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Introducing a novelty indicator for scientific research: validating the knowledge-based combinatorial approach

Author

Listed:
  • Kuniko Matsumoto

    (National Institute of Science and Technology Policy (NISTEP))

  • Sotaro Shibayama

    (Lund University)

  • Byeongwoo Kang

    (Hitotsubashi University)

  • Masatsura Igami

    (National Institute of Science and Technology Policy (NISTEP))

Abstract

Citation counts have long been considered as the primary bibliographic indicator for evaluating the quality of research—a practice premised on the assumption that citation count is reflective of the impact of a scientific publication. However, identifying several limitations in the use of citation counts alone, scholars have advanced the need for multifaceted quality evaluation methods. In this study, we apply a novelty indicator to quantify the degree of citation similarity between a focal paper and a pre-existing same-domain paper from various fields in the natural sciences by proposing a new way of identifying papers that fall into the same domain of focal papers using bibliometric data only. We also conduct a validation analysis, using Japanese survey data, to confirm its usefulness. Employing ordered logit and ordinary least squares regression models, this study tests the consistency between the novelty scores of 1871 Japanese papers published in the natural sciences between 2001 and 2006 and researchers’ subjective judgments of their novelty. The results show statistically positive correlations between novelty scores and researchers’ assessment of research types reflecting aspects of novelty in various natural science fields. As such, this study demonstrates that the proposed novelty indicator is a suitable means of identifying the novelty of various types of natural scientific research.

Suggested Citation

  • Kuniko Matsumoto & Sotaro Shibayama & Byeongwoo Kang & Masatsura Igami, 2021. "Introducing a novelty indicator for scientific research: validating the knowledge-based combinatorial approach," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(8), pages 6891-6915, August.
    • Handle: RePEc:spr:scient:v:126:y:2021:i:8:d:10.1007_s11192-021-04049-z
    DOI: 10.1007/s11192-021-04049-z
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    1. Bornmann, Lutz & Tekles, Alexander & Zhang, Helena H. & Ye, Fred Y., 2019. "Do we measure novelty when we analyze unusual combinations of cited references? A validation study of bibliometric novelty indicators based on F1000Prime data," Journal of Informetrics, Elsevier, vol. 13(4).
    2. Trapido, Denis, 2015. "How novelty in knowledge earns recognition: The role of consistent identities," Research Policy, Elsevier, vol. 44(8), pages 1488-1500.
    3. 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.
    4. Sarah Kaplan & Keyvan Vakili, 2015. "The double-edged sword of recombination in breakthrough innovation," Strategic Management Journal, Wiley Blackwell, vol. 36(10), pages 1435-1457, October.
    5. Walsh, John P. & Lee, You-Na, 2015. "The bureaucratization of science," Research Policy, Elsevier, vol. 44(8), pages 1584-1600.
    6. Tahamtan, Iman & Bornmann, Lutz, 2018. "Creativity in science and the link to cited references: Is the creative potential of papers reflected in their cited references?," Journal of Informetrics, Elsevier, vol. 12(3), pages 906-930.
    7. Lee Fleming, 2001. "Recombinant Uncertainty in Technological Search," Management Science, INFORMS, vol. 47(1), pages 117-132, January.
    8. Paul M. Romer, 1994. "The Origins of Endogenous Growth," Journal of Economic Perspectives, American Economic Association, vol. 8(1), pages 3-22, Winter.
    9. Verhoeven, Dennis & Bakker, Jurriën & Veugelers, Reinhilde, 2016. "Measuring technological novelty with patent-based indicators," Research Policy, Elsevier, vol. 45(3), pages 707-723.
    10. 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.
    11. Masatsura Igami & Sadao Nagaoka & John Walsh, 2015. "Contribution of postdoctoral fellows to fast-moving and competitive scientific research," The Journal of Technology Transfer, Springer, vol. 40(4), pages 723-741, August.
    12. Tanzila Ahmed & Ben Johnson & Charles Oppenheim & Catherine Peck, 2004. "Highly cited old papers and the reasons why they continue to be cited. Part II., The 1953 Watson and Crick article on the structure of DNA," Scientometrics, Springer;Akadémiai Kiadó, vol. 61(2), pages 147-156, October.
    13. Wang, Jian & Lee, You-Na & Walsh, John P., 2018. "Funding model and creativity in science: Competitive versus block funding and status contingency effects," Research Policy, Elsevier, vol. 47(6), pages 1070-1083.
    14. Dahlin, Kristina B. & Behrens, Dean M., 2005. "When is an invention really radical?: Defining and measuring technological radicalness," Research Policy, Elsevier, vol. 34(5), pages 717-737, June.
    15. Diana Hicks & Paul Wouters & Ludo Waltman & Sarah de Rijcke & Ismael Rafols, 2015. "Bibliometrics: The Leiden Manifesto for research metrics," Nature, Nature, vol. 520(7548), pages 429-431, April.
    16. Kristina Dahlin & Deans M. Behrens, 2005. "When is an invention really radical? Defining and measuring technological radicalness," Post-Print hal-00480416, HAL.
    17. Murayama, Kota & Nirei, Makoto & Shimizu, Hiroshi, 2015. "Management of science, serendipity, and research performance: Evidence from a survey of scientists in Japan and the U.S," Research Policy, Elsevier, vol. 44(4), pages 862-873.
    18. Nagaoka, Sadao & 長岡, 貞男 & Igami, Masatsura & 伊神, 正貫 & Eto, Manabu & 江藤, 学 & Ijichi, Tomohiro & 伊地知, 寛博, 2010. "Knowledge Creation Process in Science : Basic findings from a large‐scale survey of researchers in Japan," IIR Working Paper 10-08, Institute of Innovation Research, Hitotsubashi University.
    19. Bornmann, Lutz & Schier, Hermann & Marx, Werner & Daniel, Hans-Dieter, 2012. "What factors determine citation counts of publications in chemistry besides their quality?," Journal of Informetrics, Elsevier, vol. 6(1), pages 11-18.
    20. Charles Oppenheim & Susan P. Renn, 1978. "Highly cited old papers and the reasons why they continue to be cited," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 29(5), pages 225-231, September.
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