(2006) Chapter 2: Data Envelopment Analysis explained. In: Service Productivity Management, Improving Service Performance using Data Envelopment Analysis (DEA), Springer.Sherman, H.D. and Zhu, J. (2006) Data Envelopment Analysis Explained. Service Productivity Management Improving Service Performance ...
This research employs data envelopment analysis (DEA) to evaluate R&D efficiency of electronic initial public offerings firms (IPOs) and investigates the relation between R&D efficiency and the long-term performance of those companies. Our empirical result shows that the absence of pure technical ...
This is explained visually in Fig. 1. Download: Download high-res image (214KB) Download: Download full-size image Fig. 1. Software architecture of boostingDEA. 2.2. Software functionalities In the data envelopment analysis context, the productivity and economic performance of a set ℵ of i=...
but are not limited, to: Bayesian stochastic frontier analysis; network Data Envelopment Analysis; quantile regression; hyperbolic measurement; fuzzy super-
Data Envelopment Analysis (DEA) is a popular non-parametric tool for measuring the efficiency of a set of Decision-Making Units (DMU) in organizations employing multiple inputs to produce multiple outputs. Although, conventional DEA models introduced by Charnes et al. [11] and extended by Banker...
Data Envelopment Analysis (DEA) is one of the techniques that provides to evaluate many different input and output factors together. In this study, the information has been given about Data Envelopment Analysis, the mathematical process has been explained,the literature review has been made and the...
Based on available data from 64 countries over the world, the author tried to evaluate the effectiveness of the banking sectors in those countries through the view point of the data envelopment analysis approach to define how the global banking systems is under the effect of the current crisis....
This study aims to assess the efficiency of TOD by applying the data envelopment analysis (DEA) method. The ridership of public transportation is considered as the direct output characteristic of TOD efficiency, and nine indicators of ridership are selected as inputs on the basis of the core ...
In the context of two-stage data envelopment analysis (DEA) for efficiency correction, we shift the focus from the common central tendency orientation in its second stage to an individually oriented procedure. We propose to evaluate the influence of contextual variables on each unit's performance ...
The non-Archimedean epsilonεis commonly considered as a lower bound for the dual input weights and output weights in multiplier data envelopment analysis (DEA) models. The amount ofεcan be effectively used to differentiate between strongly and weakly efficient decision making units (DMUs). The pr...