The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Chance Constrained Efficiency Evaluation
Abstract
A model for efficiency evaluation based upon the theory of chance constrained programming is developed. The model uses a piecewise linear envelopment of confidence regions for observed stochastic multiple-input multiple-output combinations in the Data Envelopment Analysis (DEA) tradition. The model allows for an exogenous decomposition of the total variation in data for each Decision Making Unit (DMU). By varying certain probability levels the model can provide estimates of the sensitivity of efficiency scores regarding an unknown amount of noise in date. An application of the method in an evaluation of the research activities in economic departments at Danish Universities is presented.
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Citations
Cites
Maximum likelihood estimation of econometric frontier functions
Greene, W. H. (1980) · Journal of Econometrics · doi:10.1016/0304-4076(80)90041-x · Cited by 704
Cited by
Economic Efficiency and Frontier Techniques
Murillo‐Zamorano, L. R. (2004) · Journal of Economic Surveys · doi:10.1111/j.1467-6419.2004.00215.x · Cited by 465
Trajectories of efficiency measurement: A bibliometric analysis of DEA and SFA
Lampe, H. W., & Hilgers, D. (2015) · European Journal of Operational Research · doi:10.1016/j.ejor.2014.04.041 · Cited by 332
Statistical inference and nonparametric efficiency: A selective survey
Grosskopf, S. (1996) · Journal of Productivity Analysis · doi:10.1007/bf00157039 · Cited by 289
Metadata
- Authors
- Olesen, O. B., & Petersen, N. C.
- Venue
- Management Science
- Published
- 1995-03
- Volume
- 41
- Issue
- 3
- Pages
- 442-457
- ISSN
- 0025-1909 (ISSN-L)
- 1526-5501
- OpenAlex
- W2104419632
- Cited by
- 336
- References
- 1
- FWCI
- 10.17
- Type
- journal article
- Language
- en
- Open access
- closed
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- Olesen, O. B., & Petersen, N. C. (1995). Chance Constrained Efficiency Evaluation. Management Science. https://doi.org/10.1287/mnsc.41.3.442
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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