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

  • Authors:

  • Ching-Kuo Wei;Liang-Chih Chen;Rong-Kwei Li;Chih-Hung Tsai;Hsiao-Ling Huang

  • Affiliations:

  • Department of Health Care Administration, Oriental Institute of Technology, 58, Sec. 2, Sihchuan Rd., Pan-Chiao City, Taipei County 22061, Taiwan;Department of Industrial Engineering and Management, National Chiao-Tung University, Hsinchu, Taiwan;Department of Industrial Engineering and Management, National Chiao-Tung University, Hsinchu, Taiwan;Department of Information Management, Yuanpei University, No. 306, Yuanpei Street, Hsin-Chu, Taiwan;Department of Healthcare Management, Yuanpei University, No. 306, Yuanpei Street, Hsin-Chu, Taiwan

  • Venue:
  • Expert Systems with Applications: An International Journal
  • Year:
  • 2012

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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.