数据包络分析
收入
标杆管理
背景(考古学)
阶段(地层学)
集合(抽象数据类型)
运筹学
计量经济学
计算机科学
群(周期表)
数学优化
经济
微观经济学
业务
数学
营销
财务
古生物学
有机化学
化学
生物
程序设计语言
作者
Wade D. Cook,Chuanyin Guo,Wanghong Li,Zhepeng Li,Liang Liang,Joe Zhu
标识
DOI:10.1142/s0217595917500324
摘要
An important area of research involving the benchmarking methodology data envelopment analysis (DEA), concerns the modeling of multistage situations. In the usual multistage settings, it is generally assumed that all decision-making units (DMUs) have the same number and configuration of stages. However, in many real-world examples, this assumption does not hold. Consider, for example, a supply chain setting where for some DMUs, products are shipped directly from a supplier to a retailer (single-stage), while for other DMUs, products can be transshipped through distribution centers (two or more stages). In the current paper, we investigate an efficiency measurement situation where the DMUs exhibit a mix of single and two-stage setups. The particular case examined involves a set of high technology firms that can be thought of as falling into two groups; those firms where the output of interest is the annual revenue generated, and those that not only generate revenue, but as well invest a portion of that revenue in R&D. Firms in the first group can be viewed as being single-stage DMUs while those in the other group are of the two-stage type. The modeling complication here is that the set of DMUs do not explicitly form a homogeneous set of units. We develop a DEA-style model aimed at measuring efficiency in the presence of such nonhomogeneous two-group structures.
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