Scholarlink

<p>Considering internal operation of decision-making unit (DMU) while introducing technical heterogeneity is the advantage of two-stage meta-frontier data envelopment analysis (DEA) method. However, each DMU can obtain double shared ratios in different technical environments, and each DMU must ultimately determine one shared ratio under actual decision-making, which leads to a decision-making dilemma of two-stage meta-frontier DEA in application. Therefore, based on traditional shared ratio selection, some double shared ratio selection methods of dominant, autonomous and coordinated are proposed for different decision-making needs, which promote deep integration of meta-frontier and two-stage DEA, and thus provide clear and specific shared ratio selections for decision makers. In addition, to overcome the limitations of double shared ratio selection, this paper takes double shared ratios as a selection interval and further extends double shared ratio selection methods, enhancing the flexibility of shared ratio selection. Furthermore, different double shared ratio selections are divided into uniform and non-uniform for comparative analysis. This paper indicates that: (1) The degree of concentration in DMU shared ratio selection is positively correlated with efficiency. (2) Unifying the shared ratios for meta-frontier and group frontier is beneficial for improving overall efficiency level.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Double shared ratio selection of two-stage meta-frontier DEA methods based on shared input

  • 期刊论文

  • 发表日期：

    2025年6月10日

查看全文
  • Xu Guo,
  • Lei Chen

摘要

Considering internal operation of decision-making unit (DMU) while introducing technical heterogeneity is the advantage of two-stage meta-frontier data envelopment analysis (DEA) method. However, each DMU can obtain double shared ratios in different technical environments, and each DMU must ultimately determine one shared ratio under actual decision-making, which leads to a decision-making dilemma of two-stage meta-frontier DEA in application. Therefore, based on traditional shared ratio selection, some double shared ratio selection methods of dominant, autonomous and coordinated are proposed for different decision-making needs, which promote deep integration of meta-frontier and two-stage DEA, and thus provide clear and specific shared ratio selections for decision makers. In addition, to overcome the limitations of double shared ratio selection, this paper takes double shared ratios as a selection interval and further extends double shared ratio selection methods, enhancing the flexibility of shared ratio selection. Furthermore, different double shared ratio selections are divided into uniform and non-uniform for comparative analysis. This paper indicates that: (1) The degree of concentration in DMU shared ratio selection is positively correlated with efficiency. (2) Unifying the shared ratios for meta-frontier and group frontier is beneficial for improving overall efficiency level.