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Research on the formation mechanism of big data technology cooperation networks: empirical evidence from China

Author

Listed:
  • Yonghong Ma

    (Harbin Engineering University)

  • Xiaomeng Yang

    (Harbin Engineering University)

  • Sen Qu

    (Harbin Engineering University)

  • Lingkai Kong

    (Harbin Engineering University)

Abstract

The purpose of the present paper is to investigate the formation mechanism of big data technology cooperation networks by considering the combined effect of three key factors, i.e., the individual characteristics, relationship characteristics, and cooperation characteristics of research and development (R&D) entities. The utilized research data come from Chinese big data technology cooperation patents granted during the years 2009–2018. In this paper, an exponential random graph model is applied to study the impact of different indicators on a big data technology cooperation network. The results show that R&D capability and structural holes in the individual characteristics of R&D entities have negative impacts on the formation of big data technology cooperation networks. In contrast, R&D entities with a high degree centrality are beneficial to the development of big data technology cooperation networks. Regarding relationship characteristics, a trend of geographical homogeneity is obvious in the formation process of the examined big data technology cooperation network, while the effect of organisational homogeneity is nonsignificant. In terms of cooperation characteristics, the network tends to facilitate convergent cooperation and transitive cooperation rather than intermediary cooperation. The present results provide a scientific reference for entities working to build effective cooperation relationships and promote the sustainable development of big data technology.

Suggested Citation

  • Yonghong Ma & Xiaomeng Yang & Sen Qu & Lingkai Kong, 2022. "Research on the formation mechanism of big data technology cooperation networks: empirical evidence from China," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(3), pages 1273-1294, March.
    • Handle: RePEc:spr:scient:v:127:y:2022:i:3:d:10.1007_s11192-022-04270-4
    DOI: 10.1007/s11192-022-04270-4
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