Data Envelopment Analysis: Stochastic Approaches to Data Envelopment Analysis

By Subhash C. Ray. 2004

648 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/33aab02cbe755bae0034fb7b36164da8bcc0e6f8

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Citations in the corpus

Bank supervision, regulation, and efficiency: evidence from the European Union (2012, background): “Yy Xxst Min i i (1) 4 For a systematic introduction to DEA methodology, see among others, Ray (2004). where is a scalar, is a vector of ones and finally X and Y are the input and output matrices respectively.”
Environmental efficiency of the Indian cement industry: An interstate analysis (2010, background): “2 For a detailed exposition of DEA, see Ray, 2004 and Coelli et.al.”
Plural forms versus franchise and company-owned systems: A DEA approach of hotel chain performance (2009, background): “For a comprehensive exposition of these assumptions, the reader may refer to Ray [40] and Coelli et al.”
Estimation and inference in two-stage, semi-parametric models of production processes (2007, background): “This approach is advocated by Chilingerian and Sherman (2004), Ray (2004), and Ruggiero (2004); published examples include Byrnes et al. (1988), Ray (1988, 1991), Nyman and Bricker (1989), Aly et al. (1990), McCarty and Yaisawarng (1993), Rhodes and Southwick (1993), Banker and Johnston (1994),…”
Affirmative Action and Productivity in the Indian Railways (2016, background): “There is clearly no support here for the claim that higher 2 For a thorough explication of the DEA approach, see Ray (2004). proportions of SCST employees result in slower growth in TFP.”
Financial deregulation and profit efficiency: A nonparametric analysis of Indian banks (2009, methodology): “Based on nonparametric approach, Rammohan and Ray (2004) and Das et al. (2005) compared the various efficiency measures of banks across different ownership groups during the post liberalization period.”
DEA models with undesirable inputs and outputs (2010, background): “It is also possible to derive DEA models to handle undesirable data via replacing Strong Disposability of outputs by the assumptions that the outputs are weakly disposable while only the sub-vector of the desirable outputs is strongly disposable (e.g. Färe and Grosskopf 2004; Ray 2004).”
A new benchmarking approach in Cold Chain (2012, methodology): “The following mixed integer programming formulation is the basic output-oriented FDH model [47].”