基于DEA测度的学术期刊综合评价方法及应用研究

The evaluation of academic journals has always been one of the focuses for academic researchers and many industries. The existing academic journals have a wide range of evaluation indicators and many viewpoints, and it is difficult to give a uniform evaluation result for journals. Therefore, there is an urgent need for a comprehensive journal evaluation measure that can be widely accepted. As an important evaluation tool, data envelopment analysis (DEA) method can effectively give an objective comprehensive assessment of the relative performance of decision-making units with multidimensional evaluation indicators. Therefore, the project systematically introduces the DEA method to study the evaluation problems of academic journals under different typical characteristics. First of all, we character the relevance and importance of evaluation indicators, which enriches the theoretical research on the evaluation index system of academic journals, and lays the foundation for the evaluation of academic journals. Second, according to the characteristics of academic journals, it is divided into three typical characteristics named non-homogeneous, dynamic, and business networks. On the basis of non-homogeneous DEA, dynamic DEA and network DEA, we carry out research on evaluation of academic journals under the each typical characteristic. Finally, the study of journal evaluation and performance improvement are carried out in the context of Chinese academic journals. This project study will further enrich the comprehensive measurement methods for academic journal evaluation and provide relevant decision-makers with valuable decision-making information and theoretical references.

学术期刊评价一直以来都是学界和业界关注的焦点问题之一。现有学术期刊评价指标种类繁多、视角众多，难以给出统一的期刊评价结果。因此现实中迫切需要一种能够被广泛认可的综合性期刊评价测度。数据包络分析（DEA）方法作为一种重要的评价工具，可以有效地对多维评价指标下的决策单元相对表现给出客观的综合性评价。因此，本项目系统引入DEA方法研究不同典型特征下学术期刊的评价问题。首先，刻画评价指标相关性和重要性，丰富学术期刊评价指标体系理论研究，为学术期刊评价奠定基础；其次，根据学术期刊特点，划分为非同质性、动态性、业务网络性三大典型特征，并分别在非同质DEA、动态DEA和网络DEA等方法基础上开展不同典型特征下的学术期刊评价测度研究；最后，以我国学术期刊为背景开展期刊评价、绩效改进等问题研究。本项目研究将进一步丰富学术期刊评价的综合性测度方法，为相关主体提供有价值的决策信息和理论借鉴。

学术期刊评价一直以来都是学界和业界关注的焦点问题之一。现有学术期刊评价指标种类繁多、视角众多，难以给出统一的期刊评价结果。数据包络分析（DEA）方法作为一种重要的评价工具，可以有效地对多维评价指标下的决策单元相对表现给出客观的综合性评价。因此，本项目系统引入DEA方法研究不同典型特征下学术期刊的评价问题。首先，开展学术期刊评价指标体系理论研究，为学术期刊评价奠定基础；其次，根据学术期刊运营特点，划分为异质性、动态性、网络性三大典型特征，基于DEA方法开展不同典型特征下的效率评价研究；最后，基于所提出的方法对学术期刊等领域开展应用研究。. 本项目研究成果主要包括：（1）科技期刊质量评价指标研究。重点围绕基于引文分析的科技期刊质量评价指标进行研究，对科技期刊学术质量评价指标创新提出有针对性的建议。（2）效率评价方法研究。分别从非同质性、动态性、网络性三大科技期刊运营典型特征出发，开展DEA效率评价方法研究，并将其应用到不同领域中，这些方法在科技期刊领域同样适用。（3）资源配置方法研究。基于博弈论、DEA等理论和方法，开展动态博弈资源配置方法研究。该研究是一种基础方法研究，可以应用于科技期刊资源配置问题之中。. 项目研究进展总体正常，已在国内外管理学主流期刊《Environmental Science and Pollution Research》、《Journal of Systems Science and Systems Engineering》、《Journal of Systems Science and Complexity》等发表（含录用）论文4篇（均为项目标注论文），其中SCI/SSCI检索论文3篇，CSCD检索论文1篇。另有部分受资助的工作正处于审稿状态；协助培养学生6名，多次参加高水平国际学术会议并以参与了《FMS管理科学高质量期刊推荐列表》的制订。