EconPapers    
Economics at your fingertips  
 

An attempt to identify technologically relevant papers based on their references

Yasuhiro Yamashita ()
Additional contact information
Yasuhiro Yamashita: Japan Science and Technology Agency

Scientometrics, 2020, vol. 125, issue 2, No 51, 1783-1800

Abstract: Abstract In this study, two indicators derived from references in papers were proposed to characterize the papers regarding technological relevance: (1) the number of reference papers that obtained citations from patents by the time of observation, i.e., the publication years of papers to be assessed (NR-PCP), and (2) the number of reference papers authored by the firms’ researchers (NR-FP). Next, the two indicators were applied to papers published in 2001 to assess their performance. The results obtained by the two indicators were evaluated by citations from patents until 2016 in various conditions: scientific field, institutional sector, and period of measurement. Results showed a robustness of both indicators in many conditions. NR-PCP showed better results in most cases than NR-FP, although its recall was inferior to NR-FP for papers in which all references were newer than 1996. Based on the result that NR-PCP was preferred as an indicator, the rationale of using reference papers cited in the patent by the period of observation (R-PCP) as an indicator was considered based on the papers’ potential distances from the border between science and technology, which was obtained from an extended version of the citation network originally proposed by Ahmadpoor and Jones (Science 357:583–587, 2017. https://doi.org/10.1126/science.aam9527 ). Finally, issues to be addressed were discussed.

Keywords: Patent-paper citations; References; Indicator; Technological relevance (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s11192-020-03673-5 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:125:y:2020:i:2:d:10.1007_s11192-020-03673-5

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

DOI: 10.1007/s11192-020-03673-5

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 ().

 
Page updated 2025-03-20
Handle: RePEc:spr:scient:v:125:y:2020:i:2:d:10.1007_s11192-020-03673-5