Application Of DEA Research Articles

Quantitative evaluation of nation stability

This paper quantitatively evaluates nation stability, defined as the state of a country's social and economic system as measured by multiple evaluation indicators, and observes its transitions. Data Envelopment Analysis/Malmquist Index (DEA/MI) methodology is applied to the panel data for 97 countries for the period 1981–2004, although the DEA application is totally different from the DEA efficiency/productivity analysis. This analysis includes a “unified” country (Germany) and “split” countries (former Soviet Union, Czechoslovakia, and Yugoslavia). Using the novel panel-data handling proposed in this study, we demonstrate shifts in stability before/after the unification or split. The stability of split countries fell by 50% or more, showing that they were extremely unstable before the split. The use of lower-bound DEA together with ordinary DEA enables a country's stability to be evaluated in terms of both negative and positive aspects.

Modeling and notation of DEA with strong and weak disposable outputs

Recent articles published in Health Care Management Science have described DEA applications under the assumption of strong and weak disposable outputs. As we confidently assume that these papers include some methodical deficiencies, we aim to illustrate a revised approach.

Two-stage evaluation of bank branch efficiency using data envelopment analysis

There are two key motivations for this paper: (1) the need to respond to the often observed rejections of efficiency studies’ results by management as they claim that a single-perspective evaluation cannot fully reflect the operating units’ multi-function nature; and (2) a detailed bank branch performance assessment that is acceptable to both line managers and senior executives is still needed. In this context, a two-stage Data Envelopment Analysis approach is developed for simultaneously benchmarking the performance of operating units along different dimensions (for line managers) and a modified Slacks-Based Measure model is applied for the first time to aggregate the obtained efficiency scores from stage one and generate a composite performance index for each unit. This approach is illustrated by using the data from a major Canadian bank with 816 branches operating across the nation. Three important branch performance dimensions are evaluated: Production, Profitability, and Intermediation. This approach improves the reality of the performance assessment method and enables branch managers to clearly identify the strengths and weaknesses in their operations. Branch scale efficiency and the impacts of geographic location and market size on branch performance are also investigated. This multi-dimensional performance evaluation approach may improve management acceptance of the practical applications of DEA in real businesses.

A Shapley value index on the importance of variables in DEA models

In many DEA applications, decision makers always confront with a problem, which is how to determine the importance of each input or output variable in performance measurement? This paper approaches this problem from a cooperative game point of view. First, we have defined an efficiency change ratio (ECR) to calculate the marginal impact of each variable on the efficiency evaluation, which compares the efficiency scores of the two radial DEA models differing in whether the given variable is included. Based upon a simple data example, this paper finds that it is not suitable to use ECR to determine the importance of each variable, for the value of the variable’s ECR is very sensitive to the selected input set and output set. Then, this paper has defined a characteristic function of each coalition (input or output variable set) based upon ECR. The characteristic function is super-additive. Thus, we use Shapley value index as the solution of the cooperative game to determine the importance of the variable under evaluation. Finally, the proposed approach has been applied to a data set from prior DEA literature.

Assessment of productivity of hospitals in Botswana: a DEA application.

BackgroundBotswana national health policy states that the Ministry of Health shall from time to time review and revise its organization and management structures to respond to new developments and challenges in order to achieve and sustain a high level of efficiency in the provision of health care. Even though the government clearly views assuring efficiency in the health sector as one of its leadership and governance responsibilities, to date no study has been undertaken to measure the technical efficiency of hospitals which consume the majority of health sector resources. The specific objectives of this study were to quantify the technical and scale efficiency of hospitals in Botswana, and to evaluate changes in productivity over a three year period in order to analyze changes in efficiency and technology use.MethodsDEAP software was used to analyze technical efficiency along with the DEA-based Malmquist productivity index which was applied to a sample of 21 non-teaching hospitals in the Republic of Botswana over a period of three years (2006 to 2008).ResultsThe analysis revealed that 16 (76.2 percent), 16 (76.2 percent) and 13 (61.9 percent) of the 21 hospitals were run inefficiently in 2006, 2007 and 2008, with average variable returns to scale (VRS) technical efficiency scores of 70.4 percent, 74.2 percent and 76.3 percent respectively. On average, Malmquist Total Factor Productivity (MTFP) decreased by 1.5 percent. Whilst hospital efficiency increased by 3.1 percent, technical change (innovation) regressed by 4.5 percent. Efficiency change was thus attributed to an improvement in pure efficiency of 4.2 percent and a decline in scale efficiency of 1 percent. The MTFP change was the highest in 2008 (MTFP = 1.008) and the lowest in 2007 (MTFP = 0.963).ConclusionsThe results indicate significant inefficiencies within the sample for the years under study. In 2008, taken together, the inefficient hospitals would have needed to increase the number of outpatient visits by 117627 (18 percent) and inpatient days by 49415 (13 percent) in order to reach full efficiency. Alternatively, inefficiencies could have been reduced by transferring 264 clinical staff and 39 beds to health clinics, health posts and mobile posts. The transfer of excess clinical staff to those facilities which are closest to the communities may also contribute to accelerating progress towards the Millennium Development Goals related to child and maternal health.Nine (57.1 percent) of the 21 hospitals experienced MTFP deterioration during the three years. We found the sources of inefficiencies to be either adverse change in pure efficiency, scale efficiency and/or technical efficiency.In line with the report Health financing: A strategy for the African Region, which was adopted by the Fifty-sixth WHO Regional Committee for Africa, it might be helpful for Botswana to consider institutionalizing efficiency monitoring of health facilities within health management information systems.

Double Perspective Data Envelopment Analysis: One Approach to Estimate the “LOOP” Arbitrage

This paper introduces the application of real estate pricing DP DEA - Double Perspective Data - Envelopment Analysis to solve the LOOP (Law of One Price) arbitrage. A general equilibrium model of real estate values was developed to analyze price variation over digital map, and applied to the urban area of the city of Joinville. The power of real estate locational value assessment using DP-DEA is then compared with the usual MRA - Multiple Regression Analysis using a real case of land data. All computational generated results and data were subsequently geocoded on a GIS - Geographic Information System. The computational generated Price line Map is easily visualized in a real estate value chart that can enhance accuracy when compared to a conventional methodology, also a tool for immediate updates and testing the effects of new developments over urban areas.

Análise do desempenho socioambiental no setor siderúrgico brasileiro

This paper has the main aim to verify, through the application of DEA, the relationship between investment capacity and social and environmental benefits, in a way that the higher the benefits to a lower investment capacity, the better will be the efficiency and, therefore, the company social and environmental performance. In other words, we try to verify that the efficiency of each company, for the years 2003, 2004 and 2005, to convert the investment capacity (input), as measured by revenue or operational income, in social and environmental benefits (outputs), as measured by internal and external social indicators and by environmental indicators obtained in the Social Report - IBASE model, of the following companies: Acesita, Belgo, CSN, CST, Gerdau e USIMINAS. The study results of six major siderurgical companies from Brazil show that Gerdau (top benchmark) and CSN are the best ones and Acesita is the worst in terms of social and environmental performance. Besides, the environmental investment is the variable which needs more increments

Research Efficiency in Manufacturing: An Application of DEA at the Industry Level

This paper analyzes research efficiency at the industry level in manufacturing for 13 European member and four nonmember countries during 2000 and 2004. A unique dataset was compiled that matches patent applications at the European Patent Office (EPO) to industry-specific R&D inputs from EU KLEMS. We find that Germany, the United States, and Denmark have the highest efficiency scores on average in total manufacturing. The main industries that are at the technology frontier are those involved in electrical and optical equipment and machinery. Separate frontier estimations for these industries, conducted without the constraint of a constant technology frontier, provide additional support for our results.

Effects of the European Union Farm Credit Programs on Efficiency and Productivity of the Greek Livestock Sector: A Stochastic DEA Application

This study examines technical efficiency and productivity growth of Greek livestock farms participating in the 1994 European Union Farm Credit Program (1994-EU-FCP), i.e. regulation 2328/91. The farm-level economic data set used in this paper consists of two different groups of livestock farms, i.e. one group contains farms participating in the 1994-EU-FCP while the other one contains non-participating farms. The data set is observed over the 1993 and 1997 years. The paper uses the approach developed by Simar and Wilson (1998a, b) to bootstrapping both DEA efficiency measures and Malmquist productivity indices. Furthermore, the present paper uses the Malmquist index decomposition proposed by Simar and Wilson (1998b) and Zofio and Lovell (1997) to investigate the sources of productivity change. The technical efficiency score results indicate that the program managed to increase the efficiency of the participated farms though the less efficient farms entered the program. The total factor productivity growth results show a statistically significant increase of productivity for the group of program farms but no change for the group of non-program farms.

A performance evaluation model for international tourist hotels in Taiwan—An application of the relational network DEA

This research utilizes relational network data envelopment analysis to construct a model to analyze the efficiency and effectiveness of international tourist hotels (ITHs) in Taiwan. The different production processes within the hotel are evaluated, as well as the relationships between efficiency, effectiveness, and overall performance. Finally, based on the results, we recommend ways of enhancing the overall performance of the hotel industry in Taiwan.

The consumer loan default predicting model – An application of DEA–DA and neural network

In this paper we construct the consumer loan default predicting model through conducting the empirical analysis on the customers of unsecured consumer loan from a certain financial institution in Taiwan, and adopt the borrower’s demographic variables and money attitude as the real-timeaneous discriminant information. Furthermore, we construct respectively through four predicting methods, such as DA, LR, NN and DEA–DA, to compare the suitability of these four mentioned methods. The results show that DEA–DA and NN are possessed better predicting capability and they are the optimal predicting model that this study longing for. In addition, this study showed that the default loan predicting model will be possessed higher level of predicting capability after added money attitude.

Technical efficiency and its determinants in the Indian domestic banking industry: an application of DEA and Tobit analysis

Using cross-sectional data for 51 banks, this paper not only endeavours to measure the extent of technical efficiency in the Indian domestic banking industry, but also explores the most influential factors explaining its variations across banks. The empirical results show that: only 9 of the 51 banks operating in the financial year 2006-2007 are found to be efficient and, thus, define the efficient frontier of the Indian domestic banking industry; the technical efficiency scores range from 0.505 to 1, with an average of 0.792; de novo private sector banks dominate in the formation of the efficient frontier; managerial inefficiency is the main source of Overall Technical Inefficiency (OTIE) in the Indian domestic banking industry; the efficiency differences between public and private sector banks are not statistically significant; significant differences between large and medium banks appear with regard to Scale Efficiency (SE); exposure to off-balance sheet activities and profitability are the most influential determinants of Overall Technical Efficiency (OTE).

Anchor points in DEA

Anchor points play an important role in DEA theory and application. They define the transition from the efficient frontier to the “free-disposability” portion of the boundary. Our objective is to use the geometrical properties of anchor points to design and test an algorithm for their identification. We focus on the variable returns to scale production possibility set; our results do not depend on any particular DEA LP formulation, primal/dual form or orientation. Tests on real and artificial data lead to unexpected insights into their role in the geometry of the DEA production possibility set.

The influence of exchange rate gains or losses on the operational efficiency of the Taiwanese LED industry — an application of DEA

This study evaluates the efficiency of twenty one manufacturers of Light Emitting Diodes (LED) in Taiwan from 2003 to 2006 through three types of DEA models, BCC, Super-SBM, and Malmquist index. Due to the fact that the traditional DEA model can not address the problem of ranking when many DMUs have efficiency value of 1, Super-SBM-V model has been adopted. Furthermore, since the Taiwan LED manufacturers have depended on foreign trade, exchange rate gains or losses have a great influence on their operations. Reviewing both domestic and abroad studies show that the Malmquist productivity index has rarely been used to evaluate the influence of exchange rate gains or losses on LED manufacturers performances. This study adopted exchange rate gains or losses as a variable to examine the impact of these manufacturers’ productivity due to exchange rate gains or losses. Hopefully, the findings can serve as a reference for manufacturers to modify their developmental strategies. The findings of this study shows that exchange rate gains or losses in fact influenced performance. The connection between exchange rate gains or losses and operational efficiency has been strengthened on a yearly basis.

Application of the three-stage DEA in measuring efficiency – an empirical evidence

This article investigates the effects of the environmental factors and statistical noise on the efficiency of 89 global forest and paper companies in 2001 using the three-stage DEA method. Empirical evidences indicate the existence of environmental effects on the variation in the efficiency scores measurement. Furthermore, the final adjusted efficiency scores are lower than those scores measured in the traditional first-stage DEA.

Integrating the regulatory and utility firm perspectives, when measuring the efficiency of electricity distribution

Several DEA applications for benchmarking in utility regulation use classical models, which reveal inconsistencies due to Pareto inefficient targets. The natural course of action would be to incorporate weight restrictions, reflecting value judgments and requiring interaction between analyst and decision maker. We show that weight restricted DEA models still present some inconsistencies, since it is not possible to ensure that the target both dominates the observed DMU and lies on the empirical production frontier. Besides the decision maker and analyst interaction, it is necessary to consider a further distinction between the two parties: the regulatory agency and the utility company, which adopt different criteria to determine the efficient target. A model to obtain a preferred target DEA index is formulated, taking advantage of the dual-based DEA graphical analysis. Thus, we propose a two-phase DEA analysis that can integrate both perspectives. A case study about the Brazilian electricity sector is included, which illustrates the above-mentioned issues.

Evaluating the efficiency of a two‐stage production process using data envelopment analysis

AbstractData envelopment analysis (DEA) has been widely used to evaluate the comparative efficiencies of production processes. Most of the DEA applications assume that production processes consist of one stage. However, many production processes such as IT investments have more than one stage. In a two‐stage production process, the first stage inputs produce intermediate outputs, which are used as inputs to the second stage to produce the final outputs. In such cases, using single‐stage DEA may result in inaccurate efficiency evaluation. To address such problems, DEA models assuming two‐stage production processes have been developed. In this paper, we extend two‐stage DEA models by considering input and output slacks. We apply our model to the data from the banking industry and compare the results with those of the previous two‐stage DEA models. Our model can identify weakly efficient units of evaluation that could not be identified by the previous models.

Dea Application for the Tourist Satisfaction Management

The outputs of Data Envelope Analysis (DEA) can be used for destination satisfaction management. This study attempts to show an application of DEA to a tourist destination, Jeju Island, suggesting that DEA is a useful tool to produce important information in managing destination tourist satisfaction. DEA can be used to find best practices for benchmarking by producing a single index of efficiency of decision-making units (DMU; here, market segments were used). The efficiency index also helps to identify DMUs (market segments) requiring immediate attention for improvements because they have the smallest index number. Weighted efficiency reference set suggests possible DMUs to benchmark. Overcommitted input could be identified and quantified to optimize the resources allocation with the reduced input by reviewing scores of excessive inputs used. This study uses survey data in DEA. Interpretation of DEA with survey data has different implications compared to financial and other ratio data.

Mismanagement or mismeasurement? Pitfalls and protocols for DEA studies in the financial services sector

Dyson et al. [Dyson, R.G., Allen, R., Camanho, A.S., Podinovski, V.V., Sarrico, C.S., Shale, E.A., 2001. Pitfalls and protocols in DEA. European Journal of Operational Research 132, 245–259] suggest that the application of DEA presents a range of problems and they suggest that the systematic collection and reporting of these problems would significantly enhance DEA practice. It is widely accepted that DEA studies may be compromised by the problem of data heterogeneity. While this problem is expected in studies that cross national boundaries, it may also arise in studies for a single country. There can, for example, be significant market and regulatory differences between regions within a single country. Using a sample of Australian credit unions, this paper demonstrates the pitfalls and protocols of using DEA. It is intended that the guidelines provided in this study will enhance DEA practice in the financial services sector.

Validating DEA as a ranking tool: An application of DEA to assess performance in higher education

There is a general interest in ranking schemes applied to complex entities described by multiple attributes. Published rankings for universities are in great demand but are also highly controversial. We compare two classification and ranking schemes involving universities; one from a published report, ‘Top American Research Universities’ by the University of Florida's TheCenter and the other using DEA. Both approaches use the same data and model. We compare the two methods and discover important equivalences. We conclude that the critical aspect in classification and ranking is the model. This suggests that DEA is a suitable tool for these types of studies.