Efficiency decomposition in network data envelopment analysis: A relational model

Research output: Contribution to journalArticle

256 Citations (Scopus)

Abstract

Traditional studies in data envelopment analysis (DEA) view systems as a whole when measuring the efficiency, ignoring the operation of individual processes within a system. This paper builds a relational network DEA model, taking into account the interrelationship of the processes within the system, to measure the efficiency of the system and those of the processes at the same time. The system efficiency thus measured more properly represents the aggregate performance of the component processes. By introducing dummy processes, the original network system can be transformed into a series system where each stage in the series is of a parallel structure. Based on these series and parallel structures, the efficiency of the system is decomposed into the product of the efficiencies of the stages in the series and the inefficiency slack of each stage into the sum of the inefficiency slacks of its component processes connected in parallel. With efficiency decomposition, the process which causes the inefficient operation of the system can be identified for future improvement. An example of the non-life insurance industry in Taiwan illustrates the whole idea.

Original languageEnglish
Pages (from-to)949-962
Number of pages14
JournalEuropean Journal of Operational Research
Volume192
Issue number3
DOIs
Publication statusPublished - 2009 Feb 1

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Relational Model
Data envelopment analysis
Data Envelopment Analysis
Decomposition
Decompose
Series
Insurance
Series System
Relational model
Taiwan
Industry

All Science Journal Classification (ASJC) codes

  • Modelling and Simulation
  • Management Science and Operations Research
  • Information Systems and Management

Cite this

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Efficiency decomposition in network data envelopment analysis : A relational model. / Kao, Chiang.

In: European Journal of Operational Research, Vol. 192, No. 3, 01.02.2009, p. 949-962.

Research output: Contribution to journalArticle

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