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.

Analysis on regional disparity of economic development in China based on DEA

The economy of China has been developing fast after the beginning of the new century, but the 31 provinces or municipalities （excluding Hong Kong, Taiwan and Macao） develop disparately. So, finding an appropriate way to analyze and compare the economic situations of various regions is of great significance for the balanced development of the east coastal area and the hinterland. With the DEA method, on the basis of regionalism, this paper analyzes various regions of China, and gets the conclusion that the effective proportion of DEA of the coastal developed areas is relatively higher, and the extremely tittle foreign investment makes the relative efficiency of DEA of frontier areas pretty high. In addition, through the analysis parameters of the regions where DEA is relatively ineffective, this paper points out that the surplus labor force is the most influential factor, and the spare foreign investment is the main reason for the lack of efficiency of relatively developed regions.

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.

Failure Mode and Effects Analysis （FMEA） by Fuzzy Data Envelop Analysis （Fuzzy-DEA）

Failure mode and effects analysis （FMEA） offers a quick and easy way for identifying ranking-order for all failure modes in a system or a product. In FMEA the ranking methods is so called risk priority number （RPN）, which is a mathematical product of severity （S）, occurrence （0）, and detection （D）. One of major disadvantages of this ranking-order is that the failure mode with different combination of SODs may generate same RPN resulting in difficult decision-making. Another shortfall of FMEA is lacking of discerning contribution factors, which lead to insufficient information about scaling of improving effort. Through data envelopment analysis （DEA） technique and its extension, the proposed approach evolves the current rankings for failure modes by exclusively investigating SOD in lieu of RPN and to furnish with improving sca.les for SOD. The purpose of present study is to propose a state-of-the-art new approach to enhance assessment capabilities of failure mode and effects analysis （FMEA）. The paper proposes a state-of-the-art new approach, robust, structured and useful in practice, for failure analysis.

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.

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.

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.

Empirical analysis on TFP change in Chinese logistics industry： A nonparametric Malmquist index approach

Through a nonparametric Malmquist index approach, this paper analyzes the total factor productivity change in China＇s logistics industry with panel data of logistics listed corporation from 1999 to 2006, which decomposed into technical efficiency and technical progress. The result shows： （1） The average growth rate of Chinese logistics corporations from 1999 to 2006 is 0.4%, which is mainly due to the improvement of technical efficiency; （2） Technical progress which took the negative effect of the decline could not be neglected; （3） The role of technical efficiency and technical progress are different with time varying.

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.

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.

Application of a mixed DEA model to evaluate relative efficiency validity

Data envelopment analysis(DEA) model is widely used to evaluate the relative efficiency of producers. It is a kind of objective decision method with multiple indexes. However, the two basic models frequently used at present, the C2R model and the C2GS2 model have limitations when used alone,resulting in evaluations that are often unsatisfactory. In order to solve this problem, a mixed DEA model is built and is used to evaluate the validity of the business efficiency of listed companies. An explanation of how to use this mixed DEA model is offered and its feasibility is verified.

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.

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.

The Efficiency Evaluation of Commercial Banks Based on DEA/TOPSIS

This paper brings forward an efficiency evaluation method based on DEA/FOPSIS for commercial banks. To avoid the slack of output index, the difference is taken into account in the weight of different output index, mending the shortage of traditional DEA evaluation methods.

A comparative analysis of multi-output frontier models

Recently, there have been more debates on the methods of measuring efficiency. The main objective of this paper is to make a sensitivity analysis for different frontier models and compare the results obtained from the different methods of estimating multi-output frontier for a specific application. The methods include stochastic distance function frontier, stochastic ray frontier, and data envelopment analysis. The stochastic frontier regressions with and without the inefficiency effects model are also com-pared and tested. The results indicate that there are significant correlations between the results obtained from the alternative estimation methods.

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.