度指标之间的关系,为物流服务业的发展和绩效改善提供决策依据。     

基于数据包络分析的经营性城镇市政设施投资项目经济效益后评价方法研究与案例分析

依次介绍了:研究对象——经营性城镇市政设施投资项目,研究方法——数据包络分析C2R模型;并打破传统,结合数据包络分析展开了经济效益后评价新方法的探讨,最后给出了实例分析。