Data envelopment analysis for scale elasticity measurement in the stochastic case:with an application to Indian banking

In the nonparametric data envelopment analysis literature,scale elasticity is evaluated in two alternative ways:using either the technical efficiency model or the cost efficiency model.This evaluation becomes problematic in several situations,for example(a)when input proportions change in the long run,(b)when inputs are heterogeneous,and(c)when firms face ex-ante price uncertainty in making their production decisions.To address these situations,a scale elasticity evaluation was performed using a value-based cost efficiency model.However,this alternative value-based scale elasticity evaluation is sensitive to the uncertainty and variability underlying input and output data.Therefore,in this study,we introduce a stochastic cost-efficiency model based on chance-constrained programming to develop a value-based measure of the scale elasticity of firms facing data uncertainty.An illustrative empirical application to the Indian banking industry comprising 71 banks for eight years(1998–2005)was made to compare inferences about their efficiency and scale properties.The key findings are as follows:First,both the deterministic model and our proposed stochastic model yield distinctly different results concerning the efficiency and scale elasticity scores at various tolerance levels of chance constraints.However,both models yield the same results at a tolerance level of 0.5,implying that the deterministic model is a special case of the stochastic model in that it reveals the same efficiency and returns to scale characterizations of banks.Second,the stochastic model generates higher efficiency scores for inefficient banks than its deterministic counterpart.Third,public banks exhibit higher efficiency than private and foreign banks.Finally,public and old private banks mostly exhibit either decreasing or constant returns to scale,whereas foreign and new private banks experience either increasing or decreasing returns to scale.Although the application of our proposed stochastic model is illustrative,it can be potentially applied to all firms in the information and distribution-intensive industry with high fixed costs,which have ample potential for reaping scale and scope benefits.

我国医保基金运行效率提升的组态路径研究——基于DEA模型与模糊集定性比较分析

以我国31个省(自治区、直辖市)为研究样本,基于数据包络分析方法计算各省级医保基金运行效率,并提取区域经济水平、政府支持水平、老龄化水平、城市化水平以及卫健医疗水平等5个指标,运用模糊集定性比较分析方法揭示我国医保基金运行效率差异的条件组态和作用机制。研究发现,我国各地区呈现出两种不同的高医保基金运行效率模式,以及三种低医保基金运行效率组态路径;通过对比高、低组态的关系发现,在一定条件下政府支持水平与城市化水平是影响医保基金运行效率的核心因素。产生高、低医保基金运行效率差异的原因具有非对称性,引起低医保基金运行效率的路径并不是高医保基金运行效率路径的对立面。

基于DEA模型的山区公路视线诱导设施综合效用评价

为减少弯道段交通事故,对山区公路视线诱导设施综合效用进行研究.在弯道段单独或组合设置护栏、轮廓标、线形诱导标3类视线诱导设施,并基于驾驶模拟器、眼动仪和脑电仪获取眼动、脑电及驾驶行为数据,分析不同设置方案下驾驶人的行为特性.基于超效率BCC-DEA模型,构建山区公路弯道视线诱导设施有效性评价体系,对不同设置方案的综合效果进行评价.结果表明:视线诱导设施组合设置对驾驶行为的影响比单独设置效果更好,其中采用“线形诱导标+轮廓标”设置效果最优;视线诱导设施设置数量超过2个时会降低警示与诱导效果;指标敏感性分析表明,速度和横向位移指标分别是单独与组合设置时影响安全过弯的关键因素.

基于模糊DEMATEL-超效率DEA的可再生能源发电技术综合效益评估方法

“双碳”目标下,各类可再生能源发电技术发展迅速,综合权衡不同可再生能源发电方案的综合效益对可再生能源的优化设计具有重要意义。综合考虑经济效益、环境效益、能源效益和社会效益4个层面,提出了一种基于模糊决策试验和评价实验(decision making trial and evaluation laboratory,DEMATEL)与超效率数据包络分析(data envelopment analysis,DEA)模型的可再生能源发电技术综合效益评估方法。该方法分为投入-产出指标体系构建和综合评估2个阶段。首先,利用三角直觉模糊数处理模糊评价信息,将其与DEMATEL相结合量化各指标之间相互影响关系,基于指标间逻辑分析结果建立投入-产出评估指标体系。然后,基于超效率DEA模型对各可再生能源发电方案进行评估排序,结合投入冗余和产出不足分析结果给出各方案的针对性改善建议,以期为进一步选择和确定可再生能源产业发展战略提供参考。最后以某省10类可再生能源发电单元为研究对象,基于所提研究方法进行综合评估和分析,并与多准则妥协解排序法和熵权法进行对比分析,验证了所提方法的有效性。

基于DEA模型的河南省工业绿色转型绩效评价研究

构建了河南省工业绿色转型绩效评价的指标体系,然后选择3个投入指标和3个产出指标,用DEA方法对2023年河南省18个地区的工业绿色转型绩效进行评价分析,计算出各地区工业绿色转型的投入产出效率。结果表明该模型对河南省各地区工业绿色转型水平进行评价的可行性,数据易于获取,能够帮助政府部门制定相关政策和方针指导生产。

基于CH-DEA模型的中国制造业产业安全研究

2020年初,新冠疫情在世界范围内全面暴发,中国制造业受冲击显著,影响了中国整体经济健康稳定的发展。因此,分析中国制造业产业安全态势以应对制造业安全风险势在必行。创新地提出CH-DEA方法,并基于产业安全理论建立了制造业安全评价指标体系,从而科学合理地认识中国制造业产业安全现状。结果显示,2005~2020年期间中国制造业产业安全度总体呈现上升趋势,即制造业应对风险等突发事件能力及独立发展能力不断提高。微观障碍因素分析发现,现阶段中国制造业所面临的主要障碍是规模缩减,应利用科研创新能力提升制造业增加值。宏观环境影响因素分析显示,制造业产业安全与GDP、产品市场显著正相关。产品市场的良性竞争可以促使制造企业投入更多的资金采取规模化生产并更新设备,从而提升行业竞争力。

Efficiency assessment of coal mine safety input by data envelopment analysis

In recent years improper allocation of safety input has prevailed in coal mines in China, which resulted in the frequent accidents in coal mining operation. A comprehensive assessment of the input efficiency of coal mine safety should lead to improved efficiency in the use of funds and management resources. This helps government and enterprise managers better understand how safety inputs are used and to optimize allocation of resources. Study on coal mine＇s efficiency assessment of safety input was con- ducted in this paper. A C^2R model with non-Archimedean infinitesimal vector based on output is established after consideration of the input characteristics and the model properties. An assessment of an operating mine was done using a specific set of input and output criteria. It is found that the safety input was efficient in 2002 and 2005 and was weakly efficient in 2003. However, the efficiency was relatively low in both 2001 and 2004. The safety input resources can be optimized and adjusted by means of projection theory. Such analysis shows that, on average in 2001 and 2004, 45% of the expended funds could have been saved. Likewise, 10% of the safety management and technical staff could have been eliminated and working hours devoted to safety could have been reduced by 12%. These conditions could have Riven the same results.

Frame Work of Data Envelopment Analysis—A Model to Evaluate the Environmental Efficiency of China'S Industrial Sectors

Objective To evaluate the environmental and technical efficiencies of China＇s industrial sectors and provide appropriate advice for policy makers in the context of rapid economic growth and concurrent serious environmental damages caused by industrial pollutants. Methods A data of envelopment analysis （DEA） framework crediting both reduction of pollution outputs and expansion of good outputs was designed as a model to compute environmental efficiency of China＇s regional industrial systems. Results As shown by the geometric mean of environmental efficiency, if other inputs were made constant and good outputs were not to be improved, the air pollution outputs would have the potential to be decreased by about 60% in the whole China. Conclusion Both environmental and technical efficiencies have the potential to be greatly improved in China, which may provide some advice for policy-makers.

Robust data envelopment analysis based MCDM with the consideration of uncertain data

The application of data envelopment analysis （DEA） as a multiple criteria decision making （MCDM） technique has been gaining more and more attention in recent research. In the practice of applying DEA approach, the appearance of uncertainties on input and output data of decision making unit （DMU） might make the nominal solution infeasible and lead to the efficiency scores meaningless from practical view. This paper analyzes the impact of data uncertainty on the evaluation results of DEA, and proposes several robust DEA models based on the adaptation of recently developed robust optimization approaches, which would be immune against input and output data uncertainties. The robust DEA models developed are based on input-oriented and outputoriented CCR model, respectively, when the uncertainties appear in output data and input data separately. Furthermore, the robust DEA models could deal with random symmetric uncertainty and unknown-but-bounded uncertainty, in both of which the distributions of the random data entries are permitted to be unknown. The robust DEA models are implemented in a numerical example and the efficiency scores and rankings of these models are compared. The results indicate that the robust DEA approach could be a more reliable method for efficiency evaluation and ranking in MCDM problems.

Fuzzy data envelopment analysis approach based on sample decision making units

The conventional data envelopment analysis （DEA） measures the relative efficiencies of a set of decision making units with exact values of inputs and outputs. In real-world prob- lems, however, inputs and outputs typically have some levels of fuzziness. To analyze a decision making unit （DMU） with fuzzy input/output data, previous studies provided the fuzzy DEA model and proposed an associated evaluating approach. Nonetheless, numerous deficiencies must still be improved, including the α- cut approaches, types of fuzzy numbers, and ranking techniques. Moreover, a fuzzy sample DMU still cannot be evaluated for the Fuzzy DEA model. Therefore, this paper proposes a fuzzy DEA model based on sample decision making unit （FSDEA）. Five eval- uation approaches and the related algorithm and ranking methods are provided to test the fuzzy sample DMU of the FSDEA model. A numerical experiment is used to demonstrate and compare the results with those obtained using alternative approaches.

Data envelopment analysis procedure with two non-homogeneous DMU groups

The classic data envelopment analysis（DEA） model is used to evaluate decision-making units＇（DMUs） efficiency under the assumption that all DMUs are evaluated with the same criteria setting. Recently, new researches begin to focus on the efficiency analysis of non-homogeneous DMU arose by real practices such as the evaluation of departments in a university, where departments argue for the adoption of different criteria based on their disciplinary characteristics. A DEA procedure is proposed in this paper to address the efficiency analysis of two non-homogeneous DMU groups. Firstly, an analytical framework is established to compromise diversified input and output（IO） criteria from two nonhomogenous groups. Then, a criteria fusion operation is designed to obtain different DEA analysis strategies. Meanwhile, Friedman test is introduced to analyze the consistency of all efficiency results produced by different strategies. Next, ordered weighted averaging（OWA） operators are applied to integrate different information to reach final conclusions. Finally, a numerical example is used to illustrate the proposed method. The result indicates that the proposed method relaxes the restriction of the classical DEA model,and can provide more analytical flexibility to address different decision analysis scenarios arose from practical applications.

基于DEA的三级公立医院手术科室效率研究

目的中国公立医院进入高质量发展的新时代,各医院手术数量不断攀升,管理部门亟需引进一套科学评价手术科室资源效率的工具,促使医院充分利用现有手术资源。方法数据包络分析法(data envelopment analysis,DEA)对投入产出效率进行评价。以中国首批高质量发展试点单位北京市某三甲医院为例,投入量为手术科室的医护人数、床位数量、专用设备原值,产出量为经过CMI校正的手术量和出院人数。结果通过DEA模型分析,发现该医院只有K7、K9两个科室实现DEA有效,K1、K2纯技术效率过低,说明未充分利用现有手术资源。从规模效益上看,K3、K6处于递减状态,K7、K9不变,其余科室递增。通过Malmquist指数对技术效率和规模效率进行动态评价,结果显示,除新冠疫情影响期间外,其余期间均处于全要素增长率递增状态。文章也计算了各投入产出的松弛变量,精确得出应调整的生产资料投入值和产出工作量的数值。结论案例医院各手术科室效率参差不齐,决策层应对未充分利用手术资源的科室给予指导;对实现DEA有效的科室,在手术资源分配上给予适当倾斜。

Bootstrapping Data Envelopment Analysis of Efficiency and Productivity of County Public Hospitals in Eastern, Central, and Western China after the Public Hospital Reform

China implemented the public hospital reform in 2012. This study utilized bootstrapping data envelopment analysis（DEA） to evaluate the technical efficiency（TE） and productivity of county public hospitals in Eastern, Central, and Western China after the 2012 public hospital reform. Data from 127 county public hospitals（39, 45, and 43 in Eastern, Central, and Western China, respectively） were collected during 2012–2015. Changes of TE and productivity over time were estimated by bootstrapping DEA and bootstrapping Malmquist. The disparities in TE and productivity among public hospitals in the three regions of China were compared by Kruskal–Wallis H test and Mann–Whitney U test. The average bias-corrected TE values for the four-year period were 0.6442, 0.5785, 0.6099, and 0.6094 in Eastern, Central, and Western China, and the entire country respectively, with average non-technical efficiency, low pure technical efficiency（PTE）, and high scale efficiency found. Productivity increased by 8.12%, 0.25%, 12.11%, and 11.58% in China and its three regions during 2012–2015, and such increase in productivity resulted from progressive technological changes by 16.42%, 6.32%, 21.08%, and 21.42%, respectively. The TE and PTE of the county hospitals significantly differed among the three regions of China. Eastern and Western China showed significantly higher TE and PTE than Central China. More than 60% of county public hospitals in China and its three areas operated at decreasing return scales. There was a considerable space for TE improvement in county hospitals in China and its three regions. During 2012–2015, the hospitals experienced progressive productivity; however, the PTE changed adversely. Moreover, Central China continuously achieved a significantly lower efficiency score than Eastern and Western China. Decision makers and administrators in China should identify the causes of the observed inefficiencies and take appropriate measures to increase the efficiency of county public hospitals in the three areas of China, especially in Central China.

AIDS Treatments Efficiency Analysis Based on Cost Efficiency Data Envelopment Analysis Model

Three data envelopment analysis (DEA) models were used to analyse the relative efficiencies of four AIDS treatments in AIDS Clinical Trial Group (ACTG) Study 193A(1 309 patients in total, classified into 4 age groups). Results from the output-oriented BCC model show that Treatment 4 ( 600 mg of zidovudine plus 400 mg of didanosine plus 400 mg of nevirapine) is particularly efficient for age group 14—25, but not efficient for the older age groups; Treatment 1 (600 mg of zidovudine alternating monthly with 400 mg of didanosine)and Treatment 2 (600 mg of zidovudine plus 2.25 mg of zalcitabine) are efficient for the age groups 35—45 and 45— ; age group 25—35 does not have a particularly efficient treatment, but Treatments 1 and 2 are relatively good. The cost efficiency BCC model, which takes the treatment cost into account, gives similar results as the output-oriented model. Results from the indirect output-oriented BCC model, which allows the replacement among medicines, show that the efficiency of Treatment 2 has greatly decreased compared with that of the output-oriented model, and a set of optimal medicine amounts for different age groups is obtained.

突发公共卫生事件下各省医疗物资供给与医疗服务综合效率评价--基于DEA-RSR模型

文章对2020年新冠疫情下我国31个省份医院服务效率进行综合评价,并进行防疫前后综合效率对比,以帮助各省医疗系统提高弹性,在后疫情时代有效应对突发公共卫生事件。从提高不良输出DMU识别能力的角度,将“数据包络分析法(DEA)”和“秩和比综合比较法(RSR)”相结合,利用DEA和反向DEA模型分别从乐观和悲观的角度计算综合效率,在此基础上采用RSR法进行排序、分档。各省医院综合效率划分为四个等级,其中山东、四川、广东3个省份位于第四等级,青海和西藏位于第一等级;青海和西藏的医院在防疫期间的综合实力还有待加强,部分地区医疗资源出现挤兑,各省应调整医疗资源分配、扩大医疗服务功能。

Prediction Model of Data Envelopment Analysis with Undesirable Outputs

Data envelopment analysis (DEA) has become a standard non parametric approach to productivity analysis, especially to relative efficiency analysis of decision making units (DMUs). Extended to the prediction field, it can solve the prediction problem with multiple inputs and outputs which can not be solved easily by the regression analysis method.But the traditional DEA models can not solve the problem with undesirable outputs,so in this paper the inherent relationship between goal programming and the DEA method based on the relationship between multiple goal programming and goal programming is explored,and a mixed DEA model which can make all factors of inputs and undesirable outputs decrease in different proportions is built.And at the same time,all the factors of desirable outputs increase in different proportions.

Energy Efficiency Evaluation Based on Data Envelopment Analysis Integrated Analytic Hierarchy Process in Ethylene Production

Energy efficiency data from ethylene production equipment are of high dimension, dynamic and time sequential, so their evaluation is affected by many factors. Abnormal data from ethylene production are eliminated through consistency test, making the data consumption uniform to improve the comparability of data. Due to the limit of input and output data of decision making unit in data envelopment analysis(DEA), the energy efficiency data from the same technology in a certain year are disposed monthly using DEA. The DEA data of energy efficiency from the same technology are weighted and fused using analytic hierarchy process. The energy efficiency data from different technologies are evaluated by their relative effectiveness to find the direction of energy saving and consumption reduction.

Intelligent Digital Envelope for Distributed Cloud-Based Big Data Security

Cloud computing offers numerous web-based services.The adoption of many Cloud applications has been hindered by concerns about data security and privacy.Cloud service providers’access to private information raises more security issues.In addition,Cloud computing is incompatible with several industries,including finance and government.Public-key cryptography is frequently cited as a significant advancement in cryptography.In contrast,the Digital Envelope that will be used combines symmetric and asymmetric methods to secure sensitive data.This study aims to design a Digital Envelope for distributed Cloud-based large data security using public-key cryptography.Through strategic design,the hybrid Envelope model adequately supports enterprises delivering routine customer services via independent multi-sourced entities.Both the Cloud service provider and the consumer benefit from the proposed scheme since it results in more resilient and secure services.The suggested approach employs a secret version of the distributed equation to ensure the highest level of security and confidentiality for large amounts of data.Based on the proposed scheme,a Digital Envelope application is developed which prohibits Cloud service providers from directly accessing insufficient or encrypted data.

基于超效率DEA模型的陆军部队指挥所指挥效率评价

指挥所指挥效率评估是复杂的系统性问题,对提高部队指挥、作战、保障能力具有重要意义。主要运用数据包络的方法,不探讨指挥所的内部结构问题,通过对陆军典型部队指挥所输入输出数据进行分析,运用CCR-DEA和超效率DEA模型,对指挥效率问题进行研究排序,并针对输入数据提出改进建议,评估方法简单、可操作性强,对于陆军部队指挥所构建和指挥能力提升具有重要意义。

基于DEA模型的多院区医院临床科室运行效率分析

目的:分析多院区医院临床科室运行效率,为完善多院区协同发展机制提供参考。方法:运用数据包络分析中的BCC模型和Malmquist生产率指数模型,分析多院区医院临床科室运行效率。结果:不同院区同一临床科室综合效率存在差异;效率相对较低的科室主要在于规模不合理或组织管理水平不高;分院区相关科室技术进步明显,而组织管理和规模经济短期受到影响。结论:多院区医院要发挥优势学科辐射带动作用,提升“非有效”科室的组织管理水平,探索适宜发展的规模;结合不同院区功能定位和科室发展特征,合理规划和布局各项医疗资源,推动医院高质量发展。