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Effect of collaboration network structure on knowledge creation and technological performance: the case of biotechnology in Canada

Author

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  • Hamidreza Eslami

    (Concordia University)

  • Ashkan Ebadi

    (Concordia University)

  • Andrea Schiffauerova

    (Concordia University)

Abstract

Many of the novel ideas that lead to scientific publications or yield technological advances are the result of collaborations among scientists or inventors. Although various aspects of collaboration networks have been examined, the impact of many network characteristics on knowledge creation and innovation production remains unclear due to the inconsistency of the conclusions from various research studies. One such network structure, called small world, has recently attracted much theoretical attention as it has been suggested that it can enhance the information transmission efficiency among the network actors. However, the existing empirical studies have failed to provide consistent results regarding the effect of small-world network properties on network performance in terms of its scientific and technological productivity. In this paper, using the data on 29 years of journal publications and patents in the field of biotechnology in Canada, the network of scientists’ collaboration activities has been constructed based on their co-authorships in scientific articles. Various structural properties of this network have been measured and the relationships between the network structure and knowledge creation, and quantity and quality of technological performance have been examined. We found that the structure of the co-authorship network of Canadian biotechnology scientists has a significant effect on the knowledge and innovation production, but it produced no impact on the quality of patents generated by these scientists.

Suggested Citation

  • Hamidreza Eslami & Ashkan Ebadi & Andrea Schiffauerova, 2013. "Effect of collaboration network structure on knowledge creation and technological performance: the case of biotechnology in Canada," Scientometrics, Springer;Akadémiai Kiadó, vol. 97(1), pages 99-119, October.
    • Handle: RePEc:spr:scient:v:97:y:2013:i:1:d:10.1007_s11192-013-1069-6
    DOI: 10.1007/s11192-013-1069-6
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    Cited by:

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    4. Martine Gadille & Juan Ramón Gallego-Bono, 2021. "Rebuilding a Cluster While Protecting Knowledge within Low-Medium-Tech Supplier SMEs: A Spanish and French Comparison," Sustainability, MDPI, vol. 13(20), pages 1-35, October.
    5. Cristina Páez-Avilés & Frank J. Rijnsoever & Esteve Juanola-Feliu & Josep Samitier, 2018. "Multi-disciplinarity breeds diversity: the influence of innovation project characteristics on diversity creation in nanotechnology," The Journal of Technology Transfer, Springer, vol. 43(2), pages 458-481, April.
    6. Yan Yan & Jiancheng Guan, 2018. "How multiple networks help in creating knowledge: evidence from alternative energy patents," Scientometrics, Springer;Akadémiai Kiadó, vol. 115(1), pages 51-77, April.
    7. Xu Bai & Jinxi Wu & Yun Liu & Yihan Xu, 2020. "Research on the impact of global innovation network on 3D printing industry performance," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(2), pages 1015-1051, August.
    8. Yue, Zenghui & Xu, Haiyun & Yuan, Guoting & Pang, Hongshen, 2019. "Modeling study of knowledge diffusion in scientific collaboration networks based on differential dynamics: A case study in graphene field," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 524(C), pages 375-391.
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    15. repec:ags:aaea22:335781 is not listed on IDEAS
    16. Yuandi Wang & Jian Li & Lutao Ning & Deming Zeng & Xin Gu, 2014. "Dynamic patterns of technology collaboration: a case study of the Chinese automobile industry, 1985–2010," Scientometrics, Springer;Akadémiai Kiadó, vol. 101(1), pages 663-683, October.
    17. Jun-Ping Qiu & Ke Dong & Hou-Qiang Yu, 2014. "Comparative study on structure and correlation among author co-occurrence networks in bibliometrics," Scientometrics, Springer;Akadémiai Kiadó, vol. 101(2), pages 1345-1360, November.
    18. Anahita Hajibabaei & Andrea Schiffauerova & Ashkan Ebadi, 2023. "Women and key positions in scientific collaboration networks: analyzing central scientists’ profiles in the artificial intelligence ecosystem through a gender lens," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(2), pages 1219-1240, February.
    19. Ebadi, Ashkan & Schiffauerova, Andrea, 2015. "How to become an important player in scientific collaboration networks?," Journal of Informetrics, Elsevier, vol. 9(4), pages 809-825.
    20. Guan, JianCheng & Zuo, KaiRui & Chen, KaiHua & Yam, Richard C.M., 2016. "Does country-level R&D efficiency benefit from the collaboration network structure?," Research Policy, Elsevier, vol. 45(4), pages 770-784.
    21. 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.
    22. Faatiema Salie & Kylie Jager & Carsten Dreher & Tania S. Douglas, 2019. "The scientific base for orthopaedic device development in South Africa: spatial and sectoral evolution of knowledge development," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(1), pages 31-54, April.
    23. Fahimeh Ghasemian & Kamran Zamanifar & Nasser Ghasem-Aghaee, 2019. "Composing Scientific Collaborations Based on Scholars’ Rank in Hypergraph," Information Systems Frontiers, Springer, vol. 21(3), pages 687-702, June.

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