具有双重角色和非期望要素的供应商评价两阶段DEA模型

在基于DEA方法的供应商评价过程中,会出现供应商同时具有双重角色要素和非期望输出要素的情形。文章提出了一个处理双重角色要素的新思路,认为DEA模型中双重角色要素同时扮演了输入和输出两个角色,所有双重角色要素本质上就是网络DEA模型中的中间变量,并同时认为包含双重角色要素的生产系统一定能分解成为多个子系统,其中的双重角色要素既是一个子系统的输入,同时又是另一个子系统的输出。为测度供应商的效率,基于已有关系型两阶段DEA模型,将供应商的生产运营视为两阶段过程,其双重角色要素视为两阶段过程的中间变量,并通过将所有输出以加权和的形式表达,但对非期望输出用负的权重的方式,提出了一个具有双重角色和非期望输出要素的供应商评价两阶段DEA模型,最后用一个实例验证了方法的可行。     

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...     

基于两阶段交叉效率模型的中国商业银行效率评价

为了更好的评价我国商业银行的效率,在传统两阶段DEA模型中引入交叉效率,并对两阶段生产系统的内部结构进行优化,构建了考虑共享投入和非期望产出的两阶段交叉效率模型。最后结合中国16家商业银行2006-2015年的年度报表,分别应用传统的两阶段DEA模型和新模型评价样本银行的效率。结果表明：新模型比传统模型更客观、区分力更强,具有更强的稳定性,更适合用于评价我国商业银行的效率。     

一个新的考虑非期望产出的非径向-双目标DEA模型

如何实现对环境效率更准确的定量评价,是国际上从事DEA研究的学者们当前关注的问题之一。在传统DEA效率模型的基础上,综合考虑评价过程中期望产出与非期望产出之间的差异以及实际生产过程中人们追求期望产出最大化和非期望产出最小化的双重目标,构建非期望产出的非径向-双目标DEA环境效率评价模型,通过线性加权和法转化为一个求最大值的单目标线性规划问题。研究结果表明,这种新模型不仅可以分析DEA有效性与Pa-reto最优之间的关系,还利用决策单元的投影获得投入和产出的可调整量,从而提高考虑非期望产出的环境效率评价的精度。实证分析结果与现实情况的高度吻合,说明这种新的非径向-双目标DEA环境效率模型是有效的。     

存在非期望产出的决策单元阻塞问题研究

阻塞是指企业的过量投入引起生产效益下降的经济现象,近年来已经受到实业界与学术界的广泛关注。现有的决策单元阻塞问题研究普遍假设产出均是期望指标,然而,在实际生产中很多产出属于非期望指标。本文构建了同时存在期望产出和非期望产出决策单元的阻塞度量模型,该模型不仅可以判别决策单元是否存在阻塞,而且可以测算各项投入的阻塞程度,并给出了决策单元阻塞和技术无效之间的关系。最后,运用所提出的模型对我国上市商业银行的效率和阻塞情况进行了测算与分析,验证了本文模型的实用性与可行性。     

环保项目有效性评价的数据包络分析方法

利用数据包络分析(DEA)方法评价环保项目有效性时,输入、输出数据中可能同时存在环境因素,不符合传统的DEA模型要求,需要对这些数据进行转换。本文讨论了"不好的"数据平移转换法、输入和输出因素转换法、倒数转换法,建立了三种DEA模型,对建立的DEA模型一致性进行了分析,拓宽了以前DEA模型的应用范围。一个例子验证了这三种方法在评价环保项目有效性时是一致的。     

基于DEA的两阶段系统中间产品公平设定研究

在由两个子决策单元串联组成的两阶段系统中,公平设定中间产品目标对确保和激励两阶段相互合作以达到整个系统的最佳性能至关重要.数据包络分析(DEA)作为系统绩效评估的一种非参数方法吸引了众多学者的注意;基于此方法,本文提出一个考虑公平关切的两阶段DEA模型用于设定两阶段系统中间产品目标,并证明据此模型获得的设定方案正是一个纳什讨价还价博弈的均衡解.     

非期望产出、影子价格与无效决策单元的改进

本文首先建立考虑非期望产出的非参数DEA效率模型,从影子价格的视角论证DEA有效的充分必要条件,计算出无效DMU的可改进量,从而构建了一个考虑非期望产出、影子价格以及无效决策单元的改进的非参数DEA模型,然后通过一个算例进行实证分析,将这个新的模型和经典的SBM模型进行比较,结果显示两者的相关系数超过0.9,而且这一新模型还显示出一些SBM模型所没有的优良特性.这种新的非参数方法不仅能够对环境效率水平进行测度评价,而且相较于参数方法而言,它不需要事先设定规范的函数形式,对指标数据也不需要考虑计量单位问题,具有比较独特的优势.     

存在保证域的模糊非径向偏好DEA模型——基于中科院24个研究所的实证分析

数据包络分析（DEA）是一种非参数化的方法,用于评价具有类似输入和输出的决策单元的效率。传统的非径向DEA模型假设输入和输出数据均为准确值,且对权重变量不加以限制,本文构建了存在保证域的模糊非径向偏好DEA模型,并给出了一种基于模糊数截集的模型求解方法,有效地解决了输入和输出全部或部分为模糊数的决策单元评价问题。最后给出了一个中科院研究所效率评价的实例说明了方法的有效性。     

高碳区域低碳发展全要素效率评价——基于山西省的统计数据

笔者以山西省为例,借鉴全要素生产率(TFP)评价效率的基本思想,创新性地以环境污染治理投资、研发投资和劳动投入为投入指标,同时设置期望产出和非期望产出两类产出指标,对山西省2002~2011年低碳发展进行了超效率DEA评价。     

Two-stage DEA models with undesirable input-intermediate-outputs

Data envelopment analysis (DEA) is a non-parametric approach for measuring the relative efficiencies of peer decision making units (DMUs). Many studies have examined DEA efficiencies of two-stage systems, where all the outputs from the first stage are the only inputs to the second stage. Although single-stage DEA models with undesirable input-outputs have been extensively studied, there still lacks of more systematical investigation on two-stage DEA with undesirable variables. For instance, depending on its operating model, even whether an intermediate variable is desirable or undesirable can be questionable for a particular two-stage system. Furthermore, most of the existing studies on two-stage systems focus on the case where only the final outputs are undesirable. In this work, we try to systematically examine two-stage DEA models with undesirable input-intermediate-outputs. Particularly, we utilize the free-disposal axioms to construct the production possibility sets (PPS) and the corresponding DEA models with undesirable variables. The proposed models are then used to illustrate some theoretical perspectives by using the data of China׳s listed banks.     

Target intermediate products setting in a two-stage system with fairness concern

In a two-stage system with two divisions connected in series, fairly setting the target outputs for the first stage or equivalently the target inputs for the second stage is critical, in order to ensure that the two stages have incentives to collaborate with each other to achieve the best performance of the whole system. Data envelopment analysis (DEA) as a non-parametric approach for efficiency evaluation of multi-input, multi-output systems has drawn a lot of attention. Recently, many two-stage DEA models were developed for studying the internal structures of two-stage systems. However, there was no work studying fair setting of the target intermediate products (or intermediate measures) although unreasonable setting will result in unfairness to the two stages because setting higher (fewer) intermediate measures means that the first (second) stage must make more efforts to achieve the overall production plan. In this paper, a new DEA model taking account of fairness in the setting of the intermediate products is proposed, where the fairness is interpreted based on Nash bargaining game model, in which the two stages negotiate their target efficiencies in the two-stage system based on their individual efficiencies. This approach is illustrated by an empirical application to insurance companies.     

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.     

Duality of weakly disposable technology

The axiom of weak disposability is frequently imposed in data envelopment analysis (DEA) models involving undesirable outputs such as pollution. This paper sheds new light on the economic interpretation of weak disposability by developing dual formulations of the weakly disposable DEA technology. We find that the economic implications of weak disposability on the multiplier DEA problem are two-fold: (1) the shadow prices of the undesirable outputs can be positive or negative, and (2) the economic loss of the benchmark cannot exceed the suck cost of the inputs. We interpret the second implications as a limited liability condition. The dual formulations developed in this paper enable one to estimate shadow prices of the undesirable outputs using the weakly disposable technology. The insights gained are illustrated by a numerical example and an empirical application to the US power plants.     

Internal resource waste and centralization degree in two-stage systems: An efficiency analysis

Internal resource waste refers to the waste in the intermediate resources between the upstream stage and downstream stage in a production or service system. This study examines a system with a two-stage structure, in which the outputs from the first stage are taken as the inputs for the second stage. Two-stage systems can exist in centralized, decentralized, or mixed organizational modes. In this paper, we propose two-stage DEA models considering a degree of centralization that makes it possible to measure internal resource waste in different system modes. Some managerial insights are tested and verified from the perspective of efficiency analysis. We find that: 1) when there is only one intermediate measure in a centralized two-stage system, internal resource waste can be eliminated completely, and 2) a higher degree of centralization in a two-stage system can lead to less internal resource waste and more expected outputs. Finally, we present a numerical example and two practical real-world examples that illustrate our approach and findings.     

Stage efficiency evaluation in a two-stage network data envelopment analysis model with weight priority

Conventional DEA models treat the entire production system as a black box and ignore its internal structures. To address this issue, many studies have examined the DEA efficiencies of two-stage systems in which all outputs of the first stage are the only inputs to the second stage. Based on game theory, the non-cooperative model and centralized model were developed for such a two-stage network structure. However, for the centralized model with multiple optimal solutions and the non-cooperative model, an assumption is required as to whether the first or second stage should be assigned the absolute priority for optimization. In many cases, certain circumstances might exist in which one stage does not completely dominate the other stage. In this paper, we develop a methodology for assessing the overall and stage efficiencies by considering the different and DMU-specific degree of priority given to the stages. Particularly, the non-cooperative model and the centralized model can be deemed as special cases. Moreover, we compare the proposed approaches with the existing approaches, which indicates that our approaches can greatly reduce the computational burden. Two empirical examples are used to demonstrate the proposed approach.