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.

Discriminating Among Relatively Efficient Units in Data Envelopment Analysis: A Comparison of Alternative Methods and Some Extensions

This paper concentrates on methods for comparing activity units found relatively efficient by data envelopment analysis (DEA). The use of the basic DEA models does not provide direct information regarding the performance of such units. The paper provides a systematic framework of alternative ways for ranking DEA-efficient units. The framework contains criteria derived as by-products of the basic DEA models and also criteria derived from complementary DEA analysis that needs to be carried out. The proposed framework is applied to rank a set of relatively efficient restaurants on the basis of their market efficiency.

A New Approach for Ranking Efficient Units in Data Envelopment Analysis and Application to a Sample of Vietnamese Agricultural Bank Branches

This paper proposes a new approach for ranking efficiency units in data envelopment analysis as a modification of the super-efficiency models developed by Tone [1]. The new approach based on slacks-based measure of efficiency (SBM) for dealing with objective function used to classify all of the decision-making units allows the ranking of all inefficient DMUs and overcomes the disadvantages of infeasibility. This method also is applied to rank super-efficient scores for the sample of 145 agricultural bank branches in Viet Nam during 2007-2010. We then compare the estimated results from the new SCI model and the exsisting SBM model by using some statistical tests.

Assessment of Dry Port Efficiency in Africa Using Data Envelopment Analysis

This work involves the evaluation of dry port competitiveness through analysis of efficiencies for selected dry ports in Africa. Five dry ports were selected and analysis carried out over a period of four years. The dry ports considered were Mojo and Kality in Ethiopia, Mombasa in Kenya, Isaka in Tanzania and Casablanca in Casablanca, Morocco. Data Envelopment Analysis (DEA) was applied for this work. Container throughputs for the various ports under consideration were used as the output variable for the data analysis model, while the number of reach stackers, the number of tractors, the number of forklifts and the size of the dry port were used as the input variables. From the results, the Mombasa dry port was found to be the most efficient with an average score of approximately 1 over the period under consideration. Casablanca was the second efficient dry port with an average score of 0.762, while Isaka was the least efficient with an average score of 0.142. This research is significant since the African countries have embraced the dry port concept, as witnessed in the huge investments in this sector, and would serve to highlight areas that need improvement for the few existing dry port facilities, most of which are undergoing expansion as well as modernization.

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.

The Study of the Operating Performance of Marine Industry in the Blue Economic Zone: An Empirical Analysis Based on DEA and Tobit Model

The marine industry plays an important role in promoting the development of the blue economic zone,and the study of the operating performance of marine industry is of important practical significance. Using DEA method,this article measures the operating performance of marine industry in the blue economic zone. On this basis,using Tobit model,it analyzes the factors influencing the operating performance of marine industry. The results show that the industries of high carbon emission performance are basically the industries of high energy consumption,high emission and high pollution; the level of economic development and the number of important technological achievements can both significantly increase the pure technical efficiency; the sustainable environmental carrying capacity and the number of employees are conducive to improving the technological progress index and overall efficiency; the level of social infrastructure plays a role in promoting the overall efficiency,but the role is not obvious.

Analysis on Technical Efficiency of Rice Farms and Its Influencing Factors in South-western of Niger

The present study focused on analyzing the technical efficiency office farms in southwest of Niger. The data from January to March 2015 survey of 148 ms in three districts of south-western of Niger were analyzed by using DEA-Tobit two-step method. In the f＇ust step, data envelopment analysis （DEA） was applied to estimate technical, pure technical and scale efficiency. In the second step, Tobit regression was used to identify factors affecting technical efficiency. The results showed that rice producers in southwest of Niger could reduce their inputs by 52% and still produce the same level of rice output. The Tobit regression showed that factors, such as farm size, experience in rice farming, membership of cooperative, main occupation and land ownership had a direct impact on technical efficiency.

A New Stochastic Model for Classifying Flexible Measures in Data Envelopment Analysis

The way to deal with flexible data from their stochastic presence point of view as output or input in the evaluation of efficiency of the decision-making units(DMUs)motivates new perspectives in modeling and solving data envelopment analysis(DEA)in the presence of flexible variables.Because the orientation of flexible data is not pre-determined,and because the number of DMUs is fixed and all the DMUs are independent,flexible data can be treated as random variable in terms of both input and output selection.As a result,the selection of flexible variable as input or output for n DMUs can be regarded as binary random variable.Assuming the randomness of choosing flexible data as input or output,we deal with DEA models in the presence of flexible data whose input or output orientation determines a binomial distribution function.This study provides a new insight to classify flexible variable and investigates the input or output status of a variable using a stochastic model.The proposed model obviates the problems caused by the use of the large M number and using its different values in previous models.In addition,it can obtain the most appropriate efficiency value for decision-making units by assigning the chance of choosing the orientation of flexible variable to the model itself.The proposed method is compared with other available methods by employing numerical and empirical examples.

Efficiency of Moroccan Seaports: Application of DEA Using Window Analysis

The efficiency of 8 seaports in the Kingdom of Morocco region was evaluated. Two associated studies were conducted based on data collected for 4 years (2014-2017), Standard Data Envelopment Analysis (DEA) method was used in the first analysis through CCR and BCC models, and thus a scale of efficiency analysis was used in a second analysis. By using both methods, enhanced insight into the efficiency situation is collected, proving subsequently that a majority of the container ports and terminals in the Kingdom of Morocco are found to be technically inefficient. The research concludes through returns to scale method how port resources should be utilized in the aim to impulse inefficient ports perform better.

Application of Integrated Multiple Criteria Data Envelopment Analysis to Humanitarian Logistics Network Design

This paper considers a humanitarian logistics network(HTLN)design problem,including the emergency relief facilities(ERFs)location-allocation decision for the efficient distribution of emergency supplies from the ERFs to the affected areas.A goal programming(GP)approach is applied to consider the multiple objectives simultaneously.Solving the GP model with a given weight assigned to each goal yields a single HTLN scheme,so there will be various schemes available by solving the GP with multiple values of the weights.For evaluating these schemes and identifying the most efficient one,we apply the data envelopment analysis(DEA)methods considering each scheme as a decision-making unit(DMU).Since the classical DEA(C-DEA)intrinsically aims to identify efficient DMUs and the efficient frontier,the use of C-DEA may not lead to a full ranking in many situations.There are several independent evaluation approaches to increasing discriminating power.Among them,this study integrates the multiple criteria DEA(MC-DEA)with the following three DEA methods,(i)stratification DEA(S^DEA),(ii)cross-efficiency DEA(CE-DEA),and(iii)super-efficiency DEA(SE-DEA),to make the most use of each method's strengths.Through a case study of designing the HTLN system for South Carolina,the procedure of implementing the integrated multiple criteria DEA(IMC-DEA)method is demonstrated.It is observed that the IMCDEA method performs well in terms of designing the HTLN system and would help the decision-makers consider more efficient options and make a final decision.

基于SE-DEA模型与Malmquist指数的城市公交企业运营绩效评价

提出基于超效率数据包络分析(DEA)模型和Malmquist指数的公共交通企业运营绩效组合评价方法,系统分析公共交通运营状态,为科学评价城市公交运营绩效,改善公交服务水平提供决策依据。以长三角地区13家公交企业为研究对象,选取运营车辆数、从业职工数和百公里油耗为投入指标,选取车辆行驶公里数和乘客运载人数为产出指标,基于超效率-数据包络分析(SE-DEA)模型与Malmquist指数从生产效率、服务效率和综合效率三方面对公交企业运营绩效进行综合评价。结果表明:公交企业运营绩效波动较大,且呈现下降趋势;技术进步缓慢和规模效率不佳是造成运营绩效下降的主要原因。根据评价结果,从企业运营和行业监管2个角度提出可行的建议,以促进公交行业能够健康有序地发展。

用SE-DEA模型研究决策单元分类

通过一种改进的数据包络分析(DEA)模型———SE DEA模型,可以对决策单元进行分类,但在可变规模收益(VRS)条件下,这种模型可能不存在可行解.论文讨论了基于VRS的SE DEA模型不可行的充分必要条件,分析了有效决策单元的超有效和强超有效特性,实现对有效决策单元的进一步分类.最后给出了用基于VRS的SE DEA模型对决策单元进行分类的方法步骤,该分类方法改进和改善了传统的决策单元分类,可为决策者提供更加完备的决策信息.

基于SE-DEA的电力企业效率评估

针对传统数据包络分析(DEA)模型不能对有效决策单元做进一步比较的现实情况,文章引入了重新定义生产可能集的SE-DEA模型,创造性地克服了传统模型的这一缺点,实现了对所有决策单元的充分评价与排序。接着以沪深股市火力发电上市公司为例进行实证,在论证它们符合SE-DEA模型应用假设条件的基础上,验证了该模型在评价企业效率方面的有效性。

Performance Evaluation of Public Bus Transportation by Using DEA Models and Shannon’s Entropy:An Example From a Company in a Large City of China

The purpose of this paper is to assess the operational efficiency of a public bus transportation via a case study from a company in a large city of China by using data envelopment analysis(DEA)model and Shannon’s entropy.This company operates 37 main routes on the backbone roads.Thus,it plays a significant role in public transportation in the city.According to bus industry norms,an efficiency evaluation index system is constructed from the perspective of both company operations and passenger demands.For passenger satisfaction,passenger waiting time and passenger-crowding degree are considered,and they are undesirable indicators.To describe such indicators,a superefficient DEA model is constructed.With this model,by using actual data,efficiency is evaluated for each bus route.Results show that the DEA model with Shannon’s entropy being combined achieves more reasonable results.Also,sensitivity analysis is presented.Therefore,the results are meaningful for the company to improve its operations and management.

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.

SE-DEA-SVM evaluation method of ECM operational disposition scheme

Operational disposition of electronic countermeasures(ECM)is a hot topic in modern warfare research.Through fully analyzing the characteristics and shortcomings of the traditional operational disposition scheme,a super-efficient data envelopment analysis support vector machine(SE-DEA-SVM)method for evaluating the operational configuration scheme of ECM is proposed.Firstly,considering the subjective and objective factors affecting the operational disposition of ECM,the index system of operational disposition scheme is established,and we explain the solution method of terminal indexs.Secondly,the evaluation and algorithm process of SE-DEA-SVM evaluation method are introduced.In this method,the super-efficient data envelopment analysis(SE-DEA)model is used to calculate the weight of index system,and the support vector machine(SVM)method combined with the training samples of evaluation index is used to obtain the input-output model of evaluation value of combat configuration.Finally,by an example(obtaining five schemes),we verify the SE-DEA-SVM evaluation method and analyze the results.The efficiency analysis,comparison analysis,and error analysis of this method are carried out.The results show that this method is more suitable for military evaluation with small samples,and it has high efficiency,applicability,and popularization value.

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.

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.

Discussion on the business performance of life insurance industries in Taiwan and China's Mainland Application of Metafrontier model

When using the Data Development Analysis method for analyzing the efficiency of different firms, it is common to put all similar DMU together for measurement in order to figure out the efficiency values of various DMU. However, such an analysis may easily neglect the source property of an individual DMU, meaning that the differences among various DMUs derive from different environmental backgrounds, e.g. environment variables such as economic civilization, laws and regulations, and political backgrounds. Applying the Metafrontier model can overcome the barriers resulting from the environment variables, and it can analyze and measure the differences among various DMUs which have different source properties. It can also be used for measuring the difference between each group of DMU and all DMUs. Therefore, this study adopts the DEA method, assuming variable returns to scale to evaluate and comparatively analyze the business performance of life insurance industries in Taiwan and China's Mainland based on ＂BBC input orientation＂. When evaluating the business performance, the operating management echelon is affected by uncontrollable external environment variables. Thus, this study applies the Four-Stage Data Envelopment Analysis to discuss the impact of environment variables on business performance and re-measures the business efficiency of life insurance industries in Taiwan and China's Mainland after adjusting the input variables. The demonstration period adopted by this study is from 2003 to 2005, and the research subject comprises 43 companies in Taiwan and China's Mainland, among which, there are 19 companies in Taiwan and 24 companies in China's Mainland, and there are 129 sets of sample data. It is assumed that the discount rate is ？ （）, is set as 3% in this paper）, and figured out the change of each life insurance company in technical efficiency in the inter-period accumulative years from 2003 to 2005.

公路隧道入口区域驾驶人吸睛效应综合评价

为全面和系统评价公路隧道入口区域视觉吸引对驾驶人吸睛效应视觉表现的影响,本文招募30名被试开展自然驾驶实验,采集驾驶人在公路隧道入口区域不同视觉吸引条件下的眼动数据,基于因子分析法选取驾驶人吸睛效应敏感评价指标,并分别构建线性混合效应模型和数据包络分析模型,识别和探究公路隧道入口区域视觉吸引对驾驶人吸睛效应视觉表现的影响特征和作用机理。结果表明:因子分析结果显示,驾驶人吸睛效应敏感视觉指标为注视持续时间、瞳孔直径、扫视持续时间和扫视幅度;公路隧道入口区域不同视觉吸引条件对驾驶人吸睛效应的视觉表现和综合效率有显著影响,且受驾驶人年龄和驾驶经验的个体特质因素影响显著,而性别因素对其没有显著性影响;视觉吸引的存在均会不同程度地损害驾驶人的正常视觉绩效,降低其合理有效性;提示标语视觉吸引条件下,驾驶人的视觉注意水平最差,视觉认知负荷程度最高,吸睛效应的负面影响最大,广告牌条件次之。