Impacts of random noise and specification on estimates of capacity derived from data envelopment analysis
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Publication:5956200
DOI10.1016/S0377-2217(01)00087-XzbMath1018.90504OpenAlexW2161678090MaRDI QIDQ5956200
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Publication date: 16 September 2002
Published in: European Journal of Operational Research (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/s0377-2217(01)00087-x
Monte Carlo methods (65C05) Management decision making, including multiple objectives (90B50) Case-oriented studies in operations research (90B90)
Related Items (11)
Nonparametric measures of scale economies and capacity utilization: an application to U.S. manufacturing ⋮ A Monte Carlo study of old and new frontier methods for efficiency measurement ⋮ Benchmarking the benchmarks -- comparing the accuracy of data envelopment analysis models in constant returns to scale settings ⋮ Analyzing the accuracy of variable returns to scale data envelopment analysis models ⋮ Peer-judgment risk minimization using DEA cross-evaluation with an application in fishery ⋮ Testing Positive Endogeneity in Inputs in Data Envelopment Analysis ⋮ Measuring the capacity utilization of the 48 largest iron and steel enterprises in China ⋮ Methodology for calculating critical values of relevance measures in variable selection methods in data envelopment analysis ⋮ Alternative approaches to include exogenous variables in DEA measures: A comparison using Monte Carlo ⋮ Performance estimation when the distribution of inefficiency is unknown ⋮ How to generate regularly behaved production data? A Monte Carlo experimentation on DEA scale efficiency measurement
Cites Work
- Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis
- Measuring the efficiency of decision making units
- A Monte Carlo comparison of two production frontier estimation methods: Corrected ordinary least squares and data envelopment analysis
- Model misspecification in data envelopment analysis
- On the quality of the data envelopment analysis model
- Measuring Plant Capacity, Utilization and Technical Change: A Nonparametric Approach
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