IDEAS home Printed from https://ideas.repec.org/a/spr/scient/v98y2014i2d10.1007_s11192-013-1050-4.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11192-013-1050-4
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s11192-013-1050-4?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. 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.
    2. Zvi Griliches, 1998. "R&D and Productivity: The Econometric Evidence," NBER Books, National Bureau of Economic Research, Inc, number gril98-1.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. Griliches, Zvi, 1998. "R&D and Productivity," National Bureau of Economic Research Books, University of Chicago Press, edition 1, number 9780226308869, September.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Haschka, Rouven E. & Herwartz, Helmut, 2020. "Innovation efficiency in European high-tech industries: Evidence from a Bayesian stochastic frontier approach," Research Policy, Elsevier, vol. 49(8).
    2. Valeria Costantini & Francesco Crespi & Giovanni Marin & Elena Paglialunga, 2016. "Eco-innovation, sustainable supply chains and environmental performance in European industries," LEM Papers Series 2016/19, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    3. Kumar, Sanjesh & Singh, Baljeet, 2019. "Barriers to the international diffusion of technological innovations," Economic Modelling, Elsevier, vol. 82(C), pages 74-86.
    4. Georgios Gioldasis & Antonio Musolesi & Michel Simioni, 2020. "Model uncertainty, nonlinearities and out-of-sample comparison: evidence from international technology diffusion," Working Papers hal-02790523, HAL.
    5. Thomas Bolli & Martin Woerter, 2013. "Technological Diversification and Innovation Performance," KOF Working papers 13-336, KOF Swiss Economic Institute, ETH Zurich.
    6. Pietro Moncada-Paternò-Castello, 2022. "Top R&D investors, structural change and the R&D growth performance of young and old firms," Eurasian Business Review, Springer;Eurasia Business and Economics Society, vol. 12(1), pages 1-33, March.
    7. Soumyananda Dinda, 2018. "Production technology and carbon emission: long-run relation with short-run dynamics," Journal of Applied Economics, Taylor & Francis Journals, vol. 21(1), pages 106-121, January.
    8. Stavins, Robert & Jaffe, Adam & Newell, Richard, 2000. "Technological Change and the Environment," Working Paper Series rwp00-002, Harvard University, John F. Kennedy School of Government.
    9. Diemer, Andreas & Regan, Tanner, 2022. "No inventor is an island: Social connectedness and the geography of knowledge flows in the US," Research Policy, Elsevier, vol. 51(2).
    10. Hana Kim & Eungdo Kim, 2018. "How an Open Innovation Strategy for Commercialization Affects the Firm Performance of Korean Healthcare IT SMEs," Sustainability, MDPI, vol. 10(7), pages 1-14, July.
    11. John Van Reenen & Rupert Harrison & Rachel Griffith, 2006. "How Special Is the Special Relationship? Using the Impact of U.S. R&D Spillovers on U.K. Firms as a Test of Technology Sourcing," American Economic Review, American Economic Association, vol. 96(5), pages 1859-1875, December.
    12. Douglas Hanley, 2014. "Innovation, Technological Interdependence, and Economic Growth," Working Paper 533, Department of Economics, University of Pittsburgh, revised Jan 2014.
    13. Wendler, Tobias & Töbelmann, Daniel & Günther, Jutta, 2021. "Natural resources and technology - on the mitigating effect of green tech," VfS Annual Conference 2021 (Virtual Conference): Climate Economics 242416, Verein für Socialpolitik / German Economic Association.
    14. Wenqing Zhao & Bing Lu & Jianyu Zhang, 2019. "Housing Prices and Corporate Innovation in China," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 9(3), pages 1-2.
    15. Dirk Czarnitzki & Julie Delanote, 2017. "Incorporating innovation subsidies in the CDM framework: empirical evidence from Belgium," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 26(1-2), pages 78-92, February.
    16. Dirk Czarnitzki & Julie Delanote, 2015. "R&D policies for young SMEs: input and output effects," Small Business Economics, Springer, vol. 45(3), pages 465-485, October.
    17. Stéphane Lemarié & Valérie Orozco & Jean-Pierre Butault & Antonio Musolesi & Michel Simioni & Bertrand Schmitt, 2020. "Assessing the long-term impact of agricultural research on productivity: evidence from France," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 47(4), pages 1559-1586.
    18. Edquist, Harald, 2022. "The economic impact of mobile broadband speed," Telecommunications Policy, Elsevier, vol. 46(5).
    19. Stiebale, Joel, 2016. "Cross-border M&As and innovative activity of acquiring and target firms," Journal of International Economics, Elsevier, vol. 99(C), pages 1-15.
    20. Dhanora, Madan & Sharma, Ruchi & Khachoo, Qayoom, 2018. "Non-linear impact of product and process innovations on market power: A theoretical and empirical investigation," Economic Modelling, Elsevier, vol. 70(C), pages 67-77.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:scient:v:98:y:2014:i:2:d:10.1007_s11192-013-1050-4. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.