中日城市供水系统静态效率的对比研究

文章运用DEA方法，评价了北京、东京、上海以及横滨等城市2003年-2005年间供水系统的静态效率，发现日本三个城市供水系统的效率要高于中国三个城市的效率，造成这种状况的原因主要在于中国的水价体系还不够完善，供水企业收益不能完全回收其成本。     

湖北省工业技术创新能力绩效的评价

文章首先简要介绍技术创新相关概念,利用"技术创新能力绩效评价指标体系"构建数据包络分析(DEA)评价模型.然后,根据统计数据运用DEA中的CR模型从横向、纵向两个方面深入分析湖北省工业企业技术创新的状况,得出如下结论:湖北省在中部六省区占有工业技术创新的领先地位:湖北省工业技术创新能力绩效的有效性呈现逐年增强的趋势.最后,文章提出加强技术创新促进湖北省工业发展的相关对策.为湖北省工业技术创新的深入发展提供依据.     

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.     

房地产上市公司经营效率的DEA评价

文章运用数据包络分析的CRS和VRS模型,对我国证券市场有代表性的49家房地产上市公司2004年的经营效率进行了分析与评价。通过对各上市公司的技术效率、纯技术效率、规模效率及其规模效益状况的分析得出:从整体上看,我国房地产上市公司的经营发展水平处于上升阶段;在目前经营规模上的经营效率比较高;整体上基本接近规模有效;大部分的上市公司处于规模收益递减区间。     

高技术园区技术效率与规模指数——基于DEA的实证研究

文章运用数据包络分析法评价了53个国家级开发区的投入产出效率、投入剩余和产出亏空状况,同时以超效率DEA模型为基础对这些开发区的生产效率进行综合排名,最后通过线性回归探讨影响投入产出的纯技术效率和规模指数的外部因素。结果发现:(1)在众多的开发区中真正处于有效率生产状态的地区并不多,占20.75%,处于纯技术有效的开发区占39.62%;(2)导致大部分开发区无法处于有效的生产前沿面上进行生产的最直接的原因是规模过小;(3)开发区的投入产出纯技术效率受地区的开放程度、集聚程度和气候环境的影响较大,而规模指数则受开放程度、地区经济实力和政府政策的影响较为明显。     

企业信息系统项目效率的评价方法研究

在简要总结信息系统评价方法的基础上,提出了应用改进的DEA模型客观评价企业信息系统项目效率的方法,建立了信息系统项目的投入和产出指标体系,并实证分析了大型陶瓷企业信息系统项目的相对效率.     

Performance measurement with classification information: an enhanced additive DEA model

This paper presents an improved measurement tool for evaluating performance of branches within a major Canadian bank. While there have been numerous previous studies of performance in the banking industry, particularly at the branch level, this study is different in a very significant way: specifically two kinds of data are used to develop the model. The first type of data is that related to standard transactions, available from any bank; such have formed the basis of numerous previous studies. The second type of data, obtained from the site studied, is classification information, based on branch consultant/expert judgment as to good and poor performance of branches. The purpose herein is to present a modified version of an existing benchmarking model, data envelopment analysis (DEA), and to show how this tool is applied in the banking industry. The mechanism used herein to incorporate expert knowledge within the DEA framework is to first apply a discriminant or classification tool, to quantify the functional relation that best captures the expert's mental model for performance. The outcome of this first phase is an orientation of variables to aid in the definition of inputs and outputs. The resulting orientation then defines the DEA model that makes up the second phase of the model.     

基于灰关联约束超效率DEA的重点实验室评估研究——以河北省省级重点实验室为例

目前国内外对重点实验室的评估主要采用专家评价等软评价方法,较少考虑科技投入和科技产出之间的关联关系。在对国内外重点实验室评估方法进行深入研究的基础上,利用灰色关联度分析指标内在的关联性,将其作为限制条件加入超效率DEA评价模型中,构建了基于灰色关联权重约束的超效率DEA评价模型,并应用于河北省省级重点实验室评估的实证分析。研究结果显示,此模型与传统的CCR模型和超效率DEA模型相比,既可以揭示科技投入和科技产出之间的内在联系,又可以保持DEA评价的客观性,与此同时,还可实现不同实验室评估结果的全排序,使得评估结果更加符合实际。     

国家创新型城市效率评价研究——基于两阶段DEA模型

采用共享投入型两阶段数据包络分析（DEA）模型,并构建多环节的创新型城市评价指标体系,对长三角地区创新型城市的创新效率进行评价。结果表明:在未来国家创新型城市建设过程中,相关城市不仅要考虑科技创新,还应考虑经济效益、社会效益和生态效益;在资金投入方面,需要构建金融创新体系,深化资本市场的建设,提升对创新创业的支持力度,强化科技金融服务能力;在创新型城市的建设过程中,应加快产业结构的调整,鼓励自主创业和创新型中小企业的发展,加快推进城市的生态文明建设。     

The efficiency of mutual fund companies: Evidence from an innovative network SBM approach

This paper is the first DEA (Data Envelopment Analysis) evaluation of the efficiency of a sample of mutual fund companies in a large Euro fund industry, i.e. Spain. Our novel network model links the efficiency of the core activities (portfolio management and marketing/distribution) of a mutual fund company to the efficiency of its operational management function. Our results highlight the important networking effects at the marketing stage and question the prime role of portfolio management skills in the overall efficiency of a mutual fund company. The evaluation of robust efficiency clusters indicates that the efficiency rankings obtained with our network model persist significantly along our sample period. Finally, the application of the SBM (Slacks-Based Measure) Variation III to our network model allows us to identify a large number of globally inefficient but locally efficient companies with reference to competitors with similar management resources.