Data Envelopment Analysis DEA Research Articles

Analysis of the environmental strategies for supportting the economic-financial evaluation of energy sector firms within the corporate sustainability index – ISE

Business companies have entered the sustainable development to achieve growth in the market in which they operate and remain in the long term, as well as the generation of higher income. The objective of the present study is to correlate the environmental strategies as support for assessment and financial return of the Brazilian energy sector companies that are listed in the corporate sustainability Index (ISE) in the Bolsa de Valores Bovespa/BMF. For this correlation analysis, we used the Data Envelopment Analysis DEA, to perform the assessment of efficiency through the classic border and construction of a combined index ranking, with statistical analysis conducted by SPSS, with the data from the 10 companies in the energy sector used in the research. For analysis of environmental strategies, analyzed all the Yearbooks published, through a qualitative analysis. As a result, was raised a ranking of companies which presents the company Light S/A as the most efficient financial and environmental correlation. Is also a general survey of the main strategies used by each company, in order to contribute to a sustainable actions alignment to the State of national art.

Ranking electricity distribution units using slacks-based measure, strong complementary slackness condition, and discriminant analysis

This study integrates SBM (slacks-based measure), SCSC (strong complementary slackness condition), and DEA–DA (data envelopment analysis–discriminant analysis) to rank electricity distribution units in Iran. DEA is a popular technique that many researchers use it to evaluate the performance of different organizations in public and private sectors. As conventional DEA models do not fully exploit information of all inputs and outputs, they result zero in many multipliers. These DEA models may yield many efficient decision making units (DMUs). This decreases discrimination power of the DEA. To rectify this shortcoming, this study proposes a novel application of SBM–DEA/SCSC along with DEA–DA to reduce number of efficient DMUs. Using the proposed approach, electricity distribution units are classified into efficient and inefficient groups based upon their efficiency scores. Then, DEA–DA is utilized to rank efficient DMUs. Sensitivity analysis validates the proposed approach.

Technical efficiency of French nuclear energy plants

This article analyses the efficiency of French nuclear energy plants belonging to EDF-electricity of France from 2004 to 2008 with a DEA-Data Envelopment Analysis model. The -convexity model is used to investigate the technical efficiency of a representative sample of nuclear plants. The results indicated that some plants have undergone an improvement in technical efficiency while others have regressed in terms of technical efficiency. Policy implications related to the results are discussed.

MEASURING EFFICIENCY OF RECYCLING SYSTEMS BASED ON DATA ENVELOPMENT ANALYSIS (DEA) NETWORK: A CASE FROM CHINESE PROVINCIAL CIRCULAR ECONOMY

As a typical environment-economy linking system, recycling and its efficiency measurement with a triple-bottom-line (TBL) thinking, increasingly play an important role in the development of real economies and environmental protection. Since the classic black-box-based data envelopment analysis DEA model may over-estimate the operation performance of a decision making unit (DMU), this paper describes a novel network based on DEA model to narrow the gap between the DEA theory and practical needs on decision making. The proposed DEA model firstly accesses the overall efficiency of recycling systems and then divides it into efficiencies of two sub-systems. Finally, a case from Chinese provincial economy is applied to verify the novel model and the related results with comparing them with those of traditional black box DEA model so as to indicate a more accurate efficiency measurement with the new DEA model.

Fuzzy free disposal hull models under possibility and credibility measures

The free disposal hull FDH models are used as an alternative to data envelopment analysis DEA models for performance measurement and efficiency assessment. The conventional FDH models are used to evaluate the performance of a set of firms or decision-making units DMUs using deterministic input and output data. However, the input and output data in the real-life performance evaluation problems are often imprecise and ambiguous. The impreciseness and ambiguity associated with the input and output data in FDH can be represented with fuzzy variables. In this paper, the concept of chance-constrained programming is used to develop FDH models with various returns to scale assumptions, including variable returns to scale VRS, variable non-increasing returns to scale NIRS, variable non-decreasing returns to scale NDRS, and constant returns to scale CRS, for efficient DMUs with fuzzy data. We propose two fuzzy FDH models with respect to possibility and expected value credibility approach constraints. Finally, a numerical example is presented to demonstrate the efficacy of the proposed procedures and algorithms.

Bank branch operating efficiency: evaluation with data envelopment analysis

Article history: Received January 20, 2014 Accepted 30 August 2014 Available online September 9 2014 Measuring the relative efficiency of similar units has been a popular research especially when the units were mostly non-financial. Even, similar financial units may not be necessarily evaluated based on traditional financial figures such as return of equities, return of assets, etc. In this paper, we present an empirical investigation to measure the relative efficiency of 30 branches of an Iranian bank named Bank Mellat. The study considers four inputs including operating expenses, interest paid, capital expenditures and fixed assets. In addition, we use customers’ bank deposit, commissions and loans paid as output parameters. Using three different data envelopment analyses, the study measures the relative efficiencies of all units. The preliminary results indicate that most banks were working under desirable level of efficiency. © 2014 Growing Science Ltd. All rights reserved. DEA Data envelopment analysis Efficiency Banking industry

Optimal direct mailing modelling based on data envelopment analysis

Data envelopment analysis DEA is a mathematical programming technique that is frequently used for measuring and benchmarking efficiency of the homogenous decision-making units DMUs. This paper proposes a new use of DEA for customers scoring and particularly their direct mailing modelling. Moreover, because DEA models suffer from some weaknesses, that is, unrealistic weighting scheme of the inputs and outputs and incomplete ranking among efficient DMUs, the present paper compares different ways of solving these problems and concludes that common set of weights method, as a result of some advantages, outperforms other procedures.

Mutual fund performance evaluation: a value efficiency analysis approach

Data envelopment analysis DEA is an efficient tool for evaluating mutual fund performance. It is important for investors to select the best funds for investment. In evaluation of mutual fund performance, besides quantitative elements, there are many qualitative elements that are of importance to the investors. In this paper, value efficiency analysis VEA was used in mutual funds performance evaluation to incorporate the investors judgements about qualitative elements into the evaluation. Also, the results of this approach were compared with those of general DEA models. This approach is based on choosing convenient variables inputs and outputs by reviewing the past studies. Then the input/output data are analysed using the concept of value efficiency, a novel procedure for incorporating the decision maker's preferences into DEA via the most preferred solution MPS.

The use of data envelopment analysis for international market selection in the presence of multiple dual-role factors

Selection of international market IM is a critical decision and needs to be made with considerable attention and deliberation. In some situations however, some criteria have the nature of both cost and profit. Likewise, in data envelopment analysis DEA some criteria play both input cost and output profit roles, simultaneously. In the DEA literature such criteria are called dual-role factors. Hence, the objective of this paper is to develop a new model for international market selection IMS, using DEA based on ternary variable in the presence of dual-role factors. A case study illustrates the application of the proposed model.

Direct mailing decisions based on the worst and best practice cross-efficiency evaluations

The problem argued in the literature of direct mailing decisions generally contains three parts: 1 forecasting customers' future purchase/non-purchase responses; 2 evaluating the effectiveness of various strategies for increasing customers purchase responses; 3 prioritising the customers in terms of their values. A significant body of the literature has been dedicated to the first two components, and in particular, to purchase/non-purchase prediction modelling. However, in the current paper, we do not address these two components, but rather we focus on the third component. To this end, data envelopment analysis DEA technique and particularly cross-efficiency formulation of the best practice frontier Charnes, Cooper and Rhodes CCR Charnes et al., 1978 BPF-CCR is used to determine those customers who should be put on the first priorities of marketing mailing list. In addition, the cross-efficiency formulation of worst practice frontier CCR WPF-CCR is developed to exclude the worst customers from mailing list and save the mailing expenses for the best practice ones. Using a numerical example, the application of the proposed model is demonstrated.

Evaluating the efficiency of public procurement contracts for cultural heritage conservation works in Italy

Almost everywhere public intervention in cultural heritage (CH) conservation is widespread. Using Italy as a case study, the paper analyses public capital expenditure for CH conservation and investigates whether the high degree of specialization of contracting authorities affects the efficiency of CH conservation works. A two-stage analysis is carried out. At a first stage, a nonparametric approach (Data Envelopment Analysis—DEA) investigates the relative efficiency scored by each single work; at a second stage, the determinant factors of the scores variability are investigated. The empirical analysis shows that, ceteris paribus, the expertise affects the efficiency of CH works.

A use of DEA–DA to measure importance of R&D expenditure in Japanese information technology industry

This study discusses a use of DEA–DA (Data Envelopment Analysis–Discriminant Analysis) to assess the corporate value of IT (Information Technology) firms and other manufacturing firms. It is widely known that Tobin's q is a ratio that serves as a measure of corporate value. This study explores a linkage between DEA–DA (as a methodology) and Tobin's q (as a theoretical basis for corporate performance) via the measurement of Altman's Z score (as a financial performance). The Z score provides us with aggregated information regarding financial ratios and other financial measures that investors usually examine in their investment decisions. This study applies the proposed approach to compare between Japanese IT and manufacturing firms. The empirical evidence obtained in this study indicates that R&D (Research and Development) expenditure enhances the corporate value of Japanese IT and manufacturing firms. However, the R&D expenditure of IT firms is important but not essential, compared with other manufacturing firms in Japan. The empirical result is inconsistent with the opinion of many corporate leaders and individuals who are associated with the IT industry. They believe that the R&D expenditure is essential for the Japanese IT industry to maintain its international competitiveness in the global market. In addition to the R&D expenditure, the empirical study indicates that IT leaders need to pay attention to the reduction of an R&D cycle time to enhance their competitiveness because a market cycle time of IT products is less than that of the other manufacturing products. The findings on Japanese IT and manufacturing industries are applicable to other industrial nations.

Quantification of airlines business efficiency using data envelopment analysis (DEA)

DEA-Data envelopment analysis is a mathematical programming technique, which is successfully used to quantify the efficiency of companies in the manufacturing and service sector. The technique essentially estimate ratio of input and output parameters of success - efficiency, in an implicit way and the result is the efficiency of business operations quantification or measurement. This result provides an opportunity to reveal advantages and disadvantages of business activities and processes, meet the business needs and requirements and to identify opportunities to improve current work and processes, on the basis of quantifying the efficiency. Analytic process that develops on the basis of these and the real input and output parameters in addition to objectivity in the quantification of efficiency, identifies best practices. This paper presents the application of DEA to measure efficiency of European airlines which annually transport five million passengers and which are members of the AEA organization. The first step is to quantify the level of efficiency based on real data and then, the ways to improve the efficiency of their work were recommended, for the inefficient ones. Key words: Data envelopment analysis, efficiency, European airlines.

Economic evaluation of current conditions of competition and efficiency of automotive and rail systems in Colombia

This study uses microeconomic data from the transportation systems of land cargo in Colombia: rail and trucking, to determine their degree of allocative efficiency through the non-parametric method Data Envelopment Analysis DEA. The average overall efficiency found was 74.4% for trains and 20.56% for trucks. These figures indicate that rail is more efficient in the allocation of resources. This means that trains in Colombia use their input better than trucks to maximize their production, given the costs and technological characteristics of each system. This is a signal for the design of a public policy for investment in transportation infrastructure that seeks to raise the competitiveness of Colombian exports, investing not only in roads but in complementary systems such as railways too.

Medición de la eficiencia técnica relativa de las fincas asociadas a Coounión en Guasca Cundinamarca

Objetivo. Medir la eficiencia técnica relativa en las fincas asociadas a la cooperativa COOUNIÓN mediante Data Envelopment Analysis DEA (Análisis Envolvente de Datos). Materiales y métodos. Se tomaron como muestra las doce fincas asociadas a la Cooperativa Coounión en el municipio de Guasca (Cundinamarca). La información se obtuvo durante el período comprendido entre el 1º de junio del 2008 y el 31 de mayo del 2009. Los datos se estructuraron en seis variables, de las cuales se plantean dos modelos, ambos con cuatro variables y que están orientados a las entradas con rendimientos constantes a escala (CRS). El primer modelo consta de tres entradas: nutrición, mantenimiento, ordeño, y una salida: leche; mientras que el segundo modelo cuenta con dos entradas: nutrición, mantenimiento y dos salidas: carne, crías. Resultados. De las doce fincas solo una presentó, la mejor eficiencia tanto en el modelo 1 como en el modelo 2. Por esta razón, se determinaron las mejores prácticas de esta finca con el fin de replicarlas en las demás. Conclusiones. Aplicar la metodología DEA en las fincas ganaderas es viable porque permite enfocarse principalmente en aquellas variables que son controlables por el ganadero como los insumos. Por consiguiente, la evaluación de la eficiencia técnica relativa se desarrolló orientada a estos; así se demostró que las fincas pueden mantener sus niveles de producción actuales haciendo reducciones significativas en sus costos.

A consensual peer-based DEA-model with optimized cross-efficiencies – Input allocation instead of radial reduction

Data Envelopment Analysis DEA is a method for estimating (in-)efficiencies of Decision Making Units DMUs by means of weighted output – to input – ratios, being the weights optimal virtual prices of such ex-post activities for all units. The cross-efficiency matrix then evaluates these output – to input – relations with respect to all optimal price systems, and hence permits efficiency rankings for the DMUs by aggregating the matrix entries line – and/or columnwise. In this contribution the classical input oriented DEA approach is generalized twofold: its first aim is an optimal efficiency improving input allocation rather than a mere radial input reduction. The second aim is the choice of a peer-DMU, the price system of which is acceptable for the remaining units. As free input allocation permits substitutional effects and so rises productivities in view of possible peers and for all units, it supports such consensual choice. Numerical examples show the positive effects of the new concept.

Technical efficiency in Saudi banks

This study analyses the technical efficiency of Saudi banks using a two-stage DEA-data envelopment analysis approach. In the first stage, we use a bootstrapped DEA–VRS model to identify the efficiency scores, and in the second stage, we use a bootstrapped truncated regression model to identify the covariates that explain technical efficiency. Policy implications are derived.

Saudi Arabian IPOs Productivity and Efficiency

Purpose - The main objective of the paper is to examine the performance of Saudi Arabian firms’ performance as they make the transition from private ownership into public ownership.Design/ Methodology/ Approach - A sample of 13 Saudi IPOs performance is investigated. We use a data envelopment analysis DEA method to construct the Malmquist productivity and efficiency indices.Findings - We have found that Saudi IPOs exhibit a significant decline in the productivity after the IPO as compared to the pre-IPO level.Originality/ Value - The paper is the first to provide assessment for the clustering IPOs that occurred in the Kingdom of Saudi Arabia in recent years.

Financial performance analysis of US and world telecommunications companies: Importance of Information Technology in the telecommunications industry after the AT&T breakup and the NTT divestiture

This study investigates the financial performance of the world telecommunications industry by DEA–DA (Data Envelopment Analysis–Discriminant Analysis). The proposed use of DEA–DA has a linkage with Altman's Z score that has long served as a methodological and conceptual basis in finance. Based upon the Z score of telecommunications companies, we rank them for financial assessment. After evaluating their financial performance of the firms, this study pays attention to the financial performance of AT&T (American Telephone & Telegraph) and NTT (Nippon Telegraph and Telephone) after their divestiture. This study finds that AT&T outperformed NTT because AT&T changed itself to an IT (Information Technology) company that provides wireless communications services and other IT services, but NTT separated IT and wireless services into the other companies after the breakup.

Nonparametric frontier estimation via local linear regression

Abstract In this paper we propose a nonparametric regression frontier model that assumes no specific parametric family of densities for the unobserved stochastic component that represents efficiency in the model. Nonparametric estimation of the regression frontier is obtained using a local linear estimator that is shown to be consistent and nh n asymptotically normal under standard assumptions. The estimator we propose envelops the data but is not inherently biased as free disposal hull—FDH or data envelopment analysis—DEA estimators. It is also more robust to extreme values than the aforementioned estimators. A Monte Carlo study is performed to provide preliminary evidence on the estimator's finite sample properties and to compare its performance to a bias corrected FDH estimator.