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Visualization and quantitative study in bibliographic databases: A case in the field of university–industry cooperation

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  • Feng, Feng
  • Zhang, Leiyong
  • Du, Yuneng
  • Wang, Weiguang

Abstract

CiteSpace is a visual document analysis software, by which performances and trends of certain disciplines can be displayed for a given period. Moreover, the evolution of a frontier research can be explored by such software as well. This research focuses on the visualization and quantitative study in bibliographic databases by taking the university–industry collaboration studies as an example. Using the Web of Science (WOS), 587 publications and over 30,000 references were selected for analysis, which produced the following results: (1) Our method can clearly reveal the key elements of certain disciplines, such as the largest share of publications, the most frequently cited authors and journals in the university–industry cooperation research field; (2) The relationships among the frequently cited authors, references, journals and keywords can be explained visually in the university–industry cooperation research field; (3) Of special note is that the potential problems and evolutionary trends of certain research fields such as university–industry cooperation can also be ascertained via our method; (4) In general, according to the case study, our visualization and quantitative method evolved a new research framework to evaluate the performance of some research areas.

Suggested Citation

  • Feng, Feng & Zhang, Leiyong & Du, Yuneng & Wang, Weiguang, 2015. "Visualization and quantitative study in bibliographic databases: A case in the field of university–industry cooperation," Journal of Informetrics, Elsevier, vol. 9(1), pages 118-134.
    • Handle: RePEc:eee:infome:v:9:y:2015:i:1:p:118-134
    DOI: 10.1016/j.joi.2014.11.009
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    7. Csomós, György & Tóth, Géza, 2016. "Exploring the position of cities in global corporate research and development: A bibliometric analysis by two different geographical approaches," Journal of Informetrics, Elsevier, vol. 10(2), pages 516-532.
    8. Seyedghorban, Zahra & Matanda, Margaret Jekanyika & LaPlaca, Peter, 2016. "Advancing theory and knowledge in the business-to-business branding literature," Journal of Business Research, Elsevier, vol. 69(8), pages 2664-2677.
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    11. Hong Jiang & Jinlong Gai & Shukuan Zhao & Peggy E. Chaudhry & Sohail S. Chaudhry, 2022. "Applications and development of artificial intelligence system from the perspective of system science: A bibliometric review," Systems Research and Behavioral Science, Wiley Blackwell, vol. 39(3), pages 361-378, May.
    12. Csomós György, 2017. "Mapping Spatial and Temporal Changes of Global Corporate Research and Development Activities by Conducting a Bibliometric Analysis," Quaestiones Geographicae, Sciendo, vol. 36(1), pages 65-77, March.
    13. Chengliang Liu & Qinchang Gui, 2016. "Mapping intellectual structures and dynamics of transport geography research: a scientometric overview from 1982 to 2014," Scientometrics, Springer;Akadémiai Kiadó, vol. 109(1), pages 159-184, October.
    14. Yanyi Huang & Xiu-Hao Ding & Ruihong Liu & Yuanqiong He & Suming Wu, 2019. "Reviewing the Domain of Technology and Innovation Management: A Visualizing Bibliometric Analysis," SAGE Open, , vol. 9(2), pages 21582440198, June.
    15. Shen, Neng & Deng, Rumeng & Liao, Haolan & Shevchuk, Oleksandr, 2020. "Mapping renewable energy subsidy policy research published from 1997 to 2018: A scientometric review," Utilities Policy, Elsevier, vol. 64(C).
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    17. Murashova Elena & Loginova Valeria, 2017. "University–Industry Interaction Trends in the Baltic Sea Region: A Bibliometric Analysis," TalTech Journal of European Studies, Sciendo, vol. 7(2), pages 28-58, October.

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