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The value and credits of n-authors publications

Author

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  • Bornmann, Lutz
  • Osório, António

Abstract

Collaboration among researchers is becoming increasingly common, which raises a large number of scientometrics questions for which there is not a clear and generally accepted answer. For instance, what value should be given to a two-author or three-author publication with respect to a single-author publication? This paper uses axiomatic analysis and proposes a practical method to compute the expected value of an n-authors publication that takes into consideration the added value induced by collaboration in contexts in which there is no prior or ex-ante information about the publication's potential merits or scientific impact. The only information required is the number of authors. We compared the obtained theoretical values with the empirical values based on a large dataset from the Web of Science database. We found that the theoretical values are very close to the empirical values for some disciplines, but not for all. This observation provides support in favor of the method proposed in this paper. We expect that our findings can help researchers and decision-makers to choose more effective and fair counting methods that take into account the benefits of collaboration.

Suggested Citation

  • Bornmann, Lutz & Osório, António, 2019. "The value and credits of n-authors publications," Journal of Informetrics, Elsevier, vol. 13(2), pages 540-554.
  • Handle: RePEc:eee:infome:v:13:y:2019:i:2:p:540-554
    DOI: 10.1016/j.joi.2019.03.001
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    File URL: http://www.sciencedirect.com/science/article/pii/S1751157718301056
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    Citations

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    Cited by:

    1. António Osório & Lutz Bornmann, 2021. "On the disruptive power of small-teams research," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(1), pages 117-133, January.
    2. Osório, António (António Miguel) & Bornmann, Lutz, 2020. "On the disruptive power of small-teams research," Working Papers 2072/417677, Universitat Rovira i Virgili, Department of Economics.
    3. Simoes, Nadia & Crespo, Nuno, 2020. "Self-Citations and scientific evaluation: Leadership, influence, and performance," Journal of Informetrics, Elsevier, vol. 14(1).
    4. Lawrence Smolinsky & Daniel S. Sage & Aaron J. Lercher & Aaron Cao, 2021. "Citations versus expert opinions: citation analysis of featured reviews of the American Mathematical Society," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(5), pages 3853-3870, May.
    5. Siying Li & Huawei Shen & Peng Bao & Xueqi Cheng, 2021. "$$h_u$$ h u -index: a unified index to quantify individuals across disciplines," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(4), pages 3209-3226, April.
    6. João M. Fernandes & Paulo Cortez, 2020. "Alphabetic order of authors in scholarly publications: a bibliometric study for 27 scientific fields," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(3), pages 2773-2792, December.

    More about this item

    Keywords

    Co-authorship; Counting methods; Publication value; Axiomatic analysis; Bibliometrics;
    All these keywords.

    JEL classification:

    • C65 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Miscellaneous Mathematical Tools
    • D04 - Microeconomics - - General - - - Microeconomic Policy: Formulation; Implementation; Evaluation

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