考虑非期望产出复杂特性的DEA效率评价理论、方法及应用研究

Data envelopment analysis (DEA) is a very important tool for efficiency evaluation and improvement of decision-making units (DMUs). Efficiency assessment considering undesired output is a research focus of DEA. The existing literature of DEA methods with undesirable outputs involves few types of undesirable outputs and rarely considers the relations among undesirable outputs. It results in that the efficiency evaluation of DMUs with complex undesirable outputs in reality cannot be solved. In this project, the complexity of undesirable outputs is considered. Firstly, we define three main characteristics of undesirable outputs complexity as diversity, interdependency and heterogeneity, and study the impact of these characteristics on the efficiency evaluation and efficiency improvement. Secondly, a set of DEA models will be constructed for evaluating efficiency of DMUs with each characteristic, of which the feasibility and effectiveness will be demonstrated. Finally, the proposed models and methods will be employed to an empirical study on transportation efficiency evaluation with complex undesirable outputs to verify their effectiveness. This project will improve the current DEA methods to be applied in real situation, and provide supports for assessing the efficiency of DMUs considering complex undesirable outputs.

数据包络分析（DEA）是对决策单元进行效率评价和改进的重要研究方法，而含有非期望产出的决策单元效率评价更是DEA的热点研究领域。该领域现有的DEA理论方法对不同非期望产出性质刻画较为简单，且忽略了它们之间的关系，无法有效解决现实中具有非期望产出复杂特性的决策单元效率评价问题。本项目以非期望产出复杂特性为切入点开展如下研究：1）从现实问题中抽象出几种关键的非期望产出复杂特性表现，将其刻画分类为多样性、关联性及异质性特征，研究其对效率评价和效率改进的影响机理；2）分别研究考虑每一种特征的DEA效率评价与效率改进方法，构建系统的DEA模型和方法体系，并论证其可行性和科学性；3）将模型和方法应用于运输业效率评价及非期望产出治理，以验证其有效性。本项目将对现有DEA体系进行补充和完善，推进DEA理论方法发展和应用实践，并为现实中考虑非期望产出复杂特性的决策单元效率评价、效率改进和管理决策提供支持。

数据包络分析（DEA）是对决策单元进行效率评价和改进的重要研究方法，而含有非期望产出的决策单元效率评价更是DEA的热点研究领域。该领域现有的DEA理论方法对不同非期望产出性质刻画较为简单，且忽略了它们之间的关系，无法有效解决现实中具有非期望产出复杂特性的决策单元效率评价问题。本项目结合DEA方法、门槛效应、方向性距离函数等方法，对考虑非期望复杂特性的效率评价方法和应用进行了研究。首先，在对非期望产出的多样性、异质性等特性进行刻画方面，将非期望产出的多样性嵌入到DEA效率评价模型，丰富了DEA效率评价非期望产出指标的选择；其次，在对非期望产出与期望产出之间的关联性进行研究时，从二者关联角度提出了非期望产出弱可处置程度系数的确定方法，并构建了考虑费期望产出弱可处置程度的DEA效率评价模型，突破了对非期望产出强弱可处置性的二元设置；最后，将含有多种非期望产出的静态和动态模型，应用于我国公路运输业效率评价和旅游业效率评价，为行业提质增效提供了管理启示。.围绕上述研究内容，在本项目执行期内，课题组在《Energy》、《Science of the Total Environment》、《Environmental Science and Pollution Research》、《Journal of Cleaner Production》、《Journal of Hospitality & Tourism Research》、《统计与决策》等国际和国内核心期刊发表标注基金号的学术论文共计13篇，其中SCI/CSSCI收录期刊论文10篇，CSSCI收录期刊论文3篇。项目完成了预期的目标和任务，研究工作加深了对非期望产出特性在效率评价中所起作用的理解，推进了DEA方法在环境效率评价领域的应用。