Journal of CENTRUM Cathedra
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Item Open Access 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, InmaculadaBecause 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.Item Open Access 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, MikiThe 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.Item Unknown Data Envelopment Analysis in the Presence of Partial Input-to-Output Impacts(Pontificia Universidad Católica del Perú. CENTRUM, 2011) Cook, W. D.; Imanirad, RahaData 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.Item Unknown 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-TaiConventional 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.Item Open Access Airlines Performance via Two-Stage Network DEA Approach(Pontificia Universidad Católica del Perú. CENTRUM, 2011) Zhu, JoeThe 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.