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Patent applications as source for measuring technological performance

Author

Listed:
  • Juan Sepúlveda

    (Universidad Manuela Beltrán)

  • Adriana Paternina

    (REMAPLAST)

  • Andrés Suarez

    (Universidad Tecnológica de Pereira)

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.

Suggested Citation

  • Juan Sepúlveda & Adriana Paternina & Andrés Suarez, 2014. "Patent applications as source for measuring technological performance," Scientometrics, Springer;Akadémiai Kiadó, vol. 98(2), pages 1385-1395, February.
  • Handle: RePEc:spr:scient:v:98:y:2014:i:2:d:10.1007_s11192-013-1050-4
    DOI: 10.1007/s11192-013-1050-4
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    References listed on IDEAS

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    1. Fu, Xiaolan & Yang, Qing Gong, 2009. "Exploring the cross-country gap in patenting: A Stochastic Frontier Approach," Research Policy, Elsevier, vol. 38(7), pages 1203-1213, September.
    2. Alireza Noruzi & Mohammadhiwa Abdekhoda, 2012. "Mapping Iranian patents based on International Patent Classification (IPC), from 1976 to 2011," Scientometrics, Springer;Akadémiai Kiadó, vol. 93(3), pages 847-856, December.
    3. Chen-Yuan Liu & Jhen-Cheng Wang, 2010. "Forecasting the development of the biped robot walking technique in Japan through S-curve model analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 82(1), pages 21-36, January.
    4. Griliches, Zvi, 1998. "R&D and Productivity," National Bureau of Economic Research Books, University of Chicago Press, edition 1, number 9780226308869, April.
    5. Zvi Griliches, 1998. "R&D and Productivity: The Econometric Evidence," NBER Books, National Bureau of Economic Research, Inc, number gril98-1.
    6. Zvi Griliches, 1998. "Patent Statistics as Economic Indicators: A Survey," NBER Chapters, in: R&D and Productivity: The Econometric Evidence, pages 287-343, National Bureau of Economic Research, Inc.
    7. Jun Peng Yuan & Wei Ping Yue & Cheng Su & Zheng Wu & Zheng Ma & Yun Tao Pan & Nan Ma & Zhi Yu Hu & Fei Shi & Zheng Lu Yu & Yi Shan Wu, 2010. "Patent activity on water pollution and treatment in China—a scientometric perspective," Scientometrics, Springer;Akadémiai Kiadó, vol. 83(3), pages 639-651, June.
    8. Schilling, Melissa A. & Esmundo, Melissa, 2009. "Technology S-curves in renewable energy alternatives: Analysis and implications for industry and government," Energy Policy, Elsevier, vol. 37(5), pages 1767-1781, May.
    9. Dubaric, Ervin & Giannoccaro, Dimitris & Bengtsson, Rune & Ackermann, Thomas, 2011. "Patent data as indicators of wind power technology development," World Patent Information, Elsevier, vol. 33(2), pages 144-149, June.
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