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Lotka and information science

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  • Henry Voos

Abstract

Productivity in terms of scientific publication was described by Lotka in 1926. He discovered that in the hard sciences he could predict the number of papers an author would write providing he knew how many authors wrote only one paper during a given time period. The factor for predicting the number of papers in a field like chemistry was found to be 1/n2 of the number of authors writing only one paper. That is, if 100 authors wrote one paper, only 25 would write two papers, and only 11 would write three papers, etc. If the Lotka constant holds for the hard sciences it was hypothesized (and tested) that other disciplines would have other constants, and thereby form a continuum based on productivity from the hard sciences to the non‐sciences. The literature of information science has been examined between 1966 and 1970. It was determined that a new constant, 1/n3.5 fitted information science best.

Suggested Citation

  • Henry Voos, 1974. "Lotka and information science," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 25(4), pages 270-272, July.
  • Handle: RePEc:bla:jamest:v:25:y:1974:i:4:p:270-272
    DOI: 10.1002/asi.4630250410
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    Cited by:

    1. Kee H. Chung & Phillip T. Kolbe, 1992. "Empirical Regularities in the Market for Real Estate Research Output," Journal of Real Estate Research, American Real Estate Society, vol. 7(1), pages 115-124.
    2. Suresh Kumar & B.M. Gupta & C. R. Karisiddappa, 2002. "Scientific productivity of authors in theoretical population genetics," Scientometrics, Springer;Akadémiai Kiadó, vol. 53(1), pages 73-93, January.
    3. Debabrata Talukdar, 2011. "Patterns of Research Productivity in the Business Ethics Literature: Insights from Analyses of Bibliometric Distributions," Journal of Business Ethics, Springer, vol. 98(1), pages 137-151, January.
    4. Cátia Raquel Felden Bartz & Daniel Knebel Baggio & Lucas Veiga Ávila & Jéssica Casali Turcato, 2021. "Collaborative Governance: An International Bilbiometric Study of the Last Decade," Public Organization Review, Springer, vol. 21(3), pages 543-559, September.
    5. Timur Narbaev & Diana Amirbekova, 2021. "Research Productivity in Emerging Economies: Empirical Evidence from Kazakhstan," Publications, MDPI, vol. 9(4), pages 1-19, November.
    6. Krishna Muniyoor, 2022. "The Structure of Scholarly Publishing: a Case of Economics Research in India," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 13(3), pages 1801-1818, September.
    7. Wei Wang & Xiaomei Bai & Feng Xia & Teshome Megersa Bekele & Xiaoyan Su & Amr Tolba, 2017. "From triadic closure to conference closure: the role of academic conferences in promoting scientific collaborations," Scientometrics, Springer;Akadémiai Kiadó, vol. 113(1), pages 177-193, October.
    8. Miloš Savić & Mirjana Ivanović & Miloš Radovanović & Zoran Ognjanović & Aleksandar Pejović & Tatjana Jakšić Krüger, 2014. "The structure and evolution of scientific collaboration in Serbian mathematical journals," Scientometrics, Springer;Akadémiai Kiadó, vol. 101(3), pages 1805-1830, December.
    9. Rebecca Long & Aleta Crawford & Michael White & Kimberly Davis, 2009. "Determinants of faculty research productivity in information systems: An empirical analysis of the impact of academic origin and academic affiliation," Scientometrics, Springer;Akadémiai Kiadó, vol. 78(2), pages 231-260, February.
    10. J. C. Huber, 1999. "Inventive productivity and the statistics of exceedances," Scientometrics, Springer;Akadémiai Kiadó, vol. 45(1), pages 33-53, May.

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