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Knowledge Innovation Effect of University Computing Power in China: Evidence from the top500 Supercomputers

Author

Listed:
  • Yang Haodong

    (University of Science and Technology of China)

  • Liu Jialin

    (University of Science and Technology of China)

  • Wang Gaofeng

    (University of Science and Technology of China)

Abstract

With the increasingly prominent characteristics of data-intensive and AI-driven scientific paradigms, computing power has become a crucial pillar of research activities. This study aims to examine the knowledge innovation effects of university supercomputing development by theoretically proposing two mechanisms: the efficiency effect (including technical and nontechnical factors) and the scale effect. Empirically, we match the extracted scientific publications of universities via Web of Science with supercomputer information from the top 500 rankings, constructing a panel dataset of 110 distinguished universities in China. Within the causal inference framework, the spatial difference-in-differences method (spatial DID) is employed to assess the impact of university computing power "upgrades" on knowledge innovation. The research findings include: (1) Overall, supercomputing construction stimulates knowledge innovation in universities, primarily manifested in the increase in the number of general papers and highly cited papers cataloged by the Science Citation Index (SCI). (2) Knowledge innovation effects have a lag period of approximately one–four years and may have a negative impact on innovation in geographically and economically adjacent universities. (3) Supercomputing construction mainly promotes university knowledge innovation by improving innovation efficiency (efficiency effect), accounting for 85.0% ~ 96.5% of the total effect. Among these factors, the proportion of nontechnical factors is at most 38.0%. In contrast, the scale effect accounts for a maximum of 15.0%, which is achieved mainly through an increase in the scale of research personnel. (4) There is significant interuniversity heterogeneity in the knowledge innovation effects of supercomputing, with Tsinghua University, Shanghai Jiao Tong University, and Jilin University showing the most significant effects. Additionally, we provide a series of potential optimization utility lists for universities, which, together with benchmark and mechanism tests, constitute a complete policy sandbox.

Suggested Citation

  • Yang Haodong & Liu Jialin & Wang Gaofeng, 2025. "Knowledge Innovation Effect of University Computing Power in China: Evidence from the top500 Supercomputers," Research in Higher Education, Springer;Association for Institutional Research, vol. 66(1), pages 1-30, February.
    • Handle: RePEc:spr:reihed:v:66:y:2025:i:1:d:10.1007_s11162-024-09822-6
    DOI: 10.1007/s11162-024-09822-6
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    1. Ge, Shuang & Liu, Xielin, 2022. "The role of knowledge creation, absorption and acquisition in determining national competitive advantage," Technovation, Elsevier, vol. 112(C).
    2. Etzkowitz, Henry & Leydesdorff, Loet, 2000. "The dynamics of innovation: from National Systems and "Mode 2" to a Triple Helix of university-industry-government relations," Research Policy, Elsevier, vol. 29(2), pages 109-123, February.
    3. V. Krishnan & Saurabh Gupta, 2001. "Appropriateness and Impact of Platform-Based Product Development," Management Science, INFORMS, vol. 47(1), pages 52-68, January.
    4. Wang, Xuliang & Xu, Lulu & Ye, Qin & He, Shi & Liu, Yi, 2022. "How does services agglomeration affect the energy efficiency of the service sector? Evidence from China," Energy Economics, Elsevier, vol. 112(C).
    5. Philip Cooke, 2012. "From Clusters to Platform Policies in Regional Development," European Planning Studies, Taylor & Francis Journals, vol. 20(8), pages 1415-1424, August.
    6. William D. Nordhaus, 2001. "The Progress of Computing," Cowles Foundation Discussion Papers 1324, Cowles Foundation for Research in Economics, Yale University.
    7. Thi Bich Hanh Tran & Anh Dung Vu, 2022. "Effect of university-enterprise alliance orientation on university’s innovation performance and market performance: evidence from Vietnam," Journal of Marketing for Higher Education, Taylor & Francis Journals, vol. 32(2), pages 238-258, July.
    8. Dmitry Arkhangelsky & Susan Athey & David A. Hirshberg & Guido W. Imbens & Stefan Wager, 2021. "Synthetic Difference-in-Differences," American Economic Review, American Economic Association, vol. 111(12), pages 4088-4118, December.
    9. Alberto Abadie, 2005. "Semiparametric Difference-in-Differences Estimators," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 72(1), pages 1-19.
    10. Yang, Xuehui & Zhang, Huirong & Lin, Shanlang & Zhang, Jiaping & Zeng, Jianlong, 2021. "Does high-speed railway promote regional innovation growth or innovation convergence?," Technology in Society, Elsevier, vol. 64(C).
    11. Marynia Kolak & Luc Anselin, 2020. "A Spatial Perspective on the Econometrics of Program Evaluation," International Regional Science Review, , vol. 43(1-2), pages 128-153, January.
    12. Romer, Paul M, 1990. "Endogenous Technological Change," Journal of Political Economy, University of Chicago Press, vol. 98(5), pages 71-102, October.
    13. Marcus Conlé & Tobias ten Brink & Wei Zhao, 2023. "Innovation platforms as a tool for anchoring non-local knowledge: smart specialisation strategies in Guangdong, China," Industry and Innovation, Taylor & Francis Journals, vol. 30(6), pages 694-718, July.
    14. Fan-Chuan Tseng & Mu-Hsuan Huang & Dar-Zen Chen, 2020. "Factors of university–industry collaboration affecting university innovation performance," The Journal of Technology Transfer, Springer, vol. 45(2), pages 560-577, April.
    15. Yun Liu & Mengya Zhang & Gupeng Zhang & Xiongxiong You, 2022. "Scientific elites versus other scientists: who are better at taking advantage of the research collaboration network?," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(6), pages 3145-3166, June.
    16. Goodman-Bacon, Andrew, 2021. "Difference-in-differences with variation in treatment timing," Journal of Econometrics, Elsevier, vol. 225(2), pages 254-277.
    17. Klüppel, Leonardo & Knott, Anne Marie, 2023. "Are ideas being fished out?," Research Policy, Elsevier, vol. 52(2).
    18. Akter, Shahriar & Hossain, Md Afnan & Sajib, Shahriar & Sultana, Saida & Rahman, Mahfuzur & Vrontis, Demetris & McCarthy, Grace, 2023. "A framework for AI-powered service innovation capability: Review and agenda for future research," Technovation, Elsevier, vol. 125(C).
    19. Sant’Anna, Pedro H.C. & Zhao, Jun, 2020. "Doubly robust difference-in-differences estimators," Journal of Econometrics, Elsevier, vol. 219(1), pages 101-122.
    20. Koellinger, Philipp, 2008. "The relationship between technology, innovation, and firm performance--Empirical evidence from e-business in Europe," Research Policy, Elsevier, vol. 37(8), pages 1317-1328, September.
    21. Chan, Yolande E. & Krishnamurthy, Rashmi & Sadreddin, Arman, 2022. "Digitally-enabled university incubation processes," Technovation, Elsevier, vol. 118(C).
    22. J. Paul Elhorst, 2014. "Matlab Software for Spatial Panels," International Regional Science Review, , vol. 37(3), pages 389-405, July.
    23. Wu, Ning & Liu, ZuanKuo, 2021. "Higher education development, technological innovation and industrial structure upgrade," Technological Forecasting and Social Change, Elsevier, vol. 162(C).
    24. Jonbekova, Dilrabo & Sparks, Jason & Hartley, Matthew & Kuchumova, Gulfiya, 2020. "Development of university–industry partnerships in Kazakhstan: Innovation under constraint," International Journal of Educational Development, Elsevier, vol. 79(C).
    25. Haodong Yang & Li Liu & Gaofeng Wang, 2024. "Does large-scale research infrastructure affect regional knowledge innovation, and how? A case study of the National Supercomputing Center in China," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-20, December.
    26. Jiancheng Guan & He Wei, 2015. "A bilateral comparison of research performance at an institutional level," Scientometrics, Springer;Akadémiai Kiadó, vol. 104(1), pages 147-173, July.
    27. Zhang, Han & Patton, Donald & Kenney, Martin, 2013. "Building global-class universities: Assessing the impact of the 985 Project," Research Policy, Elsevier, vol. 42(3), pages 765-775.
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