利润最大化是生产经营性企业的追求目标。对于社会公共服务部门、科研单位等非赢利性机构而言,虽然利润最大化不是其追求目标,但由于规模效益问题涉及资源配置,资源使用效率等问题,所以至关重要。数据包络分析方法(DEA)是基于经济学概念上发展起来的非参数定量分析方法,可以提供决策单元规模效益变化的信息,因此可以用来对非赢利性公共部门或科研机构的分析。我们改进了标准DEA模型以克服其某些局限性,在实际应用中又与评估者的评估策略和价值导向相结合。作为应用实例,我们对某科研机构的34个研究组的规模效益进行了分析和探讨。

The profit-maximization is always the main target for enterprises. For those not-for-profit organizations, such as public sectors and research institutions, although profit is not the key objective, it is still important for decision makers to know its scale-efficiency in order to maximize the utility of limited resources. DEA is a non-parametric method to measure relative efficiency of Decision Making Units (DMUs) with multiple inputs and multiple outputs. And DEA provides information about scale efficiency changing, especially for those not-for-profit institutions. In this paper, new DEA models are presented in which some limitations of standard DEA models have been overcome and decision makers' value judgment can be adopted more directly. The results for scale efficiency of research groups of one research institute are presented as a case study.