A study of optimal weights of Data Envelopment Analysis - Development of a context-dependent DEA-R model

Ching Kuo Wei, Liang Chih Chen, Rong-Kwei Li, Chih Hung Tsai*, Hsiao Ling Huang

*Corresponding author for this work

Research output: Contribution to journalArticle

11 Scopus citations

Abstract

The weight is one of the main issues of Data Envelopment Analysis (DEA), and relevant theoretical research indicates that many DEA mathematical models include redundant restraints on weight, resulting in underestimated efficiency, pseudo inefficiency, and difficulty in representing specific Input/Output relationships. This study proposes a context-dependent DEA-R model to address shortcomings resulting from redundant restraints on the weights of an efficient decision making unit (DMU), and converts the optimal weight to analyze the influences of redundant restraints on weights. The evaluation results of Taiwan medical centers show that the efficiency of the DMU is underestimated and pseudo inefficiency may occur due to redundant restraints on weight. Moreover, optimal weights are used as variables to conduct cluster analysis in order to determine the information of the weights. The results of cluster analysis indicate that it can assist DMUs in understanding the relationships between DMUs, and contribute to the development of a unique survival strategy for hospitals.

Original languageEnglish
Pages (from-to)4599-4608
Number of pages10
JournalExpert Systems with Applications
Volume39
Issue number4
DOIs
StatePublished - 1 Mar 2012

Keywords

  • Cluster analysis
  • Context-dependent
  • Data Envelopment Analysis
  • Medical center
  • Redundant restraints on weight

Fingerprint Dive into the research topics of 'A study of optimal weights of Data Envelopment Analysis - Development of a context-dependent DEA-R model'. Together they form a unique fingerprint.

  • Cite this