IDEAS home Printed from https://ideas.repec.org/a/spr/jknowl/v15y2024i3d10.1007_s13132-023-01613-1.html
   My bibliography  Save this article

Evaluation of a Scientific Productivity Model among World Highly Cited Authors: a Study Based on Experts’ Opinions

Author

Listed:
  • Farideh Osare

    (Shahid Chamran University)

  • Mariam Keshvari

    (Shahid Chamran University
    Knowledge and Information Science (KIS), University of Isfahan)

Abstract

This article mainly aims to investigate the relevance of a scientific productivity model (based on experts’ opinions) to highly cited authors. To this end, this study intends to first identify the scientific productivity model based on experts’ opinions and then examine it among the highly cited authors’ community. The present study was conducted by a mixed quantitative and qualitative method on two statistical communities, 12 experts (who were mainly active in scientific productivity), and 235 highly cited authors in the world participated in this research. Research data were collected using such tools as a checklist, questionnaires, and the Clarivate Analytics-WoS database and analyzed with SPSS-19 and LISREL 8 software. The scientific productivity model of highly cited authors was examined by the confirmatory factor analysis (CFA). This three-factor model (including individual, organizational, and bibliometric factors), which according to CFA load factors, shows that (1) the bibliographic factor (loading factor 1), (2) the individual factor (loading factor 0.69), and (3) the organizational factor (loading factor 0.63) are effective among highly cited authors (based on the scientific productivity model). Besides, the scientific productivity model fits among the community of highly cited authors through the world based on experts’ opinions. The combination of quantitative and qualitative factors presented in this model can effectively provide the basis for individual and organizational scientific development and pave the way for individuals and organizations to promote scientific productivity. In addition, the result of this research can be effective for improving and developing scientometric indicators.

Suggested Citation

  • Farideh Osare & Mariam Keshvari, 2024. "Evaluation of a Scientific Productivity Model among World Highly Cited Authors: a Study Based on Experts’ Opinions," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 15(3), pages 14452-14485, September.
    • Handle: RePEc:spr:jknowl:v:15:y:2024:i:3:d:10.1007_s13132-023-01613-1
    DOI: 10.1007/s13132-023-01613-1
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s13132-023-01613-1
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s13132-023-01613-1?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:jknowl:v:15:y:2024:i:3:d:10.1007_s13132-023-01613-1. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.