Measuring technological performance of assignees using trace metrics in three fields

Mu-Hsuan Huang, Dar-Zen Chen (), Danqi Shen, Mona S. Wang and Fred Y. Ye ()
Additional contact information
Mu-Hsuan Huang: National Taiwan University
Dar-Zen Chen: National Taiwan University
Danqi Shen: National Taiwan University
Mona S. Wang: Zhejiang University
Fred Y. Ye: Nanjing University

Scientometrics, 2015, vol. 104, issue 1, No 4, 86 pages

Abstract: Abstract The study establishes three synthetic indicators derived from academic traces—assignee traces T 1, T 2 and ST—and investigates their application in evaluating technological performance of assignees. Patent data for the top 100 assignees in three fields, “Computer Hardware & Software”, “Motors, Engines & Parts”, and “Drugs & Medical”, were retrieved from USPTO for further analysis. The results reveal that traces are indeed valid and useful indicators for measuring technological performance and providing detailed technical information about assignees and the industry. In addition, we investigate the relationship between traces and three other indicators: patent citation counts, Current Impact Index and patent h-index. In comparison with the three other indicators, traces demonstrate unique advantages and can be a good complement to patent citation analysis.

Keywords: Academic trace; Assignee trace; Patent trace; h-Index; CII (search for similar items in EconPapers)
Date: 2015
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://link.springer.com/10.1007/s11192-015-1604-8 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:scient:v:104:y:2015:i:1:d:10.1007_s11192-015-1604-8

Ordering information: This journal article can be ordered from
http://www.springer.com/economics/journal/11192

DOI: 10.1007/s11192-015-1604-8

Access Statistics for this article

Scientometrics is currently edited by Wolfgang Glänzel

More articles in Scientometrics from Springer, Akadémiai Kiadó
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().