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Measuring patent's influence on technological evolution: A study of knowledge spanning and subsequent inventive activity

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  • Corredoira, Rafael A.
  • Banerjee, Preeta M.

Abstract

We introduce technological influence as a variable to measure an invention's direct and indirect impact on the evolution of technology. This provides a novel means to study the short and long run effect of invention antecedents on technological evolution, invention activity, and economic growth. A comparison between models of technological influence and direct technological impact is presented. Model estimations are based on data from semiconductor patents granted over a 5-year period. Results from quantile regression estimations show significant differences in the relationships between antecedents of technological influence and impact. For example, pioneering the spanning of knowledge boundaries has a positive relationship with the patent's influence, while no relationship is found with direct citations. These results have important implications for public policy and the management of technology. They suggest the need for deeper understanding of the micro-foundations of the technological evolution process and raise the question of whether inventors under current IP protection receive adequate economic incentives to promote actions driving economic growth.

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  • Corredoira, Rafael A. & Banerjee, Preeta M., 2015. "Measuring patent's influence on technological evolution: A study of knowledge spanning and subsequent inventive activity," Research Policy, Elsevier, vol. 44(2), pages 508-521.
    • Handle: RePEc:eee:respol:v:44:y:2015:i:2:p:508-521
    DOI: 10.1016/j.respol.2014.10.003
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    Cited by:

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    7. Zhanna A. Mingaleva & Lyudmila N. Deputatova & Nikolay B. Akatov & Yurii V. Starkov & Elena Mitrofanova, 2019. "Application of HADI-cycle for providing sustainability of processes of knowledge and innovation," Entrepreneurship and Sustainability Issues, VsI Entrepreneurship and Sustainability Center, vol. 7(2), pages 1628-1640, December.
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    9. Guan, Jian Cheng & Yan, Yan, 2016. "Technological proximity and recombinative innovation in the alternative energy field," Research Policy, Elsevier, vol. 45(7), pages 1460-1473.
    10. Candiani, Juan Antonio & Gilsing, Victor & Mastrogiorgio, Mariano, 2022. "Technological entry in new niches: Diversity, crowding and generalism," Technovation, Elsevier, vol. 116(C).
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    12. Ad van den Oord & Arjen van Witteloostuijn, 2018. "A multi-level model of emerging technology: An empirical study of the evolution of biotechnology from 1976 to 2003," PLOS ONE, Public Library of Science, vol. 13(5), pages 1-27, May.
    13. Corredoira, Rafael A. & Goldfarb, Brent D. & Shi, Yuan, 2018. "Federal funding and the rate and direction of inventive activity," Research Policy, Elsevier, vol. 47(9), pages 1777-1800.
    14. Kathryn Rudie Harrigan & Maria Chiara DiGuardo, 2017. "Sustainability of patent-based competitive advantage in the U.S. communications services industry," The Journal of Technology Transfer, Springer, vol. 42(6), pages 1334-1361, December.
    15. Subtil Lacerda, Juliana & van den Bergh, Jeroen C.J.M., 2020. "Effectiveness of an ‘open innovation’ approach in renewable energy: Empirical evidence from a survey on solar and wind power," Renewable and Sustainable Energy Reviews, Elsevier, vol. 118(C).
    16. Ardito, Lorenzo & D'Adda, Diego & Messeni Petruzzelli, Antonio, 2018. "Mapping innovation dynamics in the Internet of Things domain: Evidence from patent analysis," Technological Forecasting and Social Change, Elsevier, vol. 136(C), pages 317-330.
    17. Zhang, Guiyang & Tang, Chaoying, 2017. "How could firm's internal R&D collaboration bring more innovation?," Technological Forecasting and Social Change, Elsevier, vol. 125(C), pages 299-308.
    18. Doblinger, Claudia & Surana, Kavita & Li, Deyu & Hultman, Nathan & Anadón, Laura Díaz, 2022. "How do global manufacturing shifts affect long-term clean energy innovation? A study of wind energy suppliers," Research Policy, Elsevier, vol. 51(7).
    19. Xiao Zhou & Lu Huang & Yi Zhang & Miaomiao Yu, 2019. "A hybrid approach to detecting technological recombination based on text mining and patent network analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 121(2), pages 699-737, November.
    20. Lijie Feng & Yilang Li & Zhenfeng Liu & Jinfeng Wang, 2020. "Idea Generation and New Direction for Exploitation Technologies of Coal-Seam Gas through Recombinative Innovation and Patent Analysis," IJERPH, MDPI, vol. 17(8), pages 1-21, April.
    21. Rajat Khanna & Isin Guler, 2022. "Degree assortativity in collaboration networks and invention performance," Strategic Management Journal, Wiley Blackwell, vol. 43(7), pages 1402-1430, July.
    22. Cui, Victor & Ding, Waverly W. & Yanadori, Yoshio, 2019. "Exploration versus exploitation in technology firms: The role of compensation structure for R&D workforce," Research Policy, Elsevier, vol. 48(6), pages 1534-1549.
    23. Kathryn Rudie Harrigan & Maria Chiara Guardo & Elona Marku, 2018. "Patent value and the Tobin’s q ratio in media services," The Journal of Technology Transfer, Springer, vol. 43(1), pages 1-19, February.
    24. Jie Liu & Arnulf Grubler & Tieju Ma & Dieter F. Kogler, 2021. "Identifying the technological knowledge depreciation rate using patent citation data: a case study of the solar photovoltaic industry," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(1), pages 93-115, January.
    25. Jinkuk Kim & Jungsub Yoon & Jeong-Dong Lee, 2021. "Dominant design and evolution of technological trajectories: The case of tank technology, 1915–1998," Journal of Evolutionary Economics, Springer, vol. 31(2), pages 661-676, April.

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