IDEAS home Printed from https://ideas.repec.org/a/spr/jclass/v35y2018i1d10.1007_s00357-018-9247-0.html
   My bibliography  Save this article

Qualitative Judgement of Research Impact: Domain Taxonomy as a Fundamental Framework for Judgement of the Quality of Research

Author

Listed:
  • Fionn Murtagh

    (University of Derby
    Goldsmiths, University of London)

  • Michael Orlov

    (National Research University Higher School of Economics)

  • Boris Mirkin

    (National Research University Higher School of Economics
    Birkbeck, University of London)

Abstract

The appeal of metric evaluation of research impact has attracted considerable interest in recent times. Although the public at large and administrative bodies are much interested in the idea, scientists and other researchers are much more cautious, insisting that metrics are but an auxiliary instrument to the qualitative peer-based judgement. The goal of this article is to propose availing of such a well positioned construct as domain taxonomy as a tool for directly assessing the scope and quality of research. We first show how taxonomies can be used to analyze the scope and perspectives of a set of research projects or papers. Then we proceed to define a research team or researcher’s rank by those nodes in the hierarchy that have been created or significantly transformed by the results of the researcher. An experimental test of the approach in the data analysis domain is described. Although the concept of taxonomy seems rather simplistic to describe all the richness of a research domain, its changes and use can be made transparent and subject to open discussions.

Suggested Citation

  • Fionn Murtagh & Michael Orlov & Boris Mirkin, 2018. "Qualitative Judgement of Research Impact: Domain Taxonomy as a Fundamental Framework for Judgement of the Quality of Research," Journal of Classification, Springer;The Classification Society, vol. 35(1), pages 5-28, April.
  • Handle: RePEc:spr:jclass:v:35:y:2018:i:1:d:10.1007_s00357-018-9247-0
    DOI: 10.1007/s00357-018-9247-0
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s00357-018-9247-0
    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/s00357-018-9247-0?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.

    References listed on IDEAS

    as
    1. Ng, Wan Lung, 2007. "A simple classifier for multiple criteria ABC analysis," European Journal of Operational Research, Elsevier, vol. 177(1), pages 344-353, February.
    2. Giovanni Abramo & Tindaro Cicero & Ciriaco Andrea D’Angelo, 2013. "National peer-review research assessment exercises for the hard sciences can be a complete waste of money: the Italian case," Scientometrics, Springer;Akadémiai Kiadó, vol. 95(1), pages 311-324, April.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Cappelletti-Montano, Beniamino & Columbu, Silvia & Montaldo, Stefano & Musio, Monica, 2022. "Interpreting the outcomes of research assessments: A geometrical approach," Journal of Informetrics, Elsevier, vol. 16(1).
    2. A. Ferrer-Sapena & J. M. Calabuig & L. M. García Raffi & E. A. Sánchez Pérez, 2020. "Where Should I Submit My Work for Publication? An Asymmetrical Classification Model to Optimize Choice," Journal of Classification, Springer;The Classification Society, vol. 37(2), pages 490-508, July.

    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. Cheng Peng & Xunbo Wu & Yelin Fu & Kin Keung Lai, 2017. "Alternative approaches to constructing composite indicators: an application to construct a Sustainable Energy Index for APEC economies," Operational Research, Springer, vol. 17(3), pages 747-759, October.
    2. Hu, Qiwei & Chakhar, Salem & Siraj, Sajid & Labib, Ashraf, 2017. "Spare parts classification in industrial manufacturing using the dominance-based rough set approach," European Journal of Operational Research, Elsevier, vol. 262(3), pages 1136-1163.
    3. Giannis Karagiannis & Suzanna M. Paleologou, 2021. "A regression-based improvement to the multiple criteria ABC inventory classification analysis," Annals of Operations Research, Springer, vol. 306(1), pages 369-382, November.
    4. Thelwall, Mike & Fairclough, Ruth, 2015. "The influence of time and discipline on the magnitude of correlations between citation counts and quality scores," Journal of Informetrics, Elsevier, vol. 9(3), pages 529-541.
    5. Sheikh-Zadeh, Alireza & Rossetti, Manuel D. & Scott, Marc A., 2021. "Performance-based inventory classification methods for large-Scale multi-echelon replenishment systems," Omega, Elsevier, vol. 101(C).
    6. Zaida Chinchilla-Rodríguez & Grisel Zacca-González & Benjamín Vargas-Quesada & Félix Moya-Anegón, 2016. "Benchmarking scientific performance by decomposing leadership of Cuban and Latin American institutions in Public Health," Scientometrics, Springer;Akadémiai Kiadó, vol. 106(3), pages 1239-1264, March.
    7. Elio Atenógenes Villaseñor & Ricardo Arencibia-Jorge & Humberto Carrillo-Calvet, 2017. "Multiparametric characterization of scientometric performance profiles assisted by neural networks: a study of Mexican higher education institutions," Scientometrics, Springer;Akadémiai Kiadó, vol. 110(1), pages 77-104, January.
    8. Thelwall, Mike & Wilson, Paul, 2014. "Regression for citation data: An evaluation of different methods," Journal of Informetrics, Elsevier, vol. 8(4), pages 963-971.
    9. Sisi Wu & Yelin Fu & K. K. Lai & W. K. John Leung, 2018. "A Weighted Least-Square Dissimilarity Approach for Multiple Criteria ABC Inventory Classification," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 35(04), pages 1-12, August.
    10. S. Saffarzadeh & A. Hadi-Vencheh & A. Jamshidi, 2019. "An Interval Based Score Method for Multiple Criteria Decision Making Problems," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 18(05), pages 1667-1687, September.
    11. Guo Chen & Lu Xiao & Chang-ping Hu & Xue-qin Zhao, 2015. "Identifying the research focus of Library and Information Science institutions in China with institution-specific keywords," Scientometrics, Springer;Akadémiai Kiadó, vol. 103(2), pages 707-724, May.
    12. Park, Jaehun & Lee, Byung Kwon, 2021. "An opinion-driven decision-support framework for benchmarking hotel service," Omega, Elsevier, vol. 103(C).
    13. Hu, Qiwei & Boylan, John E. & Chen, Huijing & Labib, Ashraf, 2018. "OR in spare parts management: A review," European Journal of Operational Research, Elsevier, vol. 266(2), pages 395-414.
    14. Giannis Karagiannis & Georgia Paschalidou, 2017. "Assessing research effectiveness: a comparison of alternative nonparametric models," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(4), pages 456-468, April.
    15. Sheikh-Zadeh, Alireza & Rossetti, Manuel D., 2020. "Classification methods for problem size reduction in spare part provisioning," International Journal of Production Economics, Elsevier, vol. 219(C), pages 99-114.
    16. Fatih Yiğit & Şakir Esnaf, 2021. "A new Fuzzy C-Means and AHP-based three-phased approach for multiple criteria ABC inventory classification," Journal of Intelligent Manufacturing, Springer, vol. 32(6), pages 1517-1528, August.
    17. Siamak Kheybari & S. Ali Naji & Fariba Mahdi Rezaie & Reza Salehpour, 2019. "ABC classification according to Pareto’s principle: a hybrid methodology," OPSEARCH, Springer;Operational Research Society of India, vol. 56(2), pages 539-562, June.
    18. Fan Liu & Ning Ma, 2019. "Multicriteria ABC Inventory Classification Using the Social Choice Theory," Sustainability, MDPI, vol. 12(1), pages 1-19, December.
    19. Giovanni Abramo & Ciriaco Andrea D’Angelo, 2016. "Refrain from adopting the combination of citation and journal metrics to grade publications, as used in the Italian national research assessment exercise (VQR 2011–2014)," Scientometrics, Springer;Akadémiai Kiadó, vol. 109(3), pages 2053-2065, December.
    20. Subhadip Sarkar, 2023. "ABC classification using extended R-model, SVM and Lorenz curve," OPSEARCH, Springer;Operational Research Society of India, vol. 60(3), pages 1433-1455, September.

    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:jclass:v:35:y:2018:i:1:d:10.1007_s00357-018-9247-0. 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.