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

    for a different version of it.

    References listed on IDEAS

    as
    1. Raminta Pranckutė, 2021. "Web of Science (WoS) and Scopus: The Titans of Bibliographic Information in Today’s Academic World," Publications, MDPI, vol. 9(1), pages 1-59, March.
    2. Sánchez-Jiménez, Rodrigo & Guerrero-Bote, Vicente P. & Moya-Anegón, Félix, 2017. "The role of guarantor in scientific collaboration: The neighbourhood matters," Journal of Informetrics, Elsevier, vol. 11(1), pages 103-116.
    3. Giovanni Abramo & Ciriaco Andrea D’Angelo, 2014. "How do you define and measure research productivity?," Scientometrics, Springer;Akadémiai Kiadó, vol. 101(2), pages 1129-1144, November.
    4. Pierre Azoulay & Waverly Ding & Toby Stuart, 2007. "The Determinants of Faculty Patenting Behavior: Demographics or Opportunities?," NBER Chapters, in: Academic Science and Entrepreneurship: Dual Engines of Growth, National Bureau of Economic Research, Inc.
    5. Qing Hu & T. Grandon Gill, 2000. "IS Faculty Research Productivity: Influential Factors and Implications," Information Resources Management Journal (IRMJ), IGI Global Scientific Publishing, vol. 13(2), pages 15-25, April.
    6. Robert J. W. Tijssen & Martijn S. Visser & Thed N. van Leeuwen, 2002. "Benchmarking international scientific excellence: Are highly cited research papers an appropriate frame of reference?," Scientometrics, Springer;Akadémiai Kiadó, vol. 54(3), pages 381-397, July.
    7. Aghaei Chadegani, Arezoo & Salehi, Hadi & Md Yunus, Melor & Farhadi, Hadi & Fooladi, Masood & Farhadi, Maryam & Ale Ebrahim, Nader, 2013. "A Comparison between Two Main Academic Literature Collections: Web of Science and Scopus Databases," MPRA Paper 46898, University Library of Munich, Germany, revised 18 Mar 2013.
    8. Angelo Corallo & Maria Elena Latino & Marta Menegoli & Biagia De Devitiis & Rosaria Viscecchia, 2019. "Human Factor in Food Label Design to Support Consumer Healthcare and Safety: A Systematic Literature Review," Sustainability, MDPI, vol. 11(15), pages 1-14, July.
    9. Kristof Witte & Nicky Rogge, 2010. "To publish or not to publish? On the aggregation and drivers of research performance," Scientometrics, Springer;Akadémiai Kiadó, vol. 85(3), pages 657-680, December.
    10. Andrea Bonaccorsi & Cinzia Daraio, 2003. "A robust nonparametric approach to the analysis of scientific productivity," Research Evaluation, Oxford University Press, vol. 12(1), pages 47-69, April.
    11. Azoulay, Pierre & Ding, Waverly & Stuart, Toby, 2007. "The determinants of faculty patenting behavior: Demographics or opportunities?," Journal of Economic Behavior & Organization, Elsevier, vol. 63(4), pages 599-623, August.
    12. Craig Boardman & Barry Bozeman, 2015. "Academic faculty as intellectual property in university-industry research alliances," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 24(5), pages 403-420, July.
    13. Giovanni Abramo & Ciriaco Andrea D’Angelo & Alessandro Caprasecca, 2009. "The contribution of star scientists to overall sex differences in research productivity," Scientometrics, Springer;Akadémiai Kiadó, vol. 81(1), pages 137-156, October.
    14. Péter Vinkler, 2017. "Core indicators and professional recognition of scientometricians," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 68(1), pages 234-242, January.
    15. Tol, Richard S.J., 2013. "Identifying excellent researchers: A new approach," Journal of Informetrics, Elsevier, vol. 7(4), pages 803-810.
    16. Vincent Larivière & Benoit Macaluso & Éric Archambault & Yves Gingras, 2010. "Which scientific elites? On the concentration of research funds, publications and citations," Research Evaluation, Oxford University Press, vol. 19(1), pages 45-53, March.
    17. Dag W Aksnes & Randi Elisabeth Taxt, 2004. "Peer reviews and bibliometric indicators: a comparative study at a Norwegian university," Research Evaluation, Oxford University Press, vol. 13(1), pages 33-41, April.
    18. Ruiz-Castillo, Javier, 2016. "Research output indicators are not productivity indicators," UC3M Working papers. Economics we1601, Universidad Carlos III de Madrid. Departamento de Economía.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Brito, Ricardo & Rodríguez-Navarro, Alonso, 2018. "Research assessment by percentile-based double rank analysis," Journal of Informetrics, Elsevier, vol. 12(1), pages 315-329.
    2. Rodríguez-Navarro, Alonso & Brito, Ricardo, 2018. "Technological research in the EU is less efficient than the world average. EU research policy risks Europeans’ future," Journal of Informetrics, Elsevier, vol. 12(3), pages 718-731.
    3. Giovanni Abramo & Ciriaco Andrea D’Angelo, 2022. "Drivers of academic engagement in public–private research collaboration: an empirical study," The Journal of Technology Transfer, Springer, vol. 47(6), pages 1861-1884, December.
    4. Pablo D’Este & Puay Tang & Surya Mahdi & Andy Neely & Mabel Sánchez-Barrioluengo, 2013. "The pursuit of academic excellence and business engagement: is it irreconcilable?," Scientometrics, Springer;Akadémiai Kiadó, vol. 95(2), pages 481-502, May.
    5. Crespi, Gustavo & D'Este, Pablo & Fontana, Roberto & Geuna, Aldo, 2011. "The impact of academic patenting on university research and its transfer," Research Policy, Elsevier, vol. 40(1), pages 55-68, February.
    6. Mehdi Rhaiem & Nabil Amara, 2020. "Determinants of research efficiency in Canadian business schools: evidence from scholar-level data," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(1), pages 53-99, October.
    7. Ding, Waverly & Choi, Emily, 2008. "Divergent Paths or Stepping Stones: A Comparison of Scientists’ Advising and Founding Activities," Institute for Research on Labor and Employment, Working Paper Series qt4907j25p, Institute of Industrial Relations, UC Berkeley.
    8. Nicolas Carayol & Elodie Carpentier, 2022. "The spread of academic invention: a nationwide case study on French data (1995–2012)," The Journal of Technology Transfer, Springer, vol. 47(5), pages 1395-1421, October.
    9. Llopis, Oscar & D'Este, Pablo & McKelvey, Maureen & Yegros, Alfredo, 2022. "Navigating multiple logics: Legitimacy and the quest for societal impact in science," Technovation, Elsevier, vol. 110(C).
    10. Munari, Federico & Toschi, Laura, 2021. "The impact of public funding on science valorisation: an analysis of the ERC Proof-of-Concept Programme," Research Policy, Elsevier, vol. 50(6).
    11. Gianluca Fabiano & Andrea Marcellusi & Giampiero Favato, 2020. "Public–private contribution to biopharmaceutical discoveries: a bibliometric analysis of biomedical research in UK," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(1), pages 153-168, July.
    12. Giovanni Abramo & Ciriaco Andrea D’Angelo, 2024. "The scientific standing of nations and its relationship with economic competitiveness," PLOS ONE, Public Library of Science, vol. 19(6), pages 1-15, June.
    13. Modic, Dolores & Suklan, Jana, 2023. "Intellectual property coordinators' cohorts: A study into the imprints in university technology transfer," Research Policy, Elsevier, vol. 52(8).
    14. Bodas Freitas, Isabel Maria & Marques, Rosane Argou & Silva, Evando Mirra de Paula e, 2013. "University–industry collaboration and innovation in emergent and mature industries in new industrialized countries," Research Policy, Elsevier, vol. 42(2), pages 443-453.
    15. Cornelia Lawson, 2013. "Academic Inventions Outside the University: Investigating Patent Ownership in the UK," Industry and Innovation, Taylor & Francis Journals, vol. 20(5), pages 385-398, July.
    16. Aldo Geuna & Alessandro Muscio, 2008. "The governance of University knowledge transfer," SPRU Working Paper Series 173, SPRU - Science Policy Research Unit, University of Sussex Business School.
    17. Henry Sauermann & Michael Roach, 2011. "Not All Scientists pay to be Scientists:," DRUID Working Papers 11-03, DRUID, Copenhagen Business School, Department of Industrial Economics and Strategy/Aalborg University, Department of Business Studies.
    18. Jacqueline N. Lane & Ina Ganguli & Patrick Gaule & Eva Guinan & Karim R. Lakhani, 2021. "Engineering serendipity: When does knowledge sharing lead to knowledge production?," Strategic Management Journal, Wiley Blackwell, vol. 42(6), pages 1215-1244, June.
    19. Manuel Acosta & Daniel Coronado & M. Ángeles Martínez, 2018. "Does technological diversification spur university patenting?," The Journal of Technology Transfer, Springer, vol. 43(1), pages 96-119, February.
    20. Crescenzi, Riccardo & Nathan, Max & Rodríguez-Pose, Andrés, 2016. "Do inventors talk to strangers? On proximity and collaborative knowledge creation," Research Policy, Elsevier, vol. 45(1), pages 177-194.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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.