Deterministic Data Envelopment Analysis Research Articles

The Need to go Beyond Deterministic Data Envelopment Analysis (DEA): A Comparative Analysis with Bootstrapping DEA in Risk Management Efficiency Measurements

This paper attempts to rectify the flaws of deterministic data envelopment analysis (DEA), induced from the characteristics of its approach. The disadvantages have drawn considerable attention in the area of banking efficiency studies, and bootstrapping DEA (BDEA) analysis has been proposed in the literature. This paper provides a comparative analysis of each approach to understand their theoretical foundations and mathematical computations, as well as their strengths and weaknesses. The arguments were empirically supported within the context of risk management efficiency analysis in banking institutions. Finally, the paper proved the need for BDEA analysis to be used while advancing measurement precision for risk management efficiency measurements.

Stochastic efficiencies of network production systems with correlated stochastic data: the case of Taiwanese commercial banks

Although the business environment is stochastic, deterministic data envelopment analysis (DEA) models are typically used to measure the efficiency of commercial banks for the purpose of simplicity. Bank operations are characterized by a network structure due to the dual role of deposits, which, on the one hand, are the output of the process of borrowing funds from depositors and, on the other hand, are the input of the process of making loans. Since the outputs of the production process of the bank are correlated with its inputs, the model for measuring efficiency in this case is a stochastic program with correlated data. To take the correlation between the inputs and outputs into consideration, in this paper, a standard normal transformation is applied for the correlated data, and a network stochastic model is developed to obtain the distribution of the stochastic efficiency. The model is used to measure the efficiency of twenty-two commercial banks in Taiwan. The results are more reliable, discriminative, and informative than those obtained from the existing models. They also show that the performance of a bank is mainly affected by its loan performance. Different from the stereotype suggesting that private companies usually operate more efficiently than state-owned companies, public banks perform better than private banks in Taiwan.

Stochastic efficiency measures for production units with correlated data

While the real world is stochastic in nature, in many cases deterministic data envelopment analysis (DEA) models are used to measure the relative efficiency of a set of production units for simplicity. However, deterministic DEA models are not able to differentiate efficient units. More seriously, the decision maker will be over-confident with the presumably uncertain and probably misleading results. By applying a standard normal transformation, this paper develops a stochastic DEA model which is able to take the correlation between the input/output factors of each production unit to be evaluated into account to obtain the distribution of the stochastic efficiency. The efficiency distribution is more discriminative and informative than the single-valued efficiency, in that the probability that the stochastic efficiency of a unit is greater than that of another unit can be calculated. The case of twenty-five Taiwanese commercial banks discussed in a previous study that assumed the input/output factors to be independent is used to illustrate the characteristics of different models. The data is shown to be correlated, and the results confirm that ignoring the correlations between the input/output factors in measuring efficiency obtains misleading rankings.

Satisficing data envelopment analysis: a Bayesian approach for peer mining in the banking sector

Over the past few decades, the banking sectors in Latin America have undergone rapid structural changes to improve the efficiency and resilience of their financial systems. The up-to-date literature shows that all the research studies conducted to analyze the above-mentioned efficiency are based on a deterministic data envelopment analysis (DEA) model or econometric frontier approach. Nevertheless, the deterministic DEA model suffers from a possible lack of statistical power, especially in a small sample. As such, the current research paper develops the technique of satisficing DEA to examine the still less explored case of Peru. We propose a Satisficing DEA model applied to 14 banks operating in Peru to evaluate the bank-level efficiency under a stochastic environment, which is free from any theoretical distributional assumption. The proposed model does not only report the bank efficiency, but also proposes a new framework for peer mining based on the Bayesian analysis and potential improvements with the bias-corrected and accelerated confidence interval. Our study is the first of its kind in the literature to perform a peer analysis based on a probabilistic approach.

Chance Constrained Data Envelopment Analysis for Efficiency Analysis: An Application to Turkish Manufacture of Iron and Steel Sector

This study aims to determine the technical efficiency levels of the enterprises active in the “Manufacture of Basic Iron and Steel and of Ferro-Alloys” sector in Turkey. The inputs and outputs are deterministic in classical Data Envelopment Analysis, so the changes in exchange rate, inflation rate, etc. aren’t considered, and the precautions for future inconsistencies are not foreseen. This leads to critics of deterministic Data Envelopment Analysis models. In this paper, the additive model developed depending on the Banker, Charnes and Cooper (BCC) model was extended by chance constrained programming formulations in order to overcome the insufficiencies in deterministic Data Envelopment Analysis, and the technical analysis of “Manufacture of Basic Iron and Steel and of Ferro-Alloys” sector was performed.

Crecimiento y eficiencia de la industria editorial de Bogotá, Colombia

El presente estudio evalúa la eficiencia técnica y el crecimiento en productividad de la industrial editorial en Bogotá durante el período 2000-2007, mediante la aplicación de la técnica de frontera de análisis envolvente de datos determinístico (DEA, siglas en inglés). Para esto, se construye un panel de datos balanceado con base en la información de la Encuesta Anual Manufacturera. Con la descomposición del índice deMalmquist se cuantifica el aporte de la eficiencia técnica y el cambio productivo de la industria para el periodo de estudio de la productividad.

Monte Carlo Data Envelopment Analysis with Genetic Algorithm for Knowledge Management performance measurement

The paper targets to devise a genuine Knowledge Management (KM) performance measurement model in a stochastic setting based on Data Envelopment Analysis (DEA), Monte Carlo simulation and Genetic Algorithm (GA). The proposed model evaluates KM using a set of proxy measures correlated with the major KM processes. Data Collection Budget Allocation (DCBA) that maximizes the model accuracy is determined using GA. Additional data are generated and analyzed using a Monte-Carlo-enhanced DEA model to obtain the overall KM efficiency and KM processes’ efficiency scores. An application of the model has been carried out to evaluate KM performance in higher educational institutions. It is found that with GA, the accuracy of the model has been greatly improved. Lastly, comparing with a conventional deterministic DEA model, the results from the proposed model would be more useful for managers to determine future strategies to improve their KM.

A nonparametric efficiency analysis of German public transport companies

In this paper, we present a nonparametric comparative efficiency analysis of 179 communal public transport bus companies in Germany (1990–2004). We apply both deterministic data envelopment analysis (DEA) and bootstrapping to test the robustness of our estimates and to test the hypothesis of global and individual constant returns to scale. We find that the average technical efficiency of German bus companies is relatively low. We observe that the industry appears to be characterized by increasing returns to scale for smaller companies. These results would imply increasing pressure on bus companies to restructure.

A deterministic approach for performance assessment and optimization of power distribution units in Iran

This paper presents a deterministic approach for performance assessment and optimization of power distribution units in Iran. The deterministic approach is composed of data envelopment analysis (DEA), principal component analysis (PCA) and correlation techniques. Seventeen electricity distribution units have been considered for the purpose of this study. Previous studies have generally used input–output DEA models for benchmarking and evaluation of electricity distribution units. However, this study considers an integrated deterministic DEA–PCA approach since the DEA model should be verified and validated by a robust multivariate methodology such as PCA. Moreover, the DEA models are verified and validated by PCA, Spearman and Kendall's Tau correlation techniques, while previous studies do not have the verification and validation features. Also, both input- and output-oriented DEA models are used for sensitivity analysis of the input and output variables. Finally, this is the first study to present an integrated deterministic approach for assessment and optimization of power distributions in Iran.

Predicting change in bank efficiency in Jordan: a data envelopment analysis

PurposeThis study aims to investigate the relative efficiency pattern of Jordanian banks during the period between 1998 and 2004.Design/methodology/approachThe deterministic data envelopment analysis (DEA) as a quantitative approach was used to obtain the efficiency of individual commercial banks in Jordan.FindingsThe results of the DEA Charnes, Cooper and Rhodes model show an increase in bank efficiency in the entire period except in 2003 and 2004 where a decrease in bank efficiency was shown for few banks in the sample. The total efficiency scores suggest that the liberalisation programme has provided the anticipated efficiency gains. Most efficiency scores showed consistent increases after the introduction of the policy with the exception of few banks which have responded differently and shown decreased in efficiency. This may be taken to imply that the banks have responded differently to the new system. The analysis further shows that both assets utilisation and the labour factor had an adverse effect on bank efficiency, especially in terms of number of employees.Research limitations/implicationsThe effect of the Jordanian Government liberalisation programme may not be readily discerned in such a relatively short period of time, which may require that a longer time period elapses before this effect becomes noticeable.Originality/valueThe paper analyses the performance of Jordanian banks with regard to their efficiency.

An input relaxation measure of efficiency in stochastic data envelopment analysis

We introduce stochastic version of an input relaxation model in data envelopment analysis (DEA). The input relaxation model, recently developed in DEA, is useful to resource management [e.g. G.R. Jahanshahloo, M. Khodabakhshi, Suitable combination of inputs for improving outputs in DEA with determining input congestion, Appl. Math. Comput. 151(1) (2004) 263–273]. This model allows more changes in the input combinations of decision making units than those in the observed inputs of evaluating decision making units. Using this extra flexibility in input combinations we can find better outputs. We obtain a non-linear deterministic equivalent to this stochastic model. It is shown that under fairly general conditions this non-linear model can be replaced by an ordinary deterministic DEA model. The model is illustrated using a real data set.

Next Stop: Restructuring? A Nonparametric Efficiency Analysis of German Public Transport Companies

In this paper, we present a nonparametric comparative efficiency analysis of 179 communal public transport bus companies in Germany (1990-2004). We apply both deterministic data envelopment analysis (DEA) and bootstrapping to test the robustness of our estimates and to test the hypothesis of global and individual constant returns to scale. We find that the average technical efficiency of German bus companies is relatively low. We observe that the industry appears to be characterized by increasing returns to scale for smaller companies. These results would imply increasing pressure on bus companies to restructure.

Deterministic and Stochastic Capacity Estimation for Fishery Capacity Reduction

Deterministic data envelopment analysis (DEA) and stochastic production frontier (SPF) models are alternative methods for estimating capacity in fisheries. Fishery managers should be aware of likely differences in the capacity estimates obtained from these approaches if such estimates are to be used to support capacity reduction programs. In this paper, we provide a comparative analysis of DEA and SPF capacity estimates for a variety of possible capacity concepts using a panel data set for 10 vessels in the U.S. Northwest Atlantic scallop fishery. We find that DEA capacity output measures are higher than corresponding SPF measures, but that the two approaches provide similar guidance about overall and even relative boat-specific capacity levels under certain circumstances. The variations that emerge suggest, in particular, that biases can arise from inferring capacity output at "efficient" production levels, which disregards customary and usual operating conditions.

Productive efficiency of English football teams—a data envelopment analysis approach

AbstractThis paper investigates how close to their potential English Premier League Clubs play. Using a deterministic Data Envelopment Analysis Approach, the productive efficiency of 20 teams in the 2000/2001 season is measured and weaknesses of individual teams are disclosed. The sensitivity of results is analyzed with regard to different model specifications and variable combinations. Copyright © 2003 John Wiley & Sons, Ltd.

On the (in)efficiency of Swiss hospitals

The efficiency of hospitals is of interest to health insurers, government authorities and hospital management itself. However, econometric methods for determining (in)efficiency have severe drawbacks since hospitals are multiproduct firms and because the duality between production and cost functions cannot be assumed. In this work, non-parametric, deterministic data envelopment analysis (DEA) is used to measure the relative inefficiency of 89 Swiss hospitals covering the years 1993–1996 (310 observations). Special attention is given to the role of patient days in the production of health. The findings depend on whether patient days are viewed as an input of patient time or as an output, as in previous studies. While the probability of a unit being inefficient cannot be explained using the available data, the degree of overall inefficiency is shown to significantly depend on the financial incentives faced by management, in particular due to subsidization. Private hospitals do not seem to be less inefficient than public ones; however, this may be caused by their ‘overusing’ inputs that in fact are valued as amenities by patients. This consideration points to an important limitation in applying the purely quantitative criteria of DEA to hospitals.

Chance Constrained Programming Formulations for Stochastic Characterizations of Efficiency and Dominance in DEA

Pareto-Koopmans efficiency in Data Envelopment Analysis (DEA) is extended to stochastic inputs and outputs via probabilistic input-output vector comparisons in a given empirical production (possibility) set. In contrast to other approaches which have used Chance Constrained Programming formulations in DEA, the emphasis here is on “joint chance constraints.” An assumption of arbitrary but known probability distributions leads to the P-Model of chance constrained programming. A necessary condition for a DMU to be stochastically efficient and a sufficient condition for a DMU to be non-stochastically efficient are provided. Deterministic equivalents using the zero order decision rules of chance constrained programming and multivariate normal distributions take the form of an extended version of the additive model of DEA. Contacts are also maintained with all of the other presently available deterministic DEA models in the form of easily identified extensions which can be used to formalize the treatment of efficiency when stochastic elements are present.