Author: | Rolf Färe, Shawna Grosskopf, Dimitris Margaritis | ISBN: | 9789814644563 |
Publisher: | World Scientific Publishing Company | Publication: | March 26, 2015 |
Imprint: | WSPC/NOW | Language: | English |
Author: | Rolf Färe, Shawna Grosskopf, Dimitris Margaritis |
ISBN: | 9789814644563 |
Publisher: | World Scientific Publishing Company |
Publication: | March 26, 2015 |
Imprint: | WSPC/NOW |
Language: | English |
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).
Contents:
Acknowledgements
Preface
Introduction:
Looking at the Data in DEA:
DEA and Intensity Variables:
DEA and Directional Distance Functions:
DEA and Time Substitution:
Some Limitations of Two DEA Models:
References
Readership: Advanced postgraduate students and researchers in operations research and economics with a particular interest in production theory and operations management.
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).
Contents:
Acknowledgements
Preface
Introduction:
Looking at the Data in DEA:
DEA and Intensity Variables:
DEA and Directional Distance Functions:
DEA and Time Substitution:
Some Limitations of Two DEA Models:
References
Readership: Advanced postgraduate students and researchers in operations research and economics with a particular interest in production theory and operations management.