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    Productivity of Automobile Industries using the Malmquist Index: Evidence from the Last Economic Recession
    (Pontificia Universidad Católica del Perú. CENTRUM, 2011) Chen, Yao
    In this paper, the financial information provided by Fortune Magazine is used to study the productivity changes in the global auto industry during 1991-1997, including automakers from the USA, Europe, Japan, and South Korean. The paper seeks to uncover global auto industry’s productivity changes during the early 1990s economic recession. Data envelopment analysis (DEA) is used to identify the empirical performance frontier. A new DEA-based Malmquist productivity index is used to further analyze the two Malmquist components. The analysis not only reveals patterns of productivity change and presents a new interpretation along with the managerial implications of each Malmquist component, but also the analysis identifies the strategy shifts of individual companies based upon isoquant changes. The labor efficiency and overcapacity of the global auto industry is studied, and judgments can be made about whether such strategy shifts are favorable and promising.
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    Benchmarking Peruvian Banks using Data Envelopment Analysis
    (Pontificia Universidad Católica del Perú. CENTRUM, 2011) Charles, Vincent; Kumar, Mukesh; Zegarra, Luis Felipe; Avolio, Beatrice
    Despite the growing literature on bank efficiency worldwide over the last decade, researchers have neglected the Peruvian banking sector. In this paper, the technique of data envelopment analysis (DEA) is used to investigate the efficiency of Peruvian banks for the period 2000 to 2009 to benchmark currently existing banks based on their super-efficiency scores over time. Further, an in-depth analysis of currently existing banks for the period 2008 to 2009 is conducted to check the robustness of DEA efficiency scores and the potential improvement of inputs and outputs for inefficient banks, indicating by how much and in what areas inefficient banks need to improve in order to be efficient. Our finding shows an increasing trend in technical efficiency during the period 2000 to 2009 which gives an indication of an affirmative effect of the reform process in the Peruvian banking sector. On average, the multinational banks are performing better than are domestic banks throughout the period except in 2007, during which a sharp decline in efficiency performance for both the groups was apparent, possibly a result of global financial turmoil. The application of jackknifing analysis with appropriate statistical tools shows the DEA efficiency scores are robust. Among the 14 currently existing banks, Banco Ripley and Banco Santander Peru were the best performers, whereas Banco Azteca was the worst performer, followed by Interbank and Banco de Comercio. Furthermore our findings suggest that inefficient banks require more rigorous policies with respect to the allocation of funds for additional loans as well as other earnings assets. In this way, presently inefficient banks may approach the efficiencies of the best practice banks.
  • Miniatura
    ÍtemAcceso Abierto
    Coalition Formation and Data Envelopment Analysis
    (Pontificia Universidad Católica del Perú. CENTRUM, 2011) Färe, Rolf; Grosskopf, Shawna; Margaritis, Dimitri
    The introduction of a framework for optimal coalition formation using data envelopment analysis (DEA) methods is the focus of this paper. Simple examples illustrate how DEA is useful in formulating coalition models and deriving optimal solutions. In particular, the paper shows the relevance of the proposed framework in the context of analyzing how companies may reach decisions to acquire potential partners.
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    ÍtemAcceso Abierto
    Natural Resources Exchange Traded Funds: Performance Appraisal using DEA Modeling
    (Pontificia Universidad Católica del Perú. CENTRUM, 2011) Tsolas, I. E.
    The purpose of this paper is to evaluate the performance of a sample of natural resources exchange traded funds (ETFs) by applying a two-stage procedure. In the first stage, the generalized proportional distance function (GPDF) in the data envelopment analysis (DEA) context is used for the first time to measure the relative efficiency of sectoral ETFs. In the second stage, a Tobit model is employed to identify the drivers of performance. The results indicate there is scope for efficiency improvement for about half or more of the sample funds depending on the variables used in the assessments, and fund performance can be explained by fund persistence and the beta coefficient.
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    ÍtemAcceso Abierto
    Applying an Efficiency Measure of Desirable and Undesirable Outputs in DEA to U.S. Electric Utilities
    (Pontificia Universidad Católica del Perú. CENTRUM, 2011) Tone, Kaoru; Tsutsui, Miki
    The measure proposed in this paper is a new nonparametric data envelopment analysis (DEA) scheme, the hybrid measure, for determining efficiency in the presence of radial and nonradial inputs or outputs. Further extension of the scheme occurred to address nonseparable desirable and undesirable outputs. Applying the model to measure the overall efficiency of U.S. electric utilities in the presence of both desirable and undesirable outputs indicated that the utilities had improved their overall management and environmental efficiency between 1996 and 2000.
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    ÍtemAcceso Abierto
    Avoiding Large Differences in Weights in Cross-Efficiency Evaluations: Application to the Ranking of Basketball Players
    (Pontificia Universidad Católica del Perú. CENTRUM, 2011) Cooper, William W.; Ramón, Nuria; Ruiz, Jose L.; Sirvent, Inmaculada
    Because of data envelopment analysis (DEA) flexibility in the choice of weights, assessment of decision-making units (DMUs) often involves weighting only a few inputs and outputs and ignoring the remaining variables by assigning them a zero weight. Widespread literature indicates the need to avoid zero weights, and some authors claim that the fact that a given DMU attaches very different weights to the variables involved in the assessments may be a concern (see, for example, Cooper, Seiford, & Tone, 2007). The aim of this paper was to prevent unrealistic weighting schemes in cross-efficiency evaluations through an extension of the multiplier bound approach (Ramón, Ruiz, & Sirvent, 2010a) based on “model” DMUs. The approach in that paper guarantees nonzero weights while at the same time it tries to avoid large differences in the values of multipliers. An application to the ranking of basketball players involved specifying a limit for allowable differences in the relative importance that players attach to different aspects of the game by reflecting those observed in the weight profiles of some model players, which are selected according to expert opinion. The approach provided results that are consistent with basketball expert opinion and illustrated why the classical approaches to cross-efficiency evaluation, which include the benevolent and aggressive formulations, may lead to unreasonable results.
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    ÍtemAcceso Abierto
    Data Envelopment Analysis in the Presence of Partial Input-to-Output Impacts
    (Pontificia Universidad Católica del Perú. CENTRUM, 2011) Cook, W. D.; Imanirad, Raha
    Data envelopment analysis (DEA) is a methodology used to evaluate the relative efficiencies of peer decision-making units (DMUs) in multiple input, multiple output situations. In the original formulation, and in the vast literature that followed, the assumption was that all members of the input bundle affected the output bundle. However, many potential applications of efficiency measurement exist wherein some inputs do not influence certain outputs. For example, in a manufacturing setting from which multiple products (outputs) emerge, resources (e.g., packaging labor) will not affect products that do not pass through that department. For this paper, extension of the conventional DEA methodology allows for the measurement of technical efficiency in situations where only partial input-to-output impacts are evident. Evaluating the efficiencies of a set of steel fabrication plants using the methodology was the focus of the research.
  • Miniatura
    ÍtemAcceso Abierto
    Scale Efficiency Measurement in Data Envelopment Analysis with Interval Data: A Two-Level Programming Approach
    (Pontificia Universidad Católica del Perú. CENTRUM, 2011) Kao, Chiang; Lu, Shiang-Tai
    Conventional data envelopment analysis (DEA) for measuring the relative efficiency of a set of decision-making units (DMUs) requires the observations to have precise values. When observations are imprecise and represented by interval values, the efficiencies are also expected to reflect interval values. Several methods exist to calculate the interval overall and technical efficiencies, but such methods are unable to calculate the interval scale efficiency. The focus of this paper is the application of a two-level programming technique to formulate the problem of determining the bounds of the interval scale efficiency. The associated models are essentially nonlinear programs with only bound constraints for variables in a sophisticated form. Hence, one can modify the conventional quasi-Newton method for unconstrained nonlinear programming problems to solve the two-level programs. Two examples with interval data, one hypothetical and one real, aid in explaining the proposed method and the properties of the results.
  • Miniatura
    ÍtemAcceso Abierto
    Airlines Performance via Two-Stage Network DEA Approach
    (Pontificia Universidad Católica del Perú. CENTRUM, 2011) Zhu, Joe
    The performance of the airline industry has been widely studied using data envelopment analysis (DEA). Many existing DEA-based airline performance studies have used the standard DEA model, with some minor modifications. These studies have ignored the internal structure relative to the measures characterizing airline operations performance. In the current paper, airline performance is measured using a two-stage process. In the first stage, resources (fuel, salaries, and other factors) are used to maintain the fleet size and load factor. In the second stage, the fleet size and load factors generate revenue. The model used is called the centralized efficiency model where two stages are used to optimize performance simultaneously. The approach generates efficiency decomposition for the two individual stages. The use of this centralized DEA model enables obtaining insights not available from the standard DEA approach.