Equivalences between Data Envelopment Analysis and the theory of redundancy in linear systems
✍ Scribed by J.H. Dulá
- Publisher
- Elsevier Science
- Year
- 1997
- Tongue
- English
- Weight
- 971 KB
- Volume
- 101
- Category
- Article
- ISSN
- 0377-2217
No coin nor oath required. For personal study only.
✦ Synopsis
This paper establishes how the non-parametric frontier estimation methodology of Data Envelopment Analysis (DEA) and the classical problem of detecting redundancy in a system of linear inequalities are connected. We present an analysis of the sets generated in two of DEA's models from where the empirical efficient production frontier is established from the point of view of polyhedral set theory. This yields convenient alternative characterizations of these sets which provide new insights about their properties. We use these insights to show how these polyhedral sets connect DEA to redundancy in linear systems. This means that DEA can benefit from a rich and well-established collection of computational and theoretical results which apply directly from redundancy in linear systems.
📜 SIMILAR VOLUMES
Data envelopment analysis (DEA), a non-parametric productivity analysis, has become an accepted approach for assessing efficiency in a wide range of fields. Despite its extensive applications, some features of DEA remain unexploited. We aim to show that DEA can be used to evaluate the efficiency of