Comparative Study of Trace Metrics between Bibliometrics and Patentometrics  

作　　者：Fred Y.Ye Mu-Hsuan Huang Dar-Zen Chen 

机构地区：[1]School of Information Management, Nanjing University [2]Department of Library and Information Science, Taiwan University [3]Department of Mechanical Engineering and Institute of Industrial Engineering, Taiwan University

出　　处：《Journal of Data and Information Science》2016年第2期13-31,共19页数据与情报科学学报（英文版）

基　　金：the National Natural Science Foundation of China (Grant No.: 71173187);Jiangsu Key Laboratory Fund for financial support

摘　　要：Purpose： To comprehensively evaluate the overall performance of a group or an individual in both bibliometrics and patentometrics. Design/methodology/approach： Trace metrics were applied to the top 30 universities in the2014 Academic Ranking of World Universities（ARWU） — computer sciences, the top 30 ESI highly cited papers in the computer sciences field in 2014, as well as the top 30 assignees and the top 30 most cited patents in the National Bureau of Economic Research（NBER） computer hardware and software category.Findings： We found that, by applying trace metrics, the research or marketing impact efficiency, at both group and individual levels, was clearly observed. Furthermore, trace metrics were more sensitive to the different publication-citation distributions than the average citation and h-index were.Research limitations： Trace metrics considered publications with zero citations as negative contributions. One should clarify how he/she evaluates a zero-citation paper or patent before applying trace metrics.Practical implications： Decision makers could regularly examinine the performance of their university/company by applying trace metrics and adjust their policies accordingly.Originality/value： Trace metrics could be applied both in bibliometrics and patentometrics and provide a comprehensive view. Moreover, the high sensitivity and unique impact efficiency view provided by trace metrics can facilitate decision makers in examining and adjusting their policies.Purpose： To comprehensively evaluate the overall performance of a group or an individual in both bibliometrics and patentometrics. Design/methodology/approach： Trace metrics were applied to the top 30 universities in the2014 Academic Ranking of World Universities（ARWU） — computer sciences, the top 30 ESI highly cited papers in the computer sciences field in 2014, as well as the top 30 assignees and the top 30 most cited patents in the National Bureau of Economic Research（NBER） computer hardware and software category.Findings： We found that, by applying trace metrics, the research or marketing impact efficiency, at both group and individual levels, was clearly observed. Furthermore, trace metrics were more sensitive to the different publication-citation distributions than the average citation and h-index were.Research limitations： Trace metrics considered publications with zero citations as negative contributions. One should clarify how he/she evaluates a zero-citation paper or patent before applying trace metrics.Practical implications： Decision makers could regularly examinine the performance of their university/company by applying trace metrics and adjust their policies accordingly.Originality/value： Trace metrics could be applied both in bibliometrics and patentometrics and provide a comprehensive view. Moreover, the high sensitivity and unique impact efficiency view provided by trace metrics can facilitate decision makers in examining and adjusting their policies.

关 键 词：Performance matrix Trace metrics H-INDEX h-core I3 BIBLIOMETRICS Patentometrics 

分 类 号：G353.1[文化科学—情报学]