DEA models for extended two-stage network structures

Liang et al. (2008) [1] developed DEA models based upon game approach to decompose efficiency for two-stage network structures where all outputs of the first stage are the only inputs to the second stage. This paper extends Liang et al. (2008) [1] by assuming that the inputs to the second stage include both the outputs from the first stage and additional inputs to the second stage. Two models are proposed to evaluate the performance of this type general two-stage network structures. One is a non-linear centralized model whose global optimal solutions can be estimated using a heuristic search procedure. The other is a non-cooperative model, in which one of the stages is regarded as the leader and the other is the follower. The newly developed models are applied to a case of regional R&D of China.     

工业用水系统效率评价:考虑污染物可处理特性的两阶段DEA

提高水资源使用效率和污水处理效率是解决目前水资源短缺的重要途径。中国工业用水系统可分为生产用水子系统和污水处理子系统。本文考虑两个子系统之间的联系,并区分污染物在两个子系统中的弱处理和强处理特性,提出了一种基于DEA的两阶段评价模型。应用本文提出的新模型分析中国30个省级区域的工业用水系统的效率,结果表明: 中国省级区域工业用水整体效率不高,且地域分布特征明显,东部、西部、中部效率依次递减; 中国工业用水系统的非有效性主要源于污水处理效率的影响;工业用水系统效率与地区水资源禀赋存在一定的关系,水资源短缺的地区用水效率相对较高。文章所提出的方法兼顾生产用水子系统和污水处理子系统之间的相互影响,能够同时评价两个子系统效率和工业用水系统的整体效率,能有效发现系统中影响整体效率的关键环节,且可以应用于其他能源效率评价问题,具有明显的实际应用价值。     

基于自由处置性的网络系统效率评价模型研究

网络系统生产可能集是构建网络DEA模型的基础,而相邻生产子过程的投入产出连接条件则是构造生产可能集的关键。现有的网络DEA模型在本质上都假设所有子过程的投入产出都满足强自由处置性,然而在实际生产管理活动中,这一假设未必成立。本文从各类自由处置公理出发,系统地研究了各种类型的子过程投入产出连接条件,构建了一般网络系统的生产可能集,给出了相应的等价形式,并构建了相应的网络DEA模型用于评价决策单元的效率。最后利用本文提出的方法和模型对我国上市银行的效率进行了评价。本文的研究对于一般网络系统的绩效评价和改进具有重要的意义。     

Measuring performance of two-stage network structures by DEA: A review and future perspective

Data envelopment analysis (DEA) is a method for measuring the efficiency of peer decision making units (DMUs). An important area of development in recent years has been devoted to applications wherein DMUs represent two-stage or network processes. One particular subset of such processes is those in which all the outputs from the first stage are the only inputs to the second stage. The current paper reviews these models and establishes relations among various approaches. We show that all the existing approaches can be categorized as using either Stackelberg (leader-follower), or cooperative game concepts. Future perspectives and challenges are discussed.     

Slacks-based inefficiency approach for general networks with bad outputs: An application to the banking sector

In this paper the efficiency assessment of general networks of processes that produce both desirable and undesirable outputs is addressed. This problem arises in many contexts (e.g. transportation, energy generation, etc.). A general networks slacks-based inefficiency (GNSBI) measure can be computed using a simple linear program that takes into account the weak disposability of the bad outputs. The slacks-based inefficiency (SBI) of each process is also calculated. Target values for all inputs, outputs (both desirable and undesirable) and even intermediate products are also provided. The proposed approach is rather general and can accommodate many different network topologies and returns to scale assumptions. Two applications to the banking sector are presented: one to assess banks efficiencies and another to assess bank branches.     

嵌套并联结构两阶段DEA下科技创新效率测度与分解

目前有许多研究将两阶段DEA模型应用到科技创新活动当中,一般将创新活动分为研发和转化两个阶段,为了进一步探讨不同转移转化方式下科技成果的转化效率以获得更多的详细信息,本文拓展了传统的两阶段DEA模型,考虑了嵌套并联结构的两阶段网络DEA模型,将科技创新活动分为科技成果研发阶段和科技成果转化阶段,并将科技成果转化阶段分为内部转化和外部转化两个并联子系统。本文选取14家中科院院属单位作为被评价对象,应用加权加法分解方法计算整体效率和各阶段子效率。通过将本文模型与传统两阶段模型进行对比发现,传统模型会低估科技成果转化效率。结果表明：整体科技创新效率均值偏低,科技成果研发效率均值高于科技成果转化效率均值,科技成果转化效率仍有很大的提升空间。科技成果转化阶段中内部转化效率普遍较高但是外部转化效率普遍较低,较低的外部转化效率是导致科技成果转化效率低下的主要原因。最后,本文将所有被评价单位分为四类机构,分析提高科技创新效率的实现路径,可以通过重点突破模式和渐进突破模式来实现整体效率的提高。     

部分中间产出作为最终产品的两阶段合作效率

网络DEA模型研究多个进程和多个子系统的复杂系统的效率度量.针对中间产出无法为第2阶段完全消耗的情形,传统DEA模型对系统效率的评价偏高,已有网络DEA模型则对系统效率的评价偏低.本文提出部分中间产出作为最终产品,进入流通渠道的两阶段效率模型,用来测度两阶段生产过程的真实效率.采用乘积形式描述两阶段合作的特征,给出不同...     

Axial solutions for multiple objective linear problems. An application to target setting in DEA models with preferences

In this paper we introduce the class of axial solutions for multiple objective optimization problems in contexts in which partial information on preference weights is available. These solutions combine the use of an improvement axis to direct the search of the most preferred result with the concept of efficiency with respect to preference information.