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

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  • 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
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    Cited by:

    1. 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).
    2. 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.
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    4. 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.
    5. 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.

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