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Development strategy and collaboration preference in S&T of enterprises based on funded papers: a case study of Google

Author

Listed:
  • Rongying Zhao

    (Wuhan University
    Wuhan University
    Wuhan University)

  • Xinlai Li

    (Wuhan University
    Wuhan University
    Wuhan University)

  • Zhisen Liang

    (Wuhan University
    Wuhan University
    Wuhan University)

  • Danyang Li

    (Wuhan University
    Wuhan University
    Wuhan University)

Abstract

Science funding plays a guiding role in the development direction of scientific innovation. As one of research funding providers, private companies influence the development of science and technology (S&T) through their selective support. Thus, strategy and layout of enterprises in S&T can be revealed by analysing their funded papers. Taking Google as the example, the paper proposes an analytical method of funded papers by the combination of co-word analysis, clusters analysis and social network analysis, so as to explore the scientific strategy and collaboration preference. The total 2162 valid bibliographic records of papers supported by Google from the Thomson Reuters Web of Science are divided into four groups according to discipline clusters using Hierarchical Clustering Algorithm. Social network analysis is conducted to detect communities among keywords and institutions. The results demonstrate that Google shows different funding patterns between traditional research fields and emerging industries. Famous universities are the main funding targets of Google, and the important institutions can be divided into two groups.

Suggested Citation

  • Rongying Zhao & Xinlai Li & Zhisen Liang & Danyang Li, 2019. "Development strategy and collaboration preference in S&T of enterprises based on funded papers: a case study of Google," Scientometrics, Springer;Akadémiai Kiadó, vol. 121(1), pages 323-347, October.
    • Handle: RePEc:spr:scient:v:121:y:2019:i:1:d:10.1007_s11192-019-03182-0
    DOI: 10.1007/s11192-019-03182-0
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    2. Chen, Hongshu & Jin, Qianqian & Wang, Ximeng & Xiong, Fei, 2022. "Profiling academic-industrial collaborations in bibliometric-enhanced topic networks: A case study on digitalization research," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
    3. Manoj Kumar Verma & Daud Khan & Mayank Yuvaraj, 2023. "Scientometric assessment of funded scientometrics and bibliometrics research (2011–2021)," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(8), pages 4305-4320, August.

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