Stochastic efficiency measures for production units with correlated data

Chiang Kao, Shiang Tai Liu

Research output: Contribution to journalArticle

Abstract

While the real world is stochastic in nature, in many cases deterministic data envelopment analysis (DEA) models are used to measure the relative efficiency of a set of production units for simplicity. However, deterministic DEA models are not able to differentiate efficient units. More seriously, the decision maker will be over-confident with the presumably uncertain and probably misleading results. By applying a standard normal transformation, this paper develops a stochastic DEA model which is able to take the correlation between the input/output factors of each production unit to be evaluated into account to obtain the distribution of the stochastic efficiency. The efficiency distribution is more discriminative and informative than the single-valued efficiency, in that the probability that the stochastic efficiency of a unit is greater than that of another unit can be calculated. The case of twenty-five Taiwanese commercial banks discussed in a previous study that assumed the input/output factors to be independent is used to illustrate the characteristics of different models. The data is shown to be correlated, and the results confirm that ignoring the correlations between the input/output factors in measuring efficiency obtains misleading rankings.

LanguageEnglish
Pages278-287
Number of pages10
JournalEuropean Journal of Operational Research
Volume273
Issue number1
DOIs
Publication statusPublished - 2019 Feb 16

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Correlated Data
Data Envelopment Analysis
Data envelopment analysis
Unit
Output
Relative Efficiency
Single valued
Differentiate
Model
Simplicity
Ranking
Efficiency measures

All Science Journal Classification (ASJC) codes

  • Computer Science(all)
  • Modelling and Simulation
  • Management Science and Operations Research
  • Information Systems and Management

Cite this

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Stochastic efficiency measures for production units with correlated data. / Kao, Chiang; Liu, Shiang Tai.

In: European Journal of Operational Research, Vol. 273, No. 1, 16.02.2019, p. 278-287.

Research output: Contribution to journalArticle

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