IDEAS home Printed from https://ideas.repec.org/a/eee/tefoso/v172y2021ics0040162521005035.html
   My bibliography  Save this article

Rethinking the disruption index as a measure of scientific and technological advances

Author

Listed:
  • Ruan, Xuanmin
  • Lyu, Dongqing
  • Gong, Kaile
  • Cheng, Ying
  • Li, Jiang

Abstract

Wu et al. (2019) used the disruption(D) index to measure scientific and technological advances in Nature. Their findings spurred extensive discussion in academia on whether we can measure the disruption (i.e., innovation or novelty) of a research paper or a patent based on the number of citations. In this paper, we calculate the D index of ∼0.76 million publications published between 1954 and 2013 in six disciplines including both sciences and social sciences in English and Chinese. We found that the number of references has a negative effect on the D index of a paper with a relatively small number of references, and a positive effect on the D index of a paper with a large number of references. We also found that low coverage of a citation database boosts D values. Specifically, low coverage of non-journal literature in the Web of Science (WOS) boosted D values in social sciences, and the exclusion of non-Chinese language literature in the Chinese Social Sciences Citation Index (CSSCI) resulted in the inflation of D values in Chinese language literature. Limitations of the D index observed in scientific papers also exist in technological patents. This paper sheds light on the use of citation-based measurements of scientific and technological advances and highlights the limitations of this index.

Suggested Citation

  • Ruan, Xuanmin & Lyu, Dongqing & Gong, Kaile & Cheng, Ying & Li, Jiang, 2021. "Rethinking the disruption index as a measure of scientific and technological advances," Technological Forecasting and Social Change, Elsevier, vol. 172(C).
    • Handle: RePEc:eee:tefoso:v:172:y:2021:i:c:s0040162521005035
    DOI: 10.1016/j.techfore.2021.121071
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0040162521005035
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.techfore.2021.121071?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Vincent Larivière & Éric Archambault & Yves Gingras & Étienne Vignola‐Gagné, 2006. "The place of serials in referencing practices: Comparing natural sciences and engineering with social sciences and humanities," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 57(8), pages 997-1004, June.
    2. 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.
    3. Hanna-Mari Puuska & Reetta Muhonen & Yrjö Leino, 2014. "International and domestic co-publishing and their citation impact in different disciplines," Scientometrics, Springer;Akadémiai Kiadó, vol. 98(2), pages 823-839, February.
    4. Didegah, Fereshteh & Thelwall, Mike, 2013. "Which factors help authors produce the highest impact research? Collaboration, journal and document properties," Journal of Informetrics, Elsevier, vol. 7(4), pages 861-873.
    5. Russell J. Funk & Jason Owen-Smith, 2017. "A Dynamic Network Measure of Technological Change," Management Science, INFORMS, vol. 63(3), pages 791-817, March.
    6. Michael Gusenbauer, 2019. "Google Scholar to overshadow them all? Comparing the sizes of 12 academic search engines and bibliographic databases," Scientometrics, Springer;Akadémiai Kiadó, vol. 118(1), pages 177-214, January.
    7. Lutz Bornmann & Alexander Tekles, 2019. "Disruptive papers published in Scientometrics," Scientometrics, Springer;Akadémiai Kiadó, vol. 120(1), pages 331-336, July.
    8. Martín-Martín, Alberto & Orduna-Malea, Enrique & Thelwall, Mike & Delgado López-Cózar, Emilio, 2018. "Google Scholar, Web of Science, and Scopus: A systematic comparison of citations in 252 subject categories," Journal of Informetrics, Elsevier, vol. 12(4), pages 1160-1177.
    9. Lingfei Wu & Dashun Wang & James A. Evans, 2019. "Large teams develop and small teams disrupt science and technology," Nature, Nature, vol. 566(7744), pages 378-382, February.
    10. Lutz Bornmann & Sitaram Devarakonda & Alexander Tekles & George Chacko, 2020. "Disruptive papers published in Scientometrics: meaningful results by using an improved variant of the disruption index originally proposed by Wu, Wang, and Evans (2019)," Scientometrics, Springer;Akadémiai Kiadó, vol. 123(2), pages 1149-1155, May.
    11. 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.
    12. Juan Xie & Kaile Gong & Jiang Li & Qing Ke & Hyonchol Kang & Ying Cheng, 2019. "A probe into 66 factors which are possibly associated with the number of citations an article received," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(3), pages 1429-1454, June.
    13. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Zhang, Ming-Ze & Wang, Tang-Rong & Lyu, Peng-Hui & Chen, Qi-Mei & Li, Ze-Xia & Ngai, Eric W.T., 2024. "Impact of gender composition of academic teams on disruptive output," Journal of Informetrics, Elsevier, vol. 18(2).
    2. Macher, Jeffrey T. & Rutzer, Christian & Weder, Rolf, 2024. "Is there a secular decline in disruptive patents? Correcting for measurement bias," Research Policy, Elsevier, vol. 53(5).
    3. Hu, Zewen & Zhou, Xiji & Lin, Angela, 2023. "Evaluation and identification of potential high-value patents in the field of integrated circuits using a multidimensional patent indicators pre-screening strategy and machine learning approaches," Journal of Informetrics, Elsevier, vol. 17(2).
    4. Ruijie Wang & Yuhao Zhou & An Zeng, 2023. "Evaluating scientists by citation and disruption of their representative works," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(3), pages 1689-1710, March.
    5. Libo Sheng & Dongqing Lyu & Xuanmin Ruan & Hongquan Shen & Ying Cheng, 2023. "The association between prior knowledge and the disruption of an article," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(8), pages 4731-4751, August.
    6. Yuyan Jiang & Xueli Liu, 2023. "A Bibliometric Analysis and Disruptive Innovation Evaluation for the Field of Energy Security," Sustainability, MDPI, vol. 15(2), pages 1-29, January.
    7. Ao, Weiyi & Lyu, Dongqing & Ruan, Xuanmin & Li, Jiang & Cheng, Ying, 2023. "Scientific creativity patterns in scholars’ academic careers: Evidence from PubMed," Journal of Informetrics, Elsevier, vol. 17(4).
    8. Yuyan Jiang & Xueli Liu, 2023. "A construction and empirical research of the journal disruption index based on open citation data," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(7), pages 3935-3958, July.
    9. Yang, Alex Jie & Wu, Linwei & Zhang, Qi & Wang, Hao & Deng, Sanhong, 2023. "The k-step h-index in citation networks at the paper, author, and institution levels," Journal of Informetrics, Elsevier, vol. 17(4).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Peter Sjögårde & Fereshteh Didegah, 2022. "The association between topic growth and citation impact of research publications," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(4), pages 1903-1921, April.
    2. Libo Sheng & Dongqing Lyu & Xuanmin Ruan & Hongquan Shen & Ying Cheng, 2023. "The association between prior knowledge and the disruption of an article," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(8), pages 4731-4751, August.
    3. Dongqing Lyu & Kaile Gong & Xuanmin Ruan & Ying Cheng & Jiang Li, 2021. "Does research collaboration influence the “disruption” of articles? Evidence from neurosciences," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(1), pages 287-303, January.
    4. Keye Wu & Ziyue Xie & Jia Tina Du, 2024. "Does science disrupt technology? Examining science intensity, novelty, and recency through patent-paper citations in the pharmaceutical field," Scientometrics, Springer;Akadémiai Kiadó, vol. 129(9), pages 5469-5491, September.
    5. Bornmann, Lutz & Tekles, Alexander, 2021. "Convergent validity of several indicators measuring disruptiveness with milestone assignments to physics papers by experts," Journal of Informetrics, Elsevier, vol. 15(3).
    6. Yue Wang & Ning Li & Bin Zhang & Qian Huang & Jian Wu & Yang Wang, 2023. "The effect of structural holes on producing novel and disruptive research in physics," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(3), pages 1801-1823, March.
    7. Zhongyi Wang & Keying Wang & Jiyue Liu & Jing Huang & Haihua Chen, 2022. "Measuring the innovation of method knowledge elements in scientific literature," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(5), pages 2803-2827, May.
    8. Zhang, Xinyuan & Xie, Qing & Song, Min, 2021. "Measuring the impact of novelty, bibliometric, and academic-network factors on citation count using a neural network," Journal of Informetrics, Elsevier, vol. 15(2).
    9. António Osório & Lutz Bornmann, 2021. "On the disruptive power of small-teams research," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(1), pages 117-133, January.
    10. Leydesdorff, Loet & Bornmann, Lutz, 2021. "Disruption indices and their calculation using web-of-science data: Indicators of historical developments or evolutionary dynamics?," Journal of Informetrics, Elsevier, vol. 15(4).
    11. Zhang, Ming-Ze & Wang, Tang-Rong & Lyu, Peng-Hui & Chen, Qi-Mei & Li, Ze-Xia & Ngai, Eric W.T., 2024. "Impact of gender composition of academic teams on disruptive output," Journal of Informetrics, Elsevier, vol. 18(2).
    12. Martorell Cunil, Onofre & Otero González, Luis & Durán Santomil, Pablo & Mulet Forteza, Carlos, 2023. "How to accomplish a highly cited paper in the tourism, leisure and hospitality field," Journal of Business Research, Elsevier, vol. 157(C).
    13. Liu, Jialin & Chen, Hongkan & Liu, Zhibo & Bu, Yi & Gu, Weiye, 2022. "Non-linearity between referencing behavior and citation impact: A large-scale, discipline-level analysis," Journal of Informetrics, Elsevier, vol. 16(3).
    14. Liu, Qiuling & Guo, Lei & Sun, Yiping & Ren, Linlin & Wang, Xinhua & Han, Xiaohui, 2024. "Do scholars' collaborative tendencies impact the quality of their publications? A generalized propensity score matching analysis," Journal of Informetrics, Elsevier, vol. 18(1).
    15. Ruijie Wang & Yuhao Zhou & An Zeng, 2023. "Evaluating scientists by citation and disruption of their representative works," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(3), pages 1689-1710, March.
    16. Elizabeth S. Vieira, 2023. "The influence of research collaboration on citation impact: the countries in the European Innovation Scoreboard," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(6), pages 3555-3579, June.
    17. Hou, Jianhua & Li, Hao & Zhang, Yang, 2024. "Influence of interdisciplinarity of scientific papers on the durability of citation diffusion: A perspective from citation discontinuance," Journal of Informetrics, Elsevier, vol. 18(3).
    18. Hongquan Shen & Juan Xie & Jiang Li & Ying Cheng, 2021. "The correlation between scientific collaboration and citation count at the paper level: a meta-analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(4), pages 3443-3470, April.
    19. Ruan, Xuanmin & Zhu, Yuanyang & Li, Jiang & Cheng, Ying, 2020. "Predicting the citation counts of individual papers via a BP neural network," Journal of Informetrics, Elsevier, vol. 14(3).
    20. Raminta Pranckutė, 2021. "Web of Science (WoS) and Scopus: The Titans of Bibliographic Information in Today’s Academic World," Publications, MDPI, vol. 9(1), pages 1-59, March.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:tefoso:v:172:y:2021:i:c:s0040162521005035. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.sciencedirect.com/science/journal/00401625 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.