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Dynamic evolution of collaborative networks: evidence from nano-energy research in China

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  • Na Liu

    (University of Chinese Academy of Sciences)

  • Jiancheng Guan

    (University of Chinese Academy of Sciences
    Fudan University)

Abstract

In organizations, knowledge creation activities are embedded in collaborative networks and are influenced by their partners. Therefore, we examine how entire networks change over time in this study, as well as the reasoning behind the structures of ego networks based on unique scientific research discoveries published in the emerging cross-disciplinary field of nano-energy. These data were extracted from Science Citation Index Expanded. Specifically, we mainly focus on two dimensions of ego network changes: network growth and diversity. Results demonstrate the recent remarkable growth of inter-organizational collaborative networks in the nano-energy field and empirically prove that the subsequent growth and diversity of ego networks are caused by three coexisting driving forces (collaborative capacity, network status position and cohesion) that act collectively. Our study is conducted at the organizational level because we investigate the universities, research institutes and firms that participate in nano-energy scientific research and the collaborative networks formed through co-authorships among these institutions in knowledge creation processes. Moreover, our study has significant implications for the scientific research conducted by organizations in developing countries and emerging fields.

Suggested Citation

  • Na Liu & Jiancheng Guan, 2015. "Dynamic evolution of collaborative networks: evidence from nano-energy research in China," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(3), pages 1895-1919, March.
    • Handle: RePEc:spr:scient:v:102:y:2015:i:3:d:10.1007_s11192-014-1508-z
    DOI: 10.1007/s11192-014-1508-z
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    Cited by:

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    2. Guan, JianCheng & Zhang, JingJing, 2018. "The dynamics of partner and knowledge portfolios in alternative energy field," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 2869-2879.
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    5. Guijie Zhang & Luning Liu & Fangfang Wei, 2019. "Key nodes mining in the inventor–author knowledge diffusion network," Scientometrics, Springer;Akadémiai Kiadó, vol. 118(3), pages 721-735, March.

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