Showing papers on "Data envelopment analysis published in 2013"

A survey of DEA applications

Abstract: The literature of data envelopment analysis (DEA) encompasses many surveys, yet all either emphasize methodologies or do not make a distinction between methodological and application papers. This study is the first literature survey that focuses on DEA applications, covering DEA papers published in journals indexed by the Web of Science database from 1978 through August 2010. The results show that on the whole around two-thirds (63.6%) of DEA papers embed empirical data, while the remaining one-third are purely-methodological. Purely-methodological articles dominated the first 20 years of DEA development, but the accumulated number of application-embedded papers caught up to purely-methodological papers in 1999. Among the multifaceted applications, the top-five industries addressed are: banking, health care, agriculture and farm, transportation, and education. The applications that have the highest growth momentum recently are energy and environment as well as finance. In addition to the basic statistics, we uncover the development trajectory in each application area through the main path analysis. An observation from these works suggests that the two-step contextual analysis and network DEA are the recent trends across applications and that the two-step contextual analysis is the prevailing approach.

Data envelopment analysis 1978-2010: A citation-based literature survey

Abstract: This study surveys the data envelopment analysis (DEA) literature by applying a citation-based approach. The main goals are to find a set of papers playing the central role in DEA development and to discover the latest active DEA subareas. A directional network is constructed based on citation relationships among academic papers. After assigning an importance index to each link in the citation network, main DEA development paths emerge. We examine various types of main paths, including local main path, global main path, and multiple main paths. The analysis result suggests, as expected, that Charnes et al. (1978) [Charnes A, Cooper WW, Rhodes E. Measuring the efficiency of decision making units. European Journal of Operational Research 1978; 2(6): 429–444] is the most influential DEA paper. The five most active DEA subareas in recent years are identified; among them the “two-stage contextual factor evaluation framework” is relatively more active. Aside from the main path analysis, we summarize basic statistics on DEA journals and researchers. A growth curve analysis hints that the DEA literature’s size will eventually grow to at least double the size of the existing literature.

Quantitative Models for Performance Evaluation and Benchmarking : Data Envelopment Analysis with Spreadsheets

Abstract: This article reviews Joe Zhu’s book, “Quantitative Models for Performance Evaluation and Benchmarking: Data Envelopment Analysis with Spreadsheets,” now in its third edition and published by Springer.

Stochastic frontier analysis using Stata

Abstract: This paper describes sfcross and sfpanel, two new Stata commands for the estimation of cross-sectional and panel data stochastic frontier models. sfcross extends the official frontier capabilities by including additional models (Greene 2003; Wang 2002) and command functionality, such as the possibility to manage complex survey data characteristics. Similarly, sfpanel allows to estimate a much wider range of time-varying inefficiency models compared to the official xtfrontier command including, among the others, the Cornwell et al. (1990) and Lee and Schmidt (1993) models, the exible model of Kumbhakar (1990), the inefficiency effects model of Battese and Coelli (1995) and the "true" fixed and random-effects models developed by Greene (2005a). A brief overview of the stochastic frontier literature and a description of the two commands and their options are given, and illustrations using simulated and real data are provided.

A survey on bank branch efficiency and performance research with data envelopment analysis

Abstract: The banking industry has been the object of DEA analyses by a significant number of researchers and probably is the most heavily studied of all business sectors. Various DEA models have been applied in performance assessing problems, and the banks' complex production processes have further motivated the extension and improvement of DEA techniques. This paper surveys 80 published DEA applications in 24 countries/areas that specifically focus on bank branches. Key issues related to the design of DEA models in these studies are discussed. Much advice is included on how to design future experiments and studies in this domain. A number of areas where further research could be fruitful are suggested.

A Comparison of Performance of Islamic and Conventional Banks 2004 to 2009

Abstract: tWe compare the efficiency of Islamic and conventional banks during the period 2004–2009using data envelopment analysis (DEA) and meta-frontier analysis (MFA). The use of the non-parametric MFA allows for the decomposition of gross efficiency (i.e. the efficiency of banks when measured relative to a common frontier) into 2 components: net efficiency(the efficiency of banks measured relative to their own bank type frontier) and type efficiency (the efficiency which relates to modus operandi). This approach is new to the Islamic banking literature. The analysis is performed in two stages. The first stage employs DEA andMFA to compare banks on the basis of gross efficiency and its components (net and type).We find that Islamic banks are typically on a par with conventional ones in terms of gross efficiency, significantly higher on net efficiency and significantly lower on type efficiency. Second stage analyses, which account for banking environment and bank-level characteristics, confirm these results. The low type efficiency of Islamic banks could be attributed to lack of product standardization whereas high net efficiency reflects high managerial capability in Islamic banks. These findings are relevant to both policy-makers and regulators. In particular, Islamic banks should explore the benefits of moving to a more standardized system of banking, while the underperformance of conventional bank managers could be examined in the context of the on-going remuneration culture.

Financial freedom and bank efficiency: Evidence from the European Union

Abstract: This paper investigates the dynamics between the financial freedom counterparts of the economic freedom index drawn from the Heritage Foundation database and bank efficiency levels. We rely on a large sample of commercial banks operating in the 27 European Union member states over the 2000s. After estimating bank-specific efficiency scores using Data Envelopment Analysis (DEA), we develop a truncated regression model combined with bootstrapped confidence intervals to test our main hypotheses. Results suggest that the higher the degree of an economy’s financial freedom, the higher the benefits for banks in terms of cost advantages and overall efficiency. Our results also show that the effects of financial freedom on bank efficiency tend to be more pronounced in countries with freer political systems in which governments formulate and implement sound policies and higher quality governance.

Environmental energy efficiency of China's regional economies: A non-oriented slacks-based measure analysis

Abstract: This paper proposes two environmental energy efficiency indices, the pure energy efficiency and scale efficiency based on the slacks-based measure of efficiency in data envelopment analysis (SBM-DEA) These two indices are used to measure energy efficiency by incorporating three undesirable outputs—carbon dioxide, sulfur dioxide, and Chemical Oxygen Demand—in China's regional economies between 2001 and 2010 The empirical results show most provinces were not energy efficient, due primarily to pure energy inefficiency There exists a regional unbalance in terms of the environmental energy efficiency Results support the Porter hypothesis, which indicates that stricter environmental regulations can improve efficiency and encourage innovation In addition, undesirable outputs had a significant effect on energy efficiency measurements

Analyzing Firm Performance in the Insurance Industry Using Frontier Efficiency and Productivity Methods

Abstract: This chapter reviews the modern frontier efficiency and productivity methodologies that have been developed to analyze firm performance, emphasizing applications to the insurance industry. The focus is on the two most prominent methodologies—stochastic frontier analysis using econometrics and non-parametric frontier analysis using mathematical programming. The chapter considers the underlying theory of the methodologies as well as estimation techniques and the definition of inputs, outputs, and prices. Seventy-four insurance efficiency studies are identified from 1983 to 2011, and 37 chapters published in upper tier journals from 2000 to 2011 are reviewed in detail. Of the 74 total studies, 59.5% utilize data envelopment analysis as the primary methodology. There is growing consensus among researches on the definitions of inputs, outputs, and prices.

Efficiency Estimation of Production Functions

Abstract: Data Envelopment Analysis (DEA) is a Mathematical Programming technique that finds a number of applications to measure the performance of similar units. The performance of these units say Decision Making Units (DMU) is assessed with DEA is obtained by using the concept of Efficiency which is the ratio of Weighted Sum of outputs to weighted sum of inputs. The efficiency obtained by using DEA are relative to best performance of Virtual DMU. In the present study, the efficiency of Production has been measured by specifying and estimating the parameters of Translog output distance function. Further, a non-parametric approach has been applied to measure the efficiency of production by constructing several Linear Programming Problem based on Translog output distance function to study efficiency variation in Indian Commercial Banks.

Benchmarking airports from a managerial perspective

Abstract: Benchmarking airports is currently popular both in the academic literature and in practice but has proved rather problematic due to the heterogeneity inherent in any reasonably sized dataset. Most studies either treat the airport production technology as a black box, or separate the terminal and airside activities, assessing them individually. In this article we analyze airports as a single unit due to the direct complementarities, thus avoiding the artificial separation of inputs. Using data envelopment analysis (DEA), we open the black box in which a network describes the production process, thus demonstrating the sequential effects that separate final from intermediate outputs, including those under partial managerial control and those that are known to be non-discretionary. To further improve the benchmarking process, we identify appropriate peers for a case study of 43 European airports over 10 years, through a restricted reference mechanism according to pre-defined characteristics. Compared to basic DEA models, the results of the proposed structure provide more meaningful benchmarks with comparable peer units and target values that are potentially achievable in the medium term. By identifying each unit's individual reference set, unique outliers influence the performance measurement less severely than occurs under basic DEA. In addition, the formulations produce an implementation path that moves the airport towards the Pareto frontier gradually, taking into account the regulatory and business environment in which the unit is located.

R&D, productivity, and market value: An empirical study from high-technology firms

Abstract: Although prior research has addressed the influence of production activity and research and development (R&D) on productivity, it is not clear whether production and R&D affect the market value of a firm. This study proposes and verifies an R&D value chain framework to explore the relationship among productivity, R&D, and firm market values, as measured by Tobin's q theory. By doing so, we attempt to link new theoretical insights and empirical evidence on the effects of R&D efforts and basic production activities to the market valuations of high-technology firms. The value chain data envelopment analysis approach was proposed to estimate parallel-serial processes of basic operations and R&D efforts. This approach can be used to simultaneously estimate the profitability efficiency and marketability efficiency of high-technology firms. This area has rarely been studied, but it is particularly important for high-technology R&D policies and for further industrial development. Using the R&D value chain perspectives of model innovations and extensions proposed in several previous studies, we examined the appropriate levels of intermediate outputs. Production efficiency and R&D were combined to estimate the appropriate levels of intermediate outputs for high-technology firms. Based on the intermediate output analyses, we developed an R&D efforts decision matrix to explore and identify operational and R&D efficiency for high-technology firms. Our sample firms are displayed on a four-quadrant action grid that provides visual information on current short-term operational efficiency and decision making on long-term R&D strategic positions. The empirical findings from the R&D value chain model can provide information for policymakers and managers and suggest the adoption of various policies that place more emphasis on profitability and marketability strategies.

A fuzzy analytic hierarchy process (AHP)/data envelopment analysis (DEA) hybrid model for efficiently allocating energy R&D resources: In the case of energy technologies against high oil prices

Abstract: “The Low Carbon, Green Growth” was declared as Korean national agenda in 2008. Korea has been enhancing the green growth for the sustainable economic development and fostering energy. To improve Korean national energy security and promote the “Low Carbon, Green Growth”, we established a long term strategic energy technology roadmap. In this paper, five criteria, such as economical impact, commercial potential, inner capacity, technical spin-off, and development cost, were used to assess the strategic energy technologies against high oil prices. We developed the integrated two-stage multi-criteria decision making (MCDM) approach which was used to evaluate the relative weights of criteria and measures the relative efficiency of energy technologies against high oil prices. On the first stage, the fuzzy analytic hierarchy process, reflecting the vagueness of human thought with interval values instead of crisp numbers, allocated the relative weights of criteria effectively instead of the AHP approach. On the second stage, the data envelopment analysis approach measured the relative efficiency of energy technologies against high oil prices with economic viewpoints. The relative efficiency score of energy technologies against high oil prices can be the fundamental decision making data which help decision markers to effectively allocate the limited R&D resources.

Estimating the degree of operating efficiency gains from a potential bank merger and acquisition: A DEA bootstrapped approach

Abstract: We propose a bootstrapped Data Envelopment Analysis (DEA)-based procedure to pre-calculate and pre-evaluate the short-run operating efficiency gains of a potential bank merger or acquisition (M&A). As an illustrative example, we apply our proposed procedure to investigate the degree of operating efficiency gains of 45 possible bank M&As in the Greek banking industry over the period from 2007 to 2011. The results reveal that a year before and a year after the initiation of the Greek fiscal crisis, the majority of the potential bank M&As under examination were unable to generate short-run operating efficiency gains. In addition, our results for 2011 indicate that the majority of bank M&As can lead to short-run operating efficiency gains. Finally, the empirical findings support the view that a merger or acquisition between efficient banks does not ensure an efficient bank M&A.

Performance Measurement with Fuzzy Data Envelopment Analysis

Abstract: The intensity of global competition and ever-increasing economic uncertainties has led organizations to search for more efficient and effective ways to manage their business operations. Data envelopment analysis (DEA) has been widely used as a conceptually simple yet powerful tool for evaluating organizational productivity and performance. Fuzzy DEA (FDEA) is a promising extension of the conventional DEA proposed for dealing with imprecise and ambiguous data in performance measurement problems. This book is the first volume in the literature to present the state-of-the-art developments and applications of FDEA. It is designed for students, educators, researchers, consultants and practicing managers in business, industry, and government with a basic understanding of the DEA and fuzzy logic concepts.