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Patent Statistics as Indicators of Competition an Analysis of Patenting in Biotechnology

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  • Parthasarathi Banerjee

    (National Institute of Science, Technology & Development Studies (NISTADS))

  • B. M. Gupta

    (National Institute of Science, Technology & Development Studies (NISTADS))

  • K. C. Garg

    (National Institute of Science, Technology & Development Studies (NISTADS))

Abstract

Numbers of patents cannot indicate the state of research or the contents of patent documentation cannot indicate the true technological features achieved. Patent statistics though so used, is not a good indicator of the economic returns to investments in research. Use of this statistics for understanding the degree of competition and the competition-driven research strategy is attractive. A patent document is part of the public knowledge in such a way as to restrict the growth of the future public knowledge. This portent on the future content of research and on the number and areas of research, by a current application is a competition-defining aspect. This effect on the lagged future applications and accepting patent disclosure as an intentional strategic data — are the most significant characteristics of patent statistics. The present paper applied this understanding, and generated a number of indices derived from data bases on patenting. These are indicators on Competition, Technology Pool, Language Technology Pool, Modified Competition, Market Attractiveness and on the Strength of Patent Market. Values of these indicators for biotechnological research and for several countries have been derived as example.

Suggested Citation

  • Parthasarathi Banerjee & B. M. Gupta & K. C. Garg, 2000. "Patent Statistics as Indicators of Competition an Analysis of Patenting in Biotechnology," Scientometrics, Springer;Akadémiai Kiadó, vol. 47(1), pages 95-116, January.
    • Handle: RePEc:spr:scient:v:47:y:2000:i:1:d:10.1023_a:1005669810018
    DOI: 10.1023/A:1005669810018
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    1. Amy Worgan & Samuel Nunn, 2002. "Exploring a Complicated Labyrinth: Some Tips on Using Patent Data to Measure Urban and Regional Innovation," Economic Development Quarterly, , vol. 16(3), pages 229-236, August.
    2. Szu-chia Lo, 2007. "Patent analysis of genetic engineering research in Japan, Korea and Taiwan," Scientometrics, Springer;Akadémiai Kiadó, vol. 70(1), pages 183-200, January.
    3. Shyama V. Ramani & Marie-Angele de Looze, 2002. "Using patent statistics as knowledge base indicators in the biotechnology sectors: An application to France, Germany and the U.K," Scientometrics, Springer;Akadémiai Kiadó, vol. 54(3), pages 319-346, July.
    4. Iraj Daizadeh, 2007. "Issued US patents, patent-related global academic and media publications, and the US market indices are inter-correlated, with varying growth patterns," Scientometrics, Springer;Akadémiai Kiadó, vol. 73(1), pages 29-36, October.
    5. K. C. Garg, 2003. "An overview of cross-national, national, and institutional assessment as reflected in the international journal Scientometrics," Scientometrics, Springer;Akadémiai Kiadó, vol. 56(2), pages 169-199, 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. Mee-Jean Kim, 2007. "A bibliometric analysis of the effectiveness of Korea’s Biotechnology Stimulation Plans, with a comparison with four other Asian nations," Scientometrics, Springer;Akadémiai Kiadó, vol. 72(3), pages 371-388, September.
    8. Robert Dalpé, 2002. "Bibliometric analysis of biotechnology," Scientometrics, Springer;Akadémiai Kiadó, vol. 55(2), pages 189-213, August.
    9. Szu-Chia Lo, 2008. "Patent coupling analysis of primary organizations in genetic engineering research," Scientometrics, Springer;Akadémiai Kiadó, vol. 74(1), pages 143-151, January.
    10. Mu-Hsuan Huang & Dar-Zen Chen & Danqi Shen & Mona S. Wang & Fred Y. Ye, 2015. "Measuring technological performance of assignees using trace metrics in three fields," Scientometrics, Springer;Akadémiai Kiadó, vol. 104(1), pages 61-86, July.
    11. Wolfgang Glänzel & Ping Zhou, 2011. "Publication activity, citation impact and bi-directional links between publications and patents in biotechnology," Scientometrics, Springer;Akadémiai Kiadó, vol. 86(2), pages 505-525, February.
    12. Thabang Lazarus Bambo & Anastassios Pouris, 2020. "Bibliometric analysis of bioeconomy research in South Africa," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(1), pages 29-51, October.

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