| Objective:The purpose of this study is to explore a more perfect dynamic selection model for peer review experts of scientific research projects,and to design corresponding expert selection strategies.Methods:(1)Literature research:Search CNKI database,Wanfang database,SpringerLink database and other Chinese and foreign databases,consult the literature related to this study,collect and collate the indicators suitable for expert database,and study its application strategy.(2)Expert Meeting:Demonstrating the index of expert database construction and discussing its application strategy,discussing the dynamic selection model of peer review experts in theory and practical application.(3)Empirical research:Based on the existing expert database information of "Initial Project Fund",this study evaluates the scientificity of the peer review expert dynamic selection model and improves its application strategy.Empirical data are used to test the feasibility of the peer review expert dynamic selection model and improve it.(4)Data processing,index calculation,basic statistical description and statistical test are completed by SAS 9.4 statistical analysis software,and chart making is completed by Microsoft Excel 2013 and SPSS Clementine 20.0 software.Results:(1)The index of expert database was sorted out and selected.The index of expert database was divided into peer review index and academic professional index.Through analysis and comparison,this study selected 7 peer review indicators based on cumulative horizontal dispersion rate and consistency coefficient from 14 indicators of the previous research results of the research group;through literature research and expert meetings,6 academic and professional indicators based on H index and domain impact factor were selected from 9 indicators.(2)The strategy of using the index of expert database is divided into two kinds:introduction of single index function and comprehensive application.Functions of individual indicators:cumulative horizontal dispersion rate is used to explain the consistency of experts’scores,consistency coefficient is used to explain the consistency of experts’ votes,h index is used to explain the overall academic achievements and academic influence of experts,and domain influence factor is used to explain the research fields of experts and their academic achievements and academic influence in this field;in addition to the above four main indicators,There are also nine auxiliary selection indicators to supplement the characteristics of experts.Comprehensive application:After the comparison of empirical data,there is no significant difference in the results of comprehensive evaluation between rank sum ratio method and Topsis method,but rank sum ratio method is simpler,so rank sum ratio method is selected for the comprehensive application of indicators.Thirteen indicators of expert database are in the process of "selecting experts with big peers" and"selecting experts with small peers".Under the three different situations of evaluating the topic of "unknown/frontier field",different indicators are selected to be combined,and rank sum ratio method is used to make comprehensive selection.(3)Empirical research collates 7960 evaluation data of a fund project in 2018,analyses the consistency of 1603 projects,and calculates peer evaluation indicators of each expert.Thirty-seven experts were selected from 1457 evaluation experts,and their h index and G index were obtained through network search.The key words and results were combined to simulate the influence factors of their fields.The empirical results show that the dynamic selection model of peer review experts in this study is feasible,and it is more helpful for managers to select experts than the existing expert selection model of expert database.Help.(4)The idea of expert database construction explores the construction idea of this research expert database construction mode in practical application,providing more reference for managers.Conclusion:The source and selection of peer review experts are directly related to the quality and fairness of peer review results.Peer review expert database,as a support system for peer review experts,plays an important role in the selection of experts.According to the needs of managers,this study establishes a dynamic selection model of peer review experts including peer review indicators and academic professional indicators.Peer review indicators focus on reflecting experts’historical review,while academic professional indicators focus on reflecting experts’ research fields and academic achievements in the field.The combination of the two makes the expert selection model of this study retrospective,accurate and dynamic.Empirical research shows that the expert selection model formed in this study is feasible and helpful to the practical application of managers.If the expert database can be connected with the external literature database through computer programming in the later stage,it can further facilitate the selection of experts for managers. |
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