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Knowledge diffusion paths of blockchain domain: the main path analysis

Author

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  • Dejian Yu

    (Nanjing Audit University)

  • Libo Sheng

    (Nanjing Audit University)

Abstract

Blockchain technology, as a disruptive technology, has received widespread attention in the past few years from all over the world, leading to rapid growth in research outputs. This paper adopts a quantitative method, the main path analysis, to comprehensively and systematically investigate the development trajectories of blockchain. Four different main paths, the global main path, the forward local main path, the backward local main path and the key-route main path are conducted simultaneously. By analyzing these various paths, on the one hand, this paper finds that papers on paths focus on two aspects, cryptocurrencies and blockchain-based applications. On the other hand, this paper discovers several major research areas of blockchain, including internet of things (IoT), healthcare, energy industry, voting, insurance and supply chain management. At the same time, this paper further analyzes the research hotspots, as well as the development trajectories of blockchain in the areas of IoT, healthcare and supply chain management by using the key-route main path analysis. This paper is conductive for both the new and experienced researchers to identify some influential papers and grasp the knowledge diffusion paths in these domains.

Suggested Citation

  • Dejian Yu & Libo Sheng, 2020. "Knowledge diffusion paths of blockchain domain: the main path analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(1), pages 471-497, October.
    • Handle: RePEc:spr:scient:v:125:y:2020:i:1:d:10.1007_s11192-020-03650-y
    DOI: 10.1007/s11192-020-03650-y
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    Cited by:

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    4. Siddique, Maryam, 2023. "Does the Adaptive Market Hypothesis Exist in Equity Market? Evidence from Pakistan Stock Exchange," OSF Preprints 9b5dx, Center for Open Science.
    5. Song, Haoyang & Hou, Jianhua & Zhang, Yang, 2022. "Catalytic capacity of technological innovation: Multidimensional definition and measurement from the perspective of knowledge spillover," Technology in Society, Elsevier, vol. 68(C).
    6. Abderahman Rejeb & Alireza Abdollahi & Karim Rejeb & Mohamed M. Mostafa, 2023. "Tracing knowledge evolution flows in scholarly restaurant research: a main path analysis," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(3), pages 2183-2209, June.
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    8. Kim, Erin H.J. & Jeong, Yoo Kyung & Kim, YongHwan & Song, Min, 2022. "Exploring scientific trajectories of a large-scale dataset using topic-integrated path extraction," Journal of Informetrics, Elsevier, vol. 16(1).
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    10. Yu, Dejian & Pan, Tianxing, 2021. "Tracing the main path of interdisciplinary research considering citation preference: A case from blockchain domain," Journal of Informetrics, Elsevier, vol. 15(2).
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    12. Zenghui Yue & Haiyun Xu & Guoting Yuan & Yan Qi, 2022. "Modeling knowledge diffusion in the disciplinary citation network based on differential dynamics," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(12), pages 7593-7613, December.
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    14. Ichiro Watanabe & Soichiro Takagi, 2021. "Technological Trajectory Analysis of Patent Citation Networks: Examining the Technological Evolution of Computer Graphic Processing Systems," The Review of Socionetwork Strategies, Springer, vol. 15(1), pages 1-25, June.
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