World Scientific-now publishers Series in Business > Advances in Data Envelopment Analysis

Advances in Data Envelopment Analysis

Rolf Färe, Oregon State University, USA, Shawna Grosskopf, Oregon State University, USA, Dimitris Margaritis, University of Auckland, New Zealand,
Published: 01 Mar 2015
© 2015 R. Färe, S. Grosskopf and D. Margaritis
 
Subjects
Supply Chain Management
 
Keywords
Optimization TechniquesMultifactor ProductivityIntertemporal Firm Choiceechnological Change: Choices and ConsequencesDiffusion ProcessesData Envelopment AnalysisOperations Research
 
Table of contents:
Introduction
1. Looking at the Data in DEA
2. DEA and Intensity Variables
3. DEA and Directional Distance Functions
4. DEA and Time Substitution
5. Some Limitations of Two DEA Models

Advances in Data Envelopment Analysis

Data Envelopment Analysis (DEA) is often overlooked in empirical work such as diagnostic tests to determine whether the data conform with technology which, in turn, is important in identifying technical change, or finding which types of DEA models allow data transformations, including dealing with ordinal data. Advances in Data Envelopment Analysis focuses on both theoretical developments and their applications into the measurement of productive efficiency and productivity growth, such as its application to the modelling of time substitution, i.e. the problem of how to allocate resources over time, and estimating the "value" of a Decision Making Unit (DMU).

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