EconPapers    
Economics at your fingertips  
 

Patent applications as source for measuring technological performance

Juan Sepúlveda (), Adriana Paternina () and Andrés Suarez ()
Additional contact information
Juan Sepúlveda: Universidad Manuela Beltrán
Adriana Paternina: REMAPLAST
Andrés Suarez: Universidad Tecnológica de Pereira

Scientometrics, 2014, vol. 98, issue 2, No 35, 1385-1395

Abstract: Abstract S-curves analysis allows to study evolution and trends in specific technological fields; its theoretical background establishes that in order to achieve the best results the analysis must be done using an independent variable that shows the effort invested in R&D activities and a dependent variable that shows the cumulative performance in that field. Actually, S-curves are built using time as independent variable because of the constraints associated in the search of investment data. This paper examines the use of patent data applications as a sample of effort; using geothermal field as a case study, it was possible to test the relationship of Patent applications and investment (R-squared, 0.86), in first place, and the construction of S-curves using patent applications count against performance (R-Squared, 0.947). Results show a high correspondence value and potential of using patent counts to direct technological performance studies.

Keywords: Patent applications data; Technology; Performance; S-curves (search for similar items in EconPapers)
Date: 2014
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s11192-013-1050-4 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:98:y:2014:i:2:d:10.1007_s11192-013-1050-4

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

DOI: 10.1007/s11192-013-1050-4

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:98:y:2014:i:2:d:10.1007_s11192-013-1050-4