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Towards field-adjusted production: Estimating research productivity from a zero-truncated distribution

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  • Koski, Timo
  • Sandström, Erik
  • Sandström, Ulf

Abstract

Measures of research productivity (e.g. peer reviewed papers per researcher) is a fundamental part of bibliometric studies, but is often restricted by the properties of the data available. This paper addresses that fundamental issue and presents a detailed method for estimation of productivity (peer reviewed papers per researcher) based on data available in bibliographic databases (e.g. Web of Science and Scopus). The method can, for example, be used to estimate average productivity in different fields, and such field reference values can be used to produce field adjusted production values. Being able to produce such field adjusted production values could dramatically increase the relevance of bibliometric rankings and other bibliometric performance indicators. The results indicate that the estimations are reasonably stable given a sufficiently large data set.

Suggested Citation

  • Koski, Timo & Sandström, Erik & Sandström, Ulf, 2016. "Towards field-adjusted production: Estimating research productivity from a zero-truncated distribution," Journal of Informetrics, Elsevier, vol. 10(4), pages 1143-1152.
    • Handle: RePEc:eee:infome:v:10:y:2016:i:4:p:1143-1152
    DOI: 10.1016/j.joi.2016.09.002
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    References listed on IDEAS

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    Cited by:

    1. Hamdi A. Al-Jamimi & Galal M. BinMakhashen & Lutz Bornmann, 2022. "Use of bibliometrics for research evaluation in emerging markets economies: a review and discussion of bibliometric indicators," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(10), pages 5879-5930, October.
    2. Gauffriau, Marianne, 2017. "A categorization of arguments for counting methods for publication and citation indicators," Journal of Informetrics, Elsevier, vol. 11(3), pages 672-684.
    3. Bornmann, Lutz & Williams, Richard, 2017. "Can the journal impact factor be used as a criterion for the selection of junior researchers? A large-scale empirical study based on ResearcherID data," Journal of Informetrics, Elsevier, vol. 11(3), pages 788-799.
    4. Koh Yamamoto & Takuo Yasunaga, 2022. "A percentile rank score of group productivity: an evaluation of publication productivity for researchers from various fields," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(4), pages 1737-1754, April.

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