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Diffusion and adoption: an explanatory model of “question mark” and “rising star” articles

Author

Listed:
  • Guoqiang Liang

    (Dalian University of Technology
    Indiana University)

  • Haiyan Hou

    (Dalian University of Technology)

  • Qiao Chen

    (Dalian University of Technology)

  • Zhigang Hu

    (Dalian University of Technology)

Abstract

The creative process is essentially Darwinian, and only a small proportion of creative ideas have been selected for further development. This article builds a diffusion–adoption model of academic articles and re-explores the influencing factors of “highly used but rarely cited” and “lowly used but highly cited” papers. Looking through the lens of Rogers’s innovation diffusion theory provides a new perspective on the citation mechanism and advances our understanding of what citation counts measure. Here, we take highly used (top 1%) articles published in the year 2013 in Web of Science as examples of the most successfully diffused papers and classify these articles into four groups, based on the Boston consulting group matrix. We then classify the diffusion and adoption of these articles into three stages, namely: idea gatekeeping, idea spreading, and action, and compare the difference between question mark and rising star articles on funding, number of references, publishing time, journal quartile, and number of authors. Results show that publishing time (β = 1.820) and usage count (β = 0.899) act as positive independents, and references (β = − 0.016) act as a negative independent to the adoption rate of rising star articles (p

Suggested Citation

  • Guoqiang Liang & Haiyan Hou & Qiao Chen & Zhigang Hu, 2020. "Diffusion and adoption: an explanatory model of “question mark” and “rising star” articles," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(1), pages 219-232, July.
    • Handle: RePEc:spr:scient:v:124:y:2020:i:1:d:10.1007_s11192-020-03478-6
    DOI: 10.1007/s11192-020-03478-6
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    References listed on IDEAS

    as
    1. Loet Leydesdorff, 2012. "Accounting for the uncertainty in the evaluation of percentile ranks," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 63(11), pages 2349-2350, November.
    2. Bornmann, Lutz & Leydesdorff, Loet & Wang, Jian, 2014. "How to improve the prediction based on citation impact percentiles for years shortly after the publication date?," Journal of Informetrics, Elsevier, vol. 8(1), pages 175-180.
    3. Yujia Zhai & Ying Ding & Fang Wang, 2018. "Measuring the diffusion of an innovation: A citation analysis," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 69(3), pages 368-379, March.
    4. Wang, Jian & Veugelers, Reinhilde & Stephan, Paula, 2017. "Bias against novelty in science: A cautionary tale for users of bibliometric indicators," Research Policy, Elsevier, vol. 46(8), pages 1416-1436.
    5. Lutz Bornmann & Werner Marx, 2014. "The wisdom of citing scientists," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 65(6), pages 1288-1292, June.
    6. Veugelers, Reinhilde & Wang, Jian, 2019. "Scientific novelty and technological impact," Research Policy, Elsevier, vol. 48(6), pages 1362-1372.
    7. Guoqiang Liang & Haiyan Hou & Xiaodan Lou & Zhigang Hu, 2019. "Qualifying threshold of “take-off” stage for successfully disseminated creative ideas," Scientometrics, Springer;Akadémiai Kiadó, vol. 120(3), pages 1193-1208, September.
    8. Per Ahlgren & Cristian Colliander & Peter Sjögårde, 2018. "Exploring the relation between referencing practices and citation impact: A large†scale study based on Web of Science data," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 69(5), pages 728-743, May.
    9. Lutz Bornmann, 2013. "How to analyze percentile citation impact data meaningfully in bibliometrics: The statistical analysis of distributions, percentile rank classes, and top-cited papers," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 64(3), pages 587-595, March.
    10. Xianwen Wang & Chen Liu & Wenli Mao & Zhichao Fang, 2015. "Erratum to: The open access advantage considering citation, article usage and social media attention," Scientometrics, Springer;Akadémiai Kiadó, vol. 103(3), pages 1149-1149, June.
    11. Xianwen Wang & Chen Liu & Wenli Mao & Zhichao Fang, 2015. "The open access advantage considering citation, article usage and social media attention," Scientometrics, Springer;Akadémiai Kiadó, vol. 103(2), pages 555-564, May.
    12. Yassine Gargouri & Chawki Hajjem & Vincent Larivière & Yves Gingras & Les Carr & Tim Brody & Stevan Harnad, 2010. "Self-Selected or Mandated, Open Access Increases Citation Impact for Higher Quality Research," PLOS ONE, Public Library of Science, vol. 5(10), pages 1-12, October.
    13. Bornmann, Lutz, 2014. "Do altmetrics point to the broader impact of research? An overview of benefits and disadvantages of altmetrics," Journal of Informetrics, Elsevier, vol. 8(4), pages 895-903.
    14. Lee Fleming, 2001. "Recombinant Uncertainty in Technological Search," Management Science, INFORMS, vol. 47(1), pages 117-132, January.
    15. Jeffrey L. Furman & Scott Stern, 2011. "Climbing atop the Shoulders of Giants: The Impact of Institutions on Cumulative Research," American Economic Review, American Economic Association, vol. 101(5), pages 1933-1963, August.
    16. Xiangjie Kong & Huizhen Jiang & Wei Wang & Teshome Megersa Bekele & Zhenzhen Xu & Meng Wang, 2017. "Exploring dynamic research interest and academic influence for scientific collaborator recommendation," Scientometrics, Springer;Akadémiai Kiadó, vol. 113(1), pages 369-385, October.
    17. Lee, You-Na & Walsh, John P. & Wang, Jian, 2015. "Creativity in scientific teams: Unpacking novelty and impact," Research Policy, Elsevier, vol. 44(3), pages 684-697.
    18. Xianwen Wang & Zhichao Fang & Xiaoling Sun, 2016. "Usage patterns of scholarly articles on Web of Science: a study on Web of Science usage count," Scientometrics, Springer;Akadémiai Kiadó, vol. 109(2), pages 917-926, November.
    19. Natsuo Onodera & Fuyuki Yoshikane, 2015. "Factors affecting citation rates of research articles," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 66(4), pages 739-764, April.
    20. Hiroyuki Kodama & Kenji Watatani & Shintaro Sengoku, 2012. "Competency-based assessment of academic interdisciplinary research and implication to university management," Research Evaluation, Oxford University Press, vol. 22(2), pages 93-104, December.
    21. Chai, Sen & Menon, Anoop, 2019. "Breakthrough recognition: Bias against novelty and competition for attention," Research Policy, Elsevier, vol. 48(3), pages 733-747.
    22. Vincent Larivière & Yves Gingras & Cassidy R. Sugimoto & Andrew Tsou, 2015. "Team size matters: Collaboration and scientific impact since 1900," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 66(7), pages 1323-1332, July.
    23. Parolo, Pietro Della Briotta & Pan, Raj Kumar & Ghosh, Rumi & Huberman, Bernardo A. & Kaski, Kimmo & Fortunato, Santo, 2015. "Attention decay in science," Journal of Informetrics, Elsevier, vol. 9(4), pages 734-745.
    24. Chao Min & Ying Ding & Jiang Li & Yi Bu & Lei Pei & Jianjun Sun, 2018. "Innovation or imitation: The diffusion of citations," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 69(10), pages 1271-1282, October.
    25. Iman Tahamtan & Askar Safipour Afshar & Khadijeh Ahamdzadeh, 2016. "Factors affecting number of citations: a comprehensive review of the literature," Scientometrics, Springer;Akadémiai Kiadó, vol. 107(3), pages 1195-1225, June.
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