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DCBA-DEA: A Monte Carlo simulation optimization approach for predicting an accurate technical efficiency in stochastic environment

Research output: Contribution to journal › Article › Research › peer-review

Abstract

This article describes a 2-in-1 methodology utilizing simulation optimization technique and Data Envelopment Analysis in measuring an accurate efficiency score. Given the high level of stochastic data in real environment, a novel methodology known as Data Collection Budget Allocation-Data Envelopment Analysis (DCBA-DEA) is developed. An example of the method application is shown in banking institutions. In addition to the novel approach presented, this article provides a new insight to the application domain of efficiency measurement as well as the way one conducts efficiency study.

Original languageEnglish
Pages (from-to)210-220
Number of pages11
JournalIndustrial Engineering and Management Systems
Volume13
Issue number2
DOIs
Publication statusPublished - 1 Jun 2014
Externally publishedYes

Keywords

  • Data collection budget allocation
  • Data Envelopment Analysis (DEA)
  • Simulation optimization

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