DEA model with shared resources and efficiency decomposition
DEA model with shared resources and efficiency decomposition
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DOI：
10.1016/j.ejor.2010.03.031
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发表时间：
2010-11-16
影响因子：
6.4
通讯作者：
Zhu, Joe
中科院分区：
文献类型：
--
作者：
Chen, Yao;Du, Juan;Zhu, Joe
数据包络分析 (DEA) 已被证明是衡量使用多个输入生成多个输出的决策单元 (DMU) 性能的绝佳方法。在许多现实世界的场景中。 DMU 具有两阶段网络过程，在两个操作阶段使用共享输入资源。例如，在医院运营中，第一阶段使用设备、人员和信息技术等一些输入资源来生成病历，以跟踪治疗、检查、药物剂量和费用。第一阶段活动使用的同一组资源用于生成第二阶段的患者服务。患者服务还使用第一阶段运营产生的家政、医疗记录和洗衣服务。这些 DMU 不仅具有输入和输出，还具有存在于两阶段操作之间的中间措施。其显着特点是，第一阶段的一些输入由第一阶段和第二阶段共享，但是一些共享输入不能方便地拆分并分配给两个阶段的操作。认识到这种区别对于这些类型的 DEA 应用至关重要，因为如果 DEA 未能考虑到某些输入会产生其他第二阶段输出，那么测量第一阶段输出的生产效率可能会产生误导，并且可能会低估效率。当前的论文开发了一组 DEA 模型，用于测量具有不可分割共享输入的两阶段网络过程的性能。提出了两阶段网络过程的加性效率分解。这些模型是在可变规模收益 (VRS) 假设下开发的，但也可以在恒定规模收益 (CRS) 假设下轻松应用。提供了一个应用程序。 (C) 2010 Elsevier B.V. 保留所有权利。
Data envelopment analysis (DEA) has proved to be an excellent approach for measuring performance of decision making units (DMUs) that use multiple inputs to generate multiple outputs. In many real world scenarios. DMUs have a two-stage network process with shared input resources used in both stages of operations. For example, in hospital operations, some of the input resources such as equipment, personnel, and information technology are used in the first stage to generate medical record to track treatments, tests, drug dosages, and costs. The same set of resources used by first stage activities are used to generate the second-stage patient services. Patient services also use the services generated by the first stage operations of housekeeping, medical records, and laundry. These DMUs have not only inputs and outputs, but also intermediate measures that exist in-between the two-stage operations. The distinguishing characteristic is that some of the inputs to the first stage are shared by both the first and second stage, but some of the shared inputs cannot be conveniently split up and allocated to the operations of the two stages. Recognizing this distinction is critical for these types of DEA applications because measuring the efficiency of the production for first-stage outputs can be misleading and can understate the efficiency if DEA fails to consider that some of the inputs generate other second-stage outputs. The current paper develops a set of DEA models for measuring the performance of two-stage network processes with non splittable shared inputs. An additive efficiency decomposition for the two-stage network process is presented. The models are developed under the assumption of variable returns to scale (VRS), but can be readily applied under the assumption of constant returns to scale (CRS). An application is provided. (C) 2010 Elsevier B.V. All rights reserved.