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Knowledge production patterns of China and the US: quantum technology

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Abstract

This paper addresses knowledge production patterns in the research and development of quantum technologies, perhaps one of the most promising advances in modern times. Using a publication data and innovation system framework, this paper investigates and compares the knowledge production patterns of China and the US in quantum technology. Empirical evidence suggests that China’s scientific knowledge production focuses relatively more on domestic research collaboration, and ‘communication’ technology, and core-periphery collaboration partners, while US knowledge production focuses on both domestic and international collaboration, and specializes more in ‘computing’ technology, and more collaborations with OECD countries through their institutional assets. This study contributes to understanding the different knowledge production patterns of China and the US in quantum technology, with implications for other countries. Several implications and a future research agenda are discussed.

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Notes

  1. There are a variety of terms and classification criteria for quantum technology that have been suggested by major countries, such as the US, EU, UK, Germany, Japan, China, and Korea. In this study, we did not cite one of the various classification criteria as it was, but we generated the searching equation by using keywords for specific technology fields for the convenience of this study. To this end, the author requested for advice from a number of experts in quantum technology on how to use the classification criteria of quantum technology. As a result, we found that the classification criteria suggested by the experts is similar to that of the Institute for Information & Communication Technology Planning & Evaluation (IITP), a public institute in Korea. Therefore, by considering both the classification criteria suggested by the experts and the criterion of IITP, we derived the equation of searching keywords and conducted the research.

  2. The data also suggests that regardless of research actors, both the US and China rely more on domestic research collaboration than international research collaboration to produce papers on quantum technology. However, the number of papers published by China’s research actors is extremely concentrated on domestic research collaborations, while the number of US papers produced by domestic research collaboration is not much different from those produced by international research collaboration.

  3. These results are consistently found in the data classified by domestic and international collaborative research. Therefore, the data robustly supports our hypothesis 1.

  4. Other national factors that have enabled China to develop quantum technology rapidly include (1) socialist political systems, (2) long-term investment and support policy, and (3) attracting high-quality talent (Thousand Talents Plan, Ten Thousand Talents Plan).

  5. The number of papers produced by Chinese companies is very low, and hence the information about the Chinese companies is also limited. Therefore, we do not provide a table, but describe the results.

References

  • Abernathy, W. J., & Utterback, J. M. (1978). Patterns of industrial innovation. Technology Review, 80(7), 40–47.

    Google Scholar 

  • Adams, J. (2013). The fourth age of research. Nature, 497(7451), 557–560.

    Article  Google Scholar 

  • Amin, A., & Wilkinson, F. (1999). Learning, proximity and industrial performance: An introduction. Cambridge Journal of Economics, 23(2), 121–125.

    Article  Google Scholar 

  • Archibugi, D., & Pianta, M. (1992). Specialization and size of technological activities in industrial countries: The analysis of patent data. Research Policy, 21(1), 79–93.

    Article  Google Scholar 

  • Archibugi, D., & Pianta, M. (1994). Aggregate convergence and sectoral specialization in innovation. Journal of Evolutionary Economics, 4(1), 17–33.

    Article  Google Scholar 

  • Arocena, R., & Sutz, J. (2001). Changing knowledge production and Latin American universities. Research Policy, 30(8), 1221–1234.

    Article  Google Scholar 

  • Berman, A., Marino, A., & Mudambi, R. (2020). The global connectivity of regional innovation systems in Italy: A core–periphery perspective. Regional Studies, 54(5), 677–691.

    Article  Google Scholar 

  • Boschma, R. (2005). Proximity and innovation: A critical assessment. Regional Studies, 39(1), 61–74.

    Article  Google Scholar 

  • Bradsher, K. (2010). On clean energy, China skirts rules. New York times, 9, A1.

    Google Scholar 

  • Camerani, R., Rotolo, D., & Grassano, N. (2018). Do firms publish? A multi-sectoral analysis: A Multi-Sectoral Analysis. https://doi.org/10.2139/ssrn.3276054

    Book  Google Scholar 

  • Cantwell, J. (1991). The International Agglomeration of R&D. In M. Casson (Ed.), Global Research Strategy and International Competitiveness. Oxford: Blackwell.

    Google Scholar 

  • Carayannis, E. G., & Laget, P. (2004). Transatlantic innovation infrastructure networks: Public-private, EU–US R&D partnerships. R&D Management, 34(1), 17–31.

    Article  Google Scholar 

  • Chen, K., Zhang, Y., Zhu, G., & Mu, R. (2020). Do research institutes benefit from their network positions in research collaboration networks with industries or/and universities? Technovation, 94, 102002.

    Article  Google Scholar 

  • Choi, S. (2012). Core-periphery, new clusters, or rising stars?: International scientific collaboration among ‘advanced’countries in the era of globalization. Scientometrics, 90(1), 25–41.

    Article  Google Scholar 

  • Choung, J. Y. (1998). Patterns of innovation in Korea and Taiwan. IEEE Transactions on Engineering Management, 45(4), 357–365.

    Article  Google Scholar 

  • Choung, J. Y., & Hwang, H. R. (2013). The evolutionary patterns of knowledge production in Korea. Scientometrics, 94(2), 629–650.

    Article  Google Scholar 

  • Clarivate (2021) Research Fronts

  • Daniel Garisto. (2021) China is pulling ahead in global quantum race, New studies suggest. Scientific American

  • David, P. A. (1975). Technical choice innovation and economic growth: Essays on American and British experience in the nineteenth century. Cambridge University Press.

    Google Scholar 

  • Elia, S., Kafouros, M., & Buckley, P. J. (2020). The role of internationalization in enhancing the innovation performance of Chinese EMNEs: A geographic relational approach. Journal of International Management, 26(4), 100801.

    Article  Google Scholar 

  • Flagg, M., Toney, A., & Harris, P. (2021) Research security, collaboration, and the changing map of global R&D

  • Freeman, C. (1987). Technical innovation, diffusion, and long cycles of economic development. Berlin, Heidelberg: In The long-wave debate Springer.

    Book  Google Scholar 

  • Freeman, C., & Soete, L. (1999). The Economics of Industrial Innovation. MIT Press, Cambridge. A. Griibler El Al. Energy Policy, 27, 247–280.

    Google Scholar 

  • Fujii, H., & Managi, S. (2018). Trends and priority shifts in artificial intelligence technology invention: A global patent analysis. Economic Analysis and Policy, 58, 60–69.

    Article  Google Scholar 

  • Gao, X., Guo, X., & Guan, J. (2014). An analysis of the patenting activities and collaboration among industry-university-research institutes in the Chinese ICT sector. Scientometrics, 98(1), 247–263.

    Article  Google Scholar 

  • Gibbons, M., Limoges, C., Nowotny, H., Schwartzman, S., Scott, P., & Trow, M. (1994). The new production of knowledge: The dynamics of science and research in contemporary societies sage

  • Giles, M. (2019). The US and China are in a quantum arms race that will transform warfare. MIT Technology Review

  • Godin, B. (1996). Research and the practice of publication in industries. Research Policy, 25(4), 587–606.

    Article  Google Scholar 

  • Godin, B., & Gingras, Y. (2000). The place of universities in the system of knowledge production. Research Policy, 29(2), 273–278.

    Article  Google Scholar 

  • Goerzen, A., & Beamish, P. W. (2005). The effect of alliance network diversity on multinational enterprise performance. Strategic Management Journal, 26(4), 333–354.

    Article  Google Scholar 

  • Guan, J., & Wang, G. (2010). A comparative study of research performance in nanotechnology for China’s inventor–authors and their non-inventing peers. Scientometrics, 84(2), 331–343.

    Article  Google Scholar 

  • Hagedoorn, J., Link, A. N., & Vonortas, N. S. (2000). Research Partnerships. Research Policy, 29(4–5), 567–586.

    Article  Google Scholar 

  • HAI. (2021). The AI index 2021 annual report, AI Index Steering Committee, Human-Centered Artificial Intelligence, Stanford University.

  • Harzing, A. W., & Giroud, A. (2014). The competitive advantage of nations: An application to academia. Journal of Informetrics, 8(1), 29–42.

    Article  Google Scholar 

  • Hassan, S.-U., Haddawy, P., & Zhu, J. (2014). A bibliometric study of the world’s research activity in sustainable development and its sub-areas using scientific literature. Scientometrics, 99(2), 549–579.

    Article  Google Scholar 

  • Herron, P., Mehta, A., Cao, C., & Lenoir, T. (2016). Research diversification and impact: The case of national nanoscience development. Scientometrics, 109(2), 629–659.

    Article  Google Scholar 

  • Hicks, D. (1995). Published papers, tacit competencies and corporate management of the public/private character of knowledge. Industrial and Corporate Change, 4(2), 401–424.

    Article  Google Scholar 

  • Hoekman, J., Scherngell, T., Frenken, K., & Tijssen, R. (2013). Acquisition of European research funds and its effect on international scientific collaboration. Journal of Economic Geography, 13(1), 23–52.

    Article  Google Scholar 

  • Hu, A. G., & Jaffe, A. B. (2003). Patent citations and international knowledge flow: The cases of Korea and Taiwan. International Journal of Industrial Organization, 21(6), 849–880.

    Article  Google Scholar 

  • Hwang, H. R., & Choung, J. Y. (2014). The co-evolution of technology and institutions in the catch-up process: The case of the semiconductor industry in Korea and Taiwan. The Journal of Development Studies, 50(9), 1240–1260.

    Article  Google Scholar 

  • Jiang, S. Y., & Chen, S. L. (2021). Exploring landscapes of quantum technology with patent network analysis. Technology Analysis & Strategic Management, 33, 1–15.

    Article  Google Scholar 

  • John Prisco (2021). China: The Quantum Competition We Can’t Ignore. Forbes Technology Council, Fobes

  • Kang, I., Choung, J. Y., Kang, D. I., & Park, I. (2021). Divergence of knowledge production strategies for emerging technologies between late industrialized countries: Focusing on quantum technology. ETRI Journal, 43(2), 246–259.

    Article  Google Scholar 

  • Katz, J. S., & Hicks, D. M. (1996). A systemic view of British science. Scientometrics, 35(1), 133–154.

    Article  Google Scholar 

  • Kim, L. (1993). In: R. R. Nelson (Ed.), National system of industrial innovation: dynamics of capability building in Korea (pp. 357–83). New York: Oxford University Press. National innovation systems: a comparative analysis. Oxford University Press on Demand

  • Kim, L (1997), Imitation to innovation: The Dynamics of Korea's technological learning by Harvard Business School Press

  • Lavie, D., & Miller, S. R. (2008). Alliance portfolio internationalization and firm performance. Organization Science, 19(4), 623–646.

    Article  Google Scholar 

  • Lee, K., & Yoon, M. (2010). International, intra-national and inter-firm knowledge diffusion and technological catch-up: The USA, Japan, Korea and Taiwan in the memory chip industry. Technology Analysis & Strategic Management, 22(5), 553–570.

    Article  Google Scholar 

  • Leydesdorff, L., Wagner, C., Park, H. W., & Adams, J. (2013). International collaboration in science: The global map and the network. arXiv preprint arXiv:1301.0801.

  • Li, Y., Arora, S., Youtie, J., & Shapira, P. (2018). Using web mining to explore triple helix influences on growth in small and mid-size firms. Technovation, 76–77, 3–14. https://doi.org/10.1016/j.technovation.2016.01.002

    Article  Google Scholar 

  • Li, D., Heimeriks, G., & Alkemade, F. (2020). The emergence of renewable energy technologies at country level: Relatedness, international knowledge spillovers and domestic energy markets. Industry and Innovation, 27(9), 991–1013.

    Article  Google Scholar 

  • Li, D., Heimeriks, G., & Alkemade, F. (2021a). Knowledge flows in global renewable energy innovation systems: the role of technological and geographical distance. Technology Analysis & Strategic Management, 34, 1–15.

    Google Scholar 

  • Li, D., Heimeriks, G., & Alkemade, F. (2021b). Recombinant invention in solar photovoltaic technology: Can geographical proximity bridge technological distance? Regional Studies, 55(4), 605–616.

    Article  Google Scholar 

  • Liu, N., & Guan, J. (2015). Dynamic evolution of collaborative networks: Evidence from nano-energy research in China. Scientometrics, 102(3), 1895–1919.

    Article  Google Scholar 

  • Lundvall, B. A. (1992). National systems of innovation: Towards a theory of innovation and interactive learning. Francis Printer.

    Google Scholar 

  • Maisonobe, M., Eckert, D., Grossetti, M., Jégou, L., & Milard, B. (2016). The world network of scientific collaborations between cities: Domestic or international dynamics? Journal of Informetrics, 10(4), 1025–1036.

    Article  Google Scholar 

  • Malerba, F. (1993). The national system of innovation: Italy. National Innovation Systems: A Comparative Analysis, 1, 230–259.

    Google Scholar 

  • Malerba, F. (2002). Sectoral systems of innovation and production. Research Policy, 31(2), 247–264.

    Article  Google Scholar 

  • Marrocu, E., Paci, R., & Usai, S. (2013). Proximity, networking and knowledge production in Europe: What lessons for innovation policy? Technological Forecasting and Social Change, 80(8), 1484–1498.

    Article  Google Scholar 

  • Matthiessen, C. W., Schwarz, A. W., & Find, S. (2010). World cities of scientific knowledge: Systems, networks and potential dynamics. An analysis based on bibliometric indicators. Urban Studies, 47(9), 1879–1897.

    Article  Google Scholar 

  • Meyer, M. (2001). Patent citation analysis in a novel field of technology: An exploration of nano-science and nano-technology. Scientometrics, 51(1), 163–183.

    Article  Google Scholar 

  • Meyer, M., & Persson, O. (1998). Nanotechnology-interdisciplinarity, patterns of collaboration and differences in application. Scientometrics, 42(2), 195–205.

    Article  Google Scholar 

  • Meyer-Krahmer, F., & Reger, G. (1999). New perspectives on the innovation strategies of multinational enterprises: Lessons for technology policy in Europe. Research Policy, 28(7), 751–776.

    Article  Google Scholar 

  • Mowery, D. C., & Nelson, R. R. (Eds.). (1999). Sources of industrial leadership: studies of seven industries. London: Cambridge University Press.

    Google Scholar 

  • Mowery, D. C., Nelson, R. R., Sampat, B. N., & Ziedonis, A. A. (2001). The growth of patenting and licensing by US universities: An assessment of the effects of the Bayh-Dole act of 1980. Research Policy, 30(1), 99–119.

    Article  Google Scholar 

  • Nelson, R. (1993). National innovation systems: A comparative analysis. Oxford University Press.

    Google Scholar 

  • Nelson, R. R., & Rosenberg, N. (1993). Technical innovation and national systems. National Innovation Systems: A Comparative Analysis, 1, 3–21.

    Google Scholar 

  • Nguyen, C. M., & Choung, J. Y. (2020). Scientific knowledge production in China: A comparative analysis. Scientometrics, 124, 1279–1303.

    Article  Google Scholar 

  • Nowotny, H., Scott, P., & Gibbons, M. (2003). Introduction:’Mode 2’revisited: The new production of knowledge. Minerva, 41(3), 179–194.

    Article  Google Scholar 

  • Owen-Smith, J., Riccaboni, M., Pammolli, F., & Powell, W. W. (2002). A comparison of US and European university-industry relations in the life sciences. Management Science, 48(1), 24–43.

    Article  Google Scholar 

  • Ozcan, S., & Islam, N. (2017). Patent information retrieval: Approaching a method and analysing nanotechnology patent collaborations. Scientometrics, 111(2), 941.

    Article  Google Scholar 

  • Patel, P., & Pavitt, K. (1994). Uneven (and divergent) technological accumulation among advanced countries: Evidence and a framework of explanation. Industrial and Corporate Change, 3(3), 759–787.

    Article  Google Scholar 

  • Pavitt, K. (1984). Sectoral patterns of technical change: Towards a taxonomy and a theory. Research Policy, 13(6), 343–373.

    Article  Google Scholar 

  • Ploszaj, A., Celinska-Janowicz, D., & Olechnicka, A. (2018, September). Core-periphery relations in international research collaboration. In STI 2018 Conference Proceedings (pp. 1322–1327). Centre for Science and Technology Studies (CWTS)

  • Rosenberg, N., & Nelson, R. R. (1994). American universities and technical advance in industry. Research Policy, 23(3), 323–348.

    Article  Google Scholar 

  • Rotolo, D., Hicks, D., & Martin, B. R. (2015). What is an emerging technology? Research Policy, 44(10), 1827–1843.

    Article  Google Scholar 

  • Scarazzati, S., & Wang, L. (2019). The effect of collaborations on scientific research output: The case of nanoscience in Chinese regions. Scientometrics, 121(2), 839–868.

    Article  Google Scholar 

  • Scherngell, T. (2021). The geography of R&D collaboration networks. Springer, Berlin Heidelberg, Berlin, Heidelberg: Handbook of Regional Science.

    Book  MATH  Google Scholar 

  • Schott, T. (1993). World science: Globalization of institutions and participation. Science, Technology, & Human Values, 18(2), 196–208.

    Article  Google Scholar 

  • Seo, E. Y., Choung, J. Y., & Hwang, H. R. (2019). The changing patterns of knowledge production of catch-up firms during the forging-ahead period: Case study of samsung electronics Co (SEC). IEEE Transactions on Engineering Management, 66(4), 621–635.

    Article  Google Scholar 

  • Shils, E. (1991). Reflections on tradition, centre and periphery and the universal validity of science: The significance of the life of S Ramanujan. Minerva, 29(4), 393–419.

    Article  Google Scholar 

  • Shoham, Y., Perrault, R., Brynjolfsson, E., Clark, J., Manyika, J., Niebles, J. C., & Bauer, Z. (2018). The AI index 2018 annual report. Human-Centered AI Initiative, Stanford University.

    Google Scholar 

  • Shiu, J. W., Wong, C. Y., & Hu, M. C. (2014). The dynamic effect of knowledge capitals in the public research institute: Insights from patenting analysis of ITRI (Taiwan) and ETRI (Korea). Scientometrics, 98(3), 2051–2068.

    Article  Google Scholar 

  • Smith-Goodson, P. (2019). Quantum USA Vs. Quantum China: The World’s Most Important Technology Race. Moor Insights and Strategy. Forbes

  • Song, Y., Zhang, J., Song, Y., Fan, X., Zhu, Y., & Zhang, C. (2020). Can industry-university-research collaborative innovation efficiency reduce carbon emissions? Technological Forecasting and Social Change, 157, 120094. https://doi.org/10.1016/j.techfore.2020.120094

    Article  Google Scholar 

  • Sun, Y., & Cao, C. (2015). Intra-and inter-regional research collaboration across organizational boundaries: Evolving patterns in China. Technological Forecasting and Social Change, 96, 215–231.

    Article  Google Scholar 

  • Sun, Y., & Cao, C. (2020). The dynamics of the studies of China’s science, technology and innovation (STI): A bibliometric analysis of an emerging field. Scientometrics, 124(2), 1335–1365.

    Article  Google Scholar 

  • Tang, L., & Shapira, P. (2011a). China–US scientific collaboration in nanotechnology: Patterns and dynamics. Scientometrics, 88(1), 1–16.

    Article  Google Scholar 

  • Tang, L., & Shapira, P. (2011b). Regional development and interregional collaboration in the growth of nanotechnology research in China. Scientometrics, 86(2), 299–315.

    Article  Google Scholar 

  • Tamada, S., Naito, Y., Kodama, F., Gemba, K., & Suzuki, J. (2006). Significant difference of dependence upon scientific knowledge among different technologies. Scientometrics, 68(2), 289–302.

    Article  Google Scholar 

  • Tidd, J., Bessant, J. R., & Pavitt, K. (1997). Managing innovation: Integrating technological, market and organizational change. Wiley.

    Google Scholar 

  • Tidd, J., & Trewhella, M. J. (1997). Organizational and technological antecedents for knowledge acquisition and learning. R&D Management, 27(4), 359–375.

    Article  Google Scholar 

  • Wagner, C. S. (2005). Six case studies of international collaboration in science. Scientometrics, 62(1), 3–26.

    Article  Google Scholar 

  • Wagner, C. S., Brahmakulam, I., Jackson, B., Wong, A., & Yoda, T. (2001). Science and technology collaboration: Building capability in developing countries. Rand corp santa monica ca

  • Wang, Y., Hu, D., Li, W., Li, Y., & Li, Q. (2015). Collaboration strategies and effects on university research: Evidence from Chinese universities. Scientometrics, 103(2), 725–749.

    Article  Google Scholar 

  • Wang, Y., Yuan, C., Zhang, S., & Wang, R. (2021). Moderation in all things: Industry-university-research alliance portfolio configuration and SMEs’ innovation performance in China. Journal of Small Business Management. https://doi.org/10.1080/00472778.2020.1867735

    Article  Google Scholar 

  • Wong, C. Y. (2013). On a path to creative destruction: Science, technology and science-based technological trajectories of Japan and South Korea. Scientometrics, 96(1), 323–336.

    Article  Google Scholar 

  • Wu, C. Y., & Mathews, J. A. (2012). Knowledge flows in the solar photovoltaic industry: Insights from patenting by Taiwan, Korea, and China. Research Policy, 41(3), 524–540.

    Article  Google Scholar 

  • Zhang, D., Banker, R. D., Li, X., & Liu, W. (2011). Performance impact of research policy at the Chinese Academy of Sciences. Research Policy, 40(6), 875–885.

    Article  Google Scholar 

  • Zhang, G., & Tang, C. (2018). How R&D partner diversity influences innovation performance: An empirical study in the nano-biopharmaceutical field. Scientometrics, 116(3), 1487–1512.

    Article  Google Scholar 

  • Zhang, J., Yan, Y., & Guan, J. (2015). Scientific relatedness in solar energy: A comparative study between the USA and China. Scientometrics, 102(2), 1595–1613.

    Article  Google Scholar 

  • Zhang, S., Yuan, C., & Han, C. (2020). Industry–university–research alliance portfolio size and firm performance: the contingent role of political connections. Journal of Technology Transfer, 45(5), 1505.

    Article  Google Scholar 

  • Zhang, Y., Chen, K., & Fu, X. (2019). Scientific effects of Triple Helix interactions among research institutes, industries and universities. Technovation, 86, 33–47. https://doi.org/10.1016/j.technovation.2019.05.003

    Article  Google Scholar 

  • Zhang, Y., Chen, K., Zhu, G., Yam, R. C., & Guan, J. (2016). Inter-organizational scientific collaborations and policy effects: An ego-network evolutionary perspective of the Chinese Academy of Sciences. Scientometrics, 108(3), 1383–1415.

    Article  Google Scholar 

  • Zhao, Q. (2018). Electromobility research in Germany and China: Structural differences. Scientometrics, 117(1), 473–493.

    Article  Google Scholar 

  • Zhou, J., Wu, R., & Li, J. (2019). More ties the merrier? Different social ties and firm innovation performance. Asia Pacific Journal of Management, 36(2), 445–471.

    Article  Google Scholar 

  • Zhuang, T., Zhao, S., Zheng, M., & Chu, J. (2021). Triple helix relationship research on China’s regional university–industry–government collaborative innovation: Based on provincial patent data. Growth and Change, 52, 1361–1386.

    Article  Google Scholar 

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Acknowledgements

This work was supported by National Research Foundation of Korea [Grant Number NRF-2020R1A2B5B01002243]; Ministry of Science and ICT, South Korea [Grant Number IITP-2021-2018-0-01402].

Funding

National Research Foundation of Korea, NRF-2020R1A2B5B01002243, Jae-Yong Choung, Ministry of Science and ICT, IITP-2022-2018-0-01402, Jae-Yong Choung.

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Jang, B., Choung, JY. & Kang, I. Knowledge production patterns of China and the US: quantum technology. Scientometrics 127, 5691–5719 (2022). https://doi.org/10.1007/s11192-022-04478-4

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