A comparative analysis indicates that our method is an effective alternative to the Pastor et al. [12] method to identify influential observations in DEA.
📌 3 Key Takeaways
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Objective & Hypothesis:In data analyses based on a deterministic or stochastic approach, using pre-study is very important to identify observations that are not suitable to data in general.
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Key Findings & Data:Our method is a modified version of the one proposed by Pastor et al. [12].
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Conclusion & Impact:A comparative analysis indicates that our method is an effective alternative to the Pastor et al. [12] method to identify influential observations in DEA.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Data Envelopment Analysis · inuential observations · super efficiency
Abstract
In data analyses based on a deterministic or stochastic approach, using pre-study is very important to identify observations that are not suitable to data in general. Among such observations, those that have a high tendency to change results negatively are called influential observations. In this paper, we propose a new method to identify influential observations in Data Envelopment Analysis (DEA). Our method is a modified version of the one proposed by Pastor et al. [12]. Both methods are compared by using two well-known data sets and the outcomes are discussed. A comparative analysis indicates that our method is an effective alternative to the Pastor et al. [12] method to identify influential observations in DEA.
ACARLAR, İ., TEKİN, S. T. Ş., ÖRKCÜ, H. H. (2018). A modified test for detecting influential decision-making units in data envelopment analysis. Hacettepe Journal of Mathematics and Statistics, Cilt: 47 - Sayı: 1, 129–144. https://ajindex.com/articles/669448
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