Method of benchmarking route choice based on the input similarity using DEA

Jaehun Park, Hyerim Bae, Sungmook Lim

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

Abstract

Benchmarking requires an effective methodology for finding the best performer, which entails an evaluation of the relative efficiencies of competitors in terms of multiple input and output factors. To identify the best performer, Data Envelopment Analysis (DEA) has been popularly used. However, the conventional DEA has some deficiencies with respect to its use for benchmarking. First, the reference set of an inefficient DMU often has multiple efficient DMUs. Second, it might be quite impossible for an inefficient DMU to achieve its target's efficiency in a single step, especially when the target is far removed from the DMU. To overcome these deficiencies of conventional DEA, we propose a new stepwise benchmarking method using DEA, which enables inefficient DMUs to select the more appropriate benchmarking DMU based on the similarity.

Original languageEnglish
Title of host publicationIntelligent Decision Technologies - Proceedings of the 3rd International Conference on Intelligent Decision Technologies, IDT'2011
Pages519-528
Number of pages10
DOIs
StatePublished - 2011
Event3rd International Conference on Intelligent Decision Technologies, IDT'2011 - Piraeus, Greece
Duration: 20 Jul 201122 Jul 2011

Publication series

NameSmart Innovation, Systems and Technologies
Volume10 SIST
ISSN (Print)2190-3018
ISSN (Electronic)2190-3026

Conference

Conference3rd International Conference on Intelligent Decision Technologies, IDT'2011
Country/TerritoryGreece
CityPiraeus
Period20/07/1122/07/11

Keywords

  • Benchmarking
  • Data envelopment analysis
  • K-means clustering

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