Comparative Study of Trace Metrics between Bibliometrics and Patentometrics
Fred Y. Ye1; Mu-Hsuan Huang2; Dar-Zen Chen3; Dar-Zhen Chen (E-mail: dzchen@ntu.edu.tw).
2016-06-17
发表期刊Journal of Data and Information Science
卷号1期号:2页码:13-31
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 the 2014 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 the 2014 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.

文章类型Research Paper
关键词Performance Matrix Trace Metrics h-index|h-core I3 Bibliometrics Patentometrics
学科领域新闻学与传播学 ; 图书馆、情报与文献学
DOI10.20309/jdis.201611
URL查看原文
收录类别其他
所属项目编号Grant No.: 71173187
语种英语
资助项目the National Natural Science Foundation of China ; Jiangsu Key Laboratory Fund for financial support
项目资助者Ms. Danqi Shen ; Ms. Helen F. Xue ; Ms. Mei-Chun Lin
引用统计
文献类型期刊论文
条目标识符http://ir.las.ac.cn/handle/12502/8595
专题Journal of Data and Information Science_Journal of Data and Information Science-2016
通讯作者Dar-Zhen Chen (E-mail: dzchen@ntu.edu.tw).
作者单位1.School of Information Management, Nanjing University, Nanjing 210023, China
2.Department of Library and Information Science, Taiwan University, Taipei 10617, China
3.Department of Mechanical Engineering and Institute of Industrial Engineering, Taiwan University, Taipei 10617, China
第一作者单位中国科学院文献情报中心
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Fred Y. Ye,Mu-Hsuan Huang,Dar-Zen Chen,et al. Comparative Study of Trace Metrics between Bibliometrics and Patentometrics[J]. Journal of Data and Information Science,2016,1(2):13-31.
APA Fred Y. Ye,Mu-Hsuan Huang,Dar-Zen Chen,&Dar-Zhen Chen .(2016).Comparative Study of Trace Metrics between Bibliometrics and Patentometrics.Journal of Data and Information Science,1(2),13-31.
MLA Fred Y. Ye,et al."Comparative Study of Trace Metrics between Bibliometrics and Patentometrics".Journal of Data and Information Science 1.2(2016):13-31.
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