Evaluation of Energy Efficiency and Analysis of Influencing Factors of Company CW’s Manufacturing Workshops

In this work,the Slacks-Based Measure(SBM)model within Data Envelopment Analysis was employed to establish a set of indicators for evaluating the energy efficiency of manufacturing workshops.The energy efficiency of 12 Company CW’s manufacturing workshops from 2016 to 2022 was assessed.The findings indicated that aside from a few workshops operating at the production frontier,the rest exhibit significant fluctuations in energy efficiency and generally low energy efficiency.Subsequently,a combined GRA-Tobit analysis model was introduced to identify factors influencing the energy efficiency of Company CW’s manufacturing workshops.Regression analysis revealed that technological investments,employee quality,workshop production scale,investment in clean energy,and the level of pollution control all significantly impact the energy efficiency of Company CW’s manufacturing workshops.By evaluating the energy efficiency of Company CW’s manufacturing workshops and studying their influencing factors,this research aids company managers in understanding the energy efficiency of the manufacturing process.It optimizes the combination of various production elements,thereby offering effective guidance for improving the energy efficiency issues of the company’s manufacturing workshops,which can contribute to enhancing the corporation’s overall energy efficiency.

基于DEA方法的江苏省制造业上市企业创新绩效研究

基于道格拉斯生产函数,构建了企业创新绩效评价指标体系,运用DEA-CCR、DEA-BCC、DEA-Malmquist模型测算了2018—2020年169家江苏省制造业上市企业静态效率和动态效率。研究表明,江苏省制造业上市企业研发投入呈现逐年递增趋势,但创新绩效整体没有达到最优状态,主要是由于纯技术效率较低所致,需要提升资源配置效率;且受疫情影响创新绩效整体上经历了一个从增长到衰退的过程,相对来说企业技术进步率大于技术效率变化率。

Cost Containment of Total Knee Arthroplasty in the US: DEA Analysis on Regional Cost and Clinical Comparison between 2010 and 2013

The purpose of this research is to evaluate clinical and cost effectiveness of total knee replacement surgery (TKA) for adults hospitalized in the United States between 2010 and 2013. We tried to answer the question that whether lower length of stay and higher utilization of post-op facilities would be helpful to control the overall costs. Using the National Hospital Discharge Survey (NHDS) database and cost data from Blue Cross Blue shield, this study seeks to identify which U.S. region renders the highest quality patient care during a three-year span of 2008-2010. Using length of stay and discharge disposition (2010) as input factors, and regional TKA costs (2013) as output factors, Data Envelopment Analysis (DEA), a non-parametric method, illustrated the efficiency ranking of four regions in the US on TKA expenditures. The result shows the West is the most efficient region on controlling the overall cost by shrinking the length of stay and increasing the utilization of short-term/long-term care facilities.

New approach to determine common weights in DEA efficiency evaluation model

Data envelopment analysis（DEA） is a mathematical programming approach to appraise the relative efficiencies of peer decision-making unit（DMU）,which is widely used in ranking DMUs.However,almost all DEA-related ranking approaches are based on the self-evaluation efficiencies.In other words,each DMU chooses the weights it prefers to most,so the resulted efficiencies are not suitable to be used as ranking criteria.Therefore this paper proposes a new approach to determine a bundle of common weights in DEA efficiency evaluation model by introducing a multi-objective integer programming.The paper also gives the solving process of this multi-objective integer programming,and the solution is proven a Pareto efficient solution.The solving process ensures that the obtained common weight bundle is acceptable by a great number of DMUs.Finally a numeral example is given to demonstrate the approach.

PERFORMANCE EVALUATION METHOD FOR BUSINESS PROCESS OF MACHINERY MANUFACTURER BASED ON DEA/AHP HYBRID MODEL

A set of indices for performance evaluation for business processes with multiple inputs and multiple outputs is proposed, which are found in machinery manufacturers. Based on the traditional methods of data envelopment analysis （DEA） and analytical hierarchical process （AHP）, a hybrid model called DEA/AHP model is proposed to deal with the evaluation of business process performance. With the proposed method, the DEA is firstly used to develop a pairwise comparison matrix, and then the AHP is applied to evaluate the performance of business process using the pairwise comparison matrix. The significant advantage of this hybrid model is the use of objective data instead of subjective human judgment for performance evaluation. In the case study, a project of business process reengineering （BPR） with a hydraulic machinery manufacturer is used to demonstrate the effectiveness of the DEA/AHP model.

Integration of α-fairness with DEA based resource allocation model

How to allocate a resource efficiently and fairly attracts the attention of both researchers and practitioners. Data envelopment analysis（DEA） has been brought to bear on its solution. The existing literature applies Gini coefficient to measure the fairness in the resource allocation process. However, the Gini coefficient is inapplicable in many applications. This paper proposes a novel centralized resource allocation model based on DEA that considers both the efficiency and the fairness. This paper adopts a notion of fairness, namely α-fairness that is well studied in welfare economics and is of practical significance. The new model integratesα-fairness with DEA to support resource allocation decisions. It aids decision makers in making a trade-off between the efficiency and the fairness. An illustrative application is used to validate the proposed approach.

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.

Prediction of efficient outputs based on GM(1,N) model and weak DEA efficiency

This paper expresses the efficient outputs of decisionmaking unit（DMU） as the sum of ＂average outputs＂ forecasted by a GM（1,N） model and ＂increased outputs＂ which reflect the difficulty to realize efficient outputs.The increased outputs are solved by linear programming using data envelopment analysis efficiency theories,wherein a new sample is introduced whose inputs are equal to the budget in the issue No.n ＋ 1 and outputs are forecasted by the GM（1,N） model.The shortcoming in the existing methods that the forecasted efficient outputs may be less than the possible actual outputs according to developing trends of input-output rate in the periods of pre-n is overcome.The new prediction method provides decision-makers with more decisionmaking information,and the initial conditions are easy to be given.

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.

The Treatment of Non-zero Slacks in Data Envelopment Analysis

The paper studies the non-zero slacks in data envelopment analysis. A procedure is developed for the treatment of non-zero slacks. DEA projections can be done just in one step.

Comparative Water Efficiency Analysis of Sole and Multiple Cropping Systems under Tunnel Farming in Punjab-Pakistan

Water scarcity is the growing concern of present times, requiring its efficient utilization deemed as necessity. Rapidly growing population has significantly exerted pressure on its demand, in Pakistan. In order to fulfill it, all factors of production are required to be used in the possibly most efficient way. Good quality and quantity of water are the growing concerns of producers in Pakistan and around the globe. The efficient water utilization is crucial to optimize the farm returns under the selected sole and multiple cropping systems. This study considered the water efficiency analysis of multiple and sole cropping systems, with the aim of finding out cropping patterns more efficient in terms of water utilization in Pakistan. In order to estimate the water efficiency analysis, the Data Envelopment Analysis (DEA) is run to find out the water efficient cropping systems among sole and multiple cropping systems. The Tobit analysis is also used to find out the factors affecting the water efficiency of selected farms in the study area. The results of the study report an inefficient water usage in terms of irrigation, the inefficient use of water instigates the wastage of one of the most important as well as scarce farm inputs especially water, in case of multiple cropping system. Around 51% and 13% of water inefficiency are present under multiple and sole cropping systems, respectively. Basin irrigation is the method for irrigation, used by the farmers of the study area approximating to be 95% - 97%. It is one of the most conventional and least efficient methods of irrigation. Only 2.67 and 4.67 percent of farms were using the Furrow irrigation method, which is way more efficient and steady as compared to Basin irrigation method, respectively. It appears as a requirement that the most efficient methods regarding water application in Pakistan should be recognized. Lack of management in water application on both selected cropping systems resulted in over utilization of water and depletion of one of the fundamental natural resource. In order to overcome the inefficiency in water management, farmers’ farming knowledge, adoption of new irrigation techniques, efficient application of inputs is needed.

Sources of China's Economic Growth:An Analysis Based on Nonparametric Accounting Method

This paper improves the slacks-based method for estimating inefficiency,derives the criteria for the selection of the weights of output and input inefficiencies in the objective function,and creates a new nonparametric method for accounting economic growth.Based on this method,the paper estimates the sources of China s economic growth from 1978 to 2013.Our findings suggest that factor input and especially capital is a major source of economic growth for China as a whole and its major regions,and that economic growth in recent years is increasingly dependent on capital.For a rather long period of time before 2005,China s northeast,central and western regions lagged behind the eastern region in terms of economic growth,and TFP and factor input are major reasons behind such regional growth disparities.Although other regions have narrowed their disparities with and even overtaken the eastern region in terms of economic growth,the key driver is the rapid increase in the contribution of factor input.Advanced technologies of eastern region should be utilized to promote TFP progress in other regions,which is vital to economic growth in these regions and China as a whole.

Cross-efficiency DEA model-based evaluation of allocative efficiency of rural information resources in Jiangsu Province, China

Purpose: This paper aims to compare and rank the allocative efficiency of information resources in rural areas by taking 13 rural areas in Jiangsu Province, China as the research sample.Design/methodology/approach: We designed input and output indicators for allocation of rural information resources and conducted the quantitative evaluation of allocative efficiency of rural information resources based on cross-efficiency model in combination with the classical CCR model in data envelopment analysis(DEA).Findings: Cross-efficiency DEA model can be used for our research with the objective to evaluate quantitatively and objectively whether the allocation of information resources in various rural areas is reasonable and whether the output is commensurate with the input.Research limitations: We have to give up using some indicators because of limited data availability. There is a need to further improve the cross-efficiency DEA model because it cannot identify the specific factors influencing the efficiency of decision-making units(DMUs).Practical implications: The evaluation results will help us understand the present allocative efficiency levels of information resources in various rural areas so as to provide a decisionmaking basis for formulation of the policies aimed at promoting the circulation of information resources in rural areas.Originality/value: Little or no research has been published about the allocative efficiency of rural information resources. The value of this research lies in its focus on studying rural informatization from the perspective of allocative efficiency of rural information resources and in the application of cross-efficiency DEA model to evaluate allocative efficiency of rural information resources as well.

基本公共卫生服务效率及其影响因素

目的基于2017年武汉市13个地区基层医疗卫生机构的横断面数据,分析武汉市基本公共卫生服务效率及其主要影响因素。方法采用松弛测度(slack-based-measure,SBM)-超效率数据包络分析(data envelopment analysis,DEA)模型,对武汉市基本公共卫生服务效率进行测算,通过Tobit回归分析进一步探讨其影响因素。结果2017年武汉市13个地区基本公共卫生服务的超效率、纯技术效率、规模效率几何均数分别为1.073、1.213、0.884。其中76.9%的地区为DEA有效,若非DEA有效地区能达到DEA有效,全市可少开办11家基层医疗卫生机构、减少1451张病床、节省6983万元基本公共卫生服务补助经费。60岁及以上老年人比例、平均期望寿命、每千人口卫生技术人员数、每千人口床位数对武汉市基本公共卫生服务效率的影响具有统计学意义。结论武汉市基本公共卫生服务效率地区差异较大,规模效率是制约基本公共卫生服务效率的关键因素。60岁及以上老年人比例越高、平均期望寿命越长、每千人口卫生技术人员数越多,基本公共卫生服务效率越低;每千人口床位数越多,基本公共服务效率越高。针对这些因素,需提高老年人健康管理水平,优化机构人员配置,合理调整机构规模,重视基本公共卫生服务的公益性。

京津冀中医药卫生资源配置现状及效率

目的了解实行京津冀一体化发展以来京津冀中医药卫生资源的配置情况,为京津冀中医药协同发展提供参考建议。方法对2015—2018年京津冀中医药卫生资源数据进行描述性分析,用数据包络分析评价2018年京津冀中医药卫生资源的配置效率。结果北京市每万常住人口中医医疗卫生机构数、每万常住人口卫生技术人员数、每万常住人口实有床位数均处于三地最高水平。河北省中医药卫生资源的增幅较大,中医医院的服务量增长较快。北京市的中医药卫生资源配置弱有效,天津市、河北省的中医药卫生资源配置无效。结论北京市的中医药卫生资源相对丰富。河北省的中医药卫生资源及中医药卫生服务发展较好。在京津冀中医药协同发展的背景下,应将北京市的非首都功能向河北省疏解,河北省应加强中医药人才建设。

2010—2018 年长三角地区医疗服务效率比较

目的分析2010—2018年长三角地区医疗服务效率,为促进各地优化卫生资源配置、提高卫生服务水平提供参考。方法通过定性和定量相结合的研究方法,建立数据包络分析模型,对医疗服务效率进行统计描述和模型分析,并结合文献综述和专家访谈,阐释效率分析结果。结果长三角地区各地医疗服务效率特征各异。上海市业务效率较高,浙江省业务效率发展快速,江苏省效率其次,安徽省较低。应将各地的医疗服务效率分析结果置于各自卫生发展的背景条件、资源禀赋和战略定位下进行分析。结论在当前经济新常态、防控新型冠状病毒肺炎疫情的环境下,控制卫生费用的不合理增长显得更加迫切和必要。建议合理配置资源,提高医疗资源使用效率,进一步控制医疗费用上升。要强化政府在公立医院补偿机制中应该发挥的作用,鼓励和引导多元主体参与医疗服务提供,满足群众多层次、多样化的健康需求。此外,还应促进区域协同发展,推进区域健康一体化建设。

县域医疗共同体建设背景下的乡镇卫生院效率

目的了解我国乡镇卫生院的运行现状及县域医疗共同体建设前后的效率变化,为政府相关部门决策提供参考依据。方法用数据包络分析和Malmquist指数,分析我国29个省(自治区、直辖市)的乡镇卫生院的投入产出效率。结果29个省(自治区、直辖市)的乡镇卫生院的技术效率均数为0.773,最高为1.000,最低为0.384,效率的地区差异较明显。2016—2018年,除纯技术效率略有上升外,全要素生产率、技术效率、技术均有所下降。乡镇卫生院整体运行效率较低,产出不足与投入冗余是主要原因,规模效率和技术制约了乡镇卫生院生产率的增长。结论建议:因地制宜,优化卫生资源配置;发挥政府主导作用,完善医疗共同体配套政策;引导居民转变就医理念,合理就医。

Full ranking procedure based on best and worst frontiers

In the traditional data envelopment analysis （DEA） structure, the efficiency score for one decision making unit （DMU） is calculated by measuring the distance of the evaluated DMU to the best practice frontier. Recent researches have provided the reasonability of considering the worst practice frontier as a supple- ment to the traditional DEA techniques. The existing researches take only one type of frontier into account, and they cannot com- pare the evaluated DMU with both the best and the worst perform- ing DMUs. A DEA-based procedure is developed to consider the best and the worst frontiers in the same scenario where the ratio of two distances （RDS） measure is proposed. The principal appli- cation of this approach is for ranking, and, as a complement tool, for performance evaluation. The proposed approach can be used in a wide range of applications such as the performance evaluation of employees and others. Finally, a bookstore data set is used to illustrate the proposed approach.

AN EXTENDED AGGREGATED RATIO ANALYSIS IN DEA

Data Envelopment Analysis（DEA） and Ratio Analysis（RA） are two widely used methods for measuring units＇ productivity and any other criteria that could be assessed based on the available input and output variables.A number of researchers have studied DEA and RA and noted the positive and negative differences between them.Aggregated ratio analysis（ARA） model,which provide an important linkage between DEA and RA theory,is equivalent to the CCR DEA model,and this equivalence property offers a great deal of opportunities for DEA to be interpreted and applied in different ways.This paper extends the results of ARA model and proposes an extended aggregated ratio analysis（EARA） model,similar as the development from CCR model to BCC model in DEA context.The proposed model can offer an insight into the characteristic of returns to scale,playing the corresponding role as BCC model does.The numerical example is revisited in the paper and the results are compared.

Ranking approach of cross-efficiency based on improved TOPSIS technique

The cross-efficiency evaluation method is reviewed which is developed as a data envelopment analysis （DEA） extensive tool. The cross-efficiency evaluation method is utilized to identify the decision making unit （DMU） with the best practice and to rank the DMUs by their respective cross-efficiency scores. The main drawbacks of the cross-efficiency evaluation method when the ultimate average cross-efficiency scores are used to evalu- ate and rank the DMUs are also pointed out. With the research gap, an improved technique for order preference by similarity to ideal solution （TOPSIS） is introduced to rank the crossfficiency by eliminating the average assumption. Finally, an empirical example is illustrated to examine the validity of the proposed method.