IDEAS home Printed from https://ideas.repec.org/a/gam/jpubli/v12y2024i4p50-d1547459.html
   My bibliography  Save this article

Research Metrics in Architecture: An Analysis of the Current Challenges Compared to Engineering Disciplines

Author

Listed:
  • Omar S. Asfour

    (Architecture and City Design Department, King Fahd University of Petroleum & Minerals, Dhahran 31261, Saudi Arabia
    Interdisciplinary Research Center for Construction and Building Materials, King Fahd University of Petroleum & Minerals, Dhahran 31261, Saudi Arabia)

  • Jamal Al-Qawasmi

    (Architecture and City Design Department, King Fahd University of Petroleum & Minerals, Dhahran 31261, Saudi Arabia
    Interdisciplinary Research Center for Construction and Building Materials, King Fahd University of Petroleum & Minerals, Dhahran 31261, Saudi Arabia)

Abstract

The Hirsch index (‘ h -index’) is a widely recognized metric for assessing researchers’ impact, considering both the quantity and quality of their research work. Despite its global acceptance, the h -index has created some uncertainty about appropriate benchmark values across different disciplines. One such area of concern is architecture, which is often at a disadvantage compared to the fields of science and engineering. To examine this disparity, this study compared the citation count and h -index in architecture with those of other engineering disciplines. Data were collected extensively from Scopus database, focusing on the top 50 universities. The analysis revealed that architecture consistently recorded lower citation counts and h -index values than the selected engineering fields. Specifically, the average h-index for faculty members at the associate and full professor ranks was found to be 7.0 in architecture, compared to 22.8 in civil engineering and 25.6 in mechanical engineering. The findings highlight that a universal h -index benchmark is impractical, as research areas significantly vary in terms of research opportunities, challenges, and performance expectations. Thus, this study proposes the adoption of an additional relative h -index metric, ‘ h r -index’, which accounts for the deviation of individual researchers from the average h -index value within their fields of knowledge. This metric can serve as a complement to the standard h -index, providing a more equitable and accurate assessment of researchers’ performance and impact within their areas of expertise.

Suggested Citation

  • Omar S. Asfour & Jamal Al-Qawasmi, 2024. "Research Metrics in Architecture: An Analysis of the Current Challenges Compared to Engineering Disciplines," Publications, MDPI, vol. 12(4), pages 1-17, December.
  • Handle: RePEc:gam:jpubli:v:12:y:2024:i:4:p:50-:d:1547459
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2304-6775/12/4/50/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2304-6775/12/4/50/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Tehmina Amjad & Yusra Rehmat & Ali Daud & Rabeeh Ayaz Abbasi, 2020. "Scientific impact of an author and role of self-citations," Scientometrics, Springer;Akadémiai Kiadó, vol. 122(2), pages 915-932, February.
    2. Anne-Wil Harzing & Satu Alakangas & David Adams, 2014. "hIa: an individual annual h-index to accommodate disciplinary and career length differences," Scientometrics, Springer;Akadémiai Kiadó, vol. 99(3), pages 811-821, June.
    3. Madiha Ameer & Muhammad Tanvir Afzal, 2019. "Evaluation of h-index and its qualitative and quantitative variants in Neuroscience," Scientometrics, Springer;Akadémiai Kiadó, vol. 121(2), pages 653-673, November.
    4. Fabio Zagonari, 2019. "Scientific Production and Productivity for Characterizing an Author’s Publication History: Simple and Nested Gini’s and Hirsch’s Indexes Combined," Publications, MDPI, vol. 7(2), pages 1-30, May.
    5. Fabio Zagonari & Paolo Foschi, 2024. "Coping with the Inequity and Inefficiency of the H-Index: A Cross-Disciplinary Empirical Analysis," Publications, MDPI, vol. 12(2), pages 1-30, April.
    6. Justin W. Flatt & Alessandro Blasimme & Effy Vayena, 2017. "Improving the Measurement of Scientific Success by Reporting a Self-Citation Index," Publications, MDPI, vol. 5(3), pages 1-6, August.
    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. Fabio Zagonari, 2019. "Scientific Production and Productivity for Characterizing an Author’s Publication History: Simple and Nested Gini’s and Hirsch’s Indexes Combined," Publications, MDPI, vol. 7(2), pages 1-30, May.
    2. Abdulrahman A. Alshdadi & Muhammad Usman & Madini O. Alassafi & Muhammad Tanvir Afzal & Rayed AlGhamdi, 2023. "Formulation of rules for the scientific community using deep learning," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(3), pages 1825-1852, March.
    3. Deming Lin & Tianhui Gong & Wenbin Liu & Martin Meyer, 2020. "An entropy-based measure for the evolution of h index research," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(3), pages 2283-2298, December.
    4. James C. Ryan, 2016. "A validation of the individual annual h-index (hIa): application of the hIa to a qualitatively and quantitatively different sample," Scientometrics, Springer;Akadémiai Kiadó, vol. 109(1), pages 577-590, October.
    5. Anne-Wil Harzing & Wilfred Mijnhardt, 2015. "Proof over promise: towards a more inclusive ranking of Dutch academics in Economics & Business," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(1), pages 727-749, January.
    6. Abramo, Giovanni & D'Angelo, Ciriaco Andrea & Grilli, Leonardo, 2021. "The effects of citation-based research evaluation schemes on self-citation behavior," Journal of Informetrics, Elsevier, vol. 15(4).
    7. T. Liskiewicz & G. Liskiewicz & J. Paczesny, 2021. "Factors affecting the citations of papers in tribology journals," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(4), pages 3321-3336, April.
    8. Yuetong Chen & Hao Wang & Baolong Zhang & Wei Zhang, 2022. "A method of measuring the article discriminative capacity and its distribution," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(6), pages 3317-3341, June.
    9. Gordana Budimir & Sophia Rahimeh & Sameh Tamimi & Primož Južnič, 2021. "Comparison of self-citation patterns in WoS and Scopus databases based on national scientific production in Slovenia (1996–2020)," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(3), pages 2249-2267, March.
    10. Muhammad Usman & Ghulam Mustafa & Muhammad Tanvir Afzal, 2021. "Ranking of author assessment parameters using Logistic Regression," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(1), pages 335-353, January.
    11. Margaret K. Merga & Sayidi Mat Roni & Shannon Mason, 2020. "Should Google Scholar be used for benchmarking against the professoriate in education?," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(3), pages 2505-2522, December.
    12. Tolga Yuret, 2018. "Author-weighted impact factor and reference return ratio: can we attain more equality among fields?," Scientometrics, Springer;Akadémiai Kiadó, vol. 116(3), pages 2097-2111, September.
    13. Sven E. Hug & Michael Ochsner & Martin P. Brändle, 2017. "Citation analysis with microsoft academic," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(1), pages 371-378, April.
    14. Yannick Berker, 2018. "Golden-ratio as a substitute to geometric and harmonic counting to determine multi-author publication credit," Scientometrics, Springer;Akadémiai Kiadó, vol. 114(3), pages 839-857, March.
    15. Esther Salmerón-Manzano & Francisco Manzano-Agugliaro, 2017. "Worldwide Scientific Production Indexed by Scopus on Labour Relations," Publications, MDPI, vol. 5(4), pages 1-14, October.
    16. Tanmoy Konar, 2021. "Author-Suggested, Weighted Citation Index: A Novel Approach for Determining the Contribution of Individual Researchers," Publications, MDPI, vol. 9(3), pages 1-8, July.
    17. Tehmina Amjad & Nafeesa Shahid & Ali Daud & Asma Khatoon, 2022. "Citation burst prediction in a bibliometric network," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(5), pages 2773-2790, May.
    18. Anne-Wil Harzing & Satu Alakangas, 2016. "Google Scholar, Scopus and the Web of Science: a longitudinal and cross-disciplinary comparison," Scientometrics, Springer;Akadémiai Kiadó, vol. 106(2), pages 787-804, February.
    19. Constantin Schoen & Katja Rost & David Seidl, 2018. "The influence of gender ratios on academic careers: Combining social networks with tokenism," PLOS ONE, Public Library of Science, vol. 13(11), pages 1-21, November.
    20. Tehmina Amjad & Javeria Munir, 2021. "Investigating the impact of collaboration with authority authors: a case study of bibliographic data in field of philosophy," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(5), pages 4333-4353, May.

    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:gam:jpubli:v:12:y:2024:i:4:p:50-:d:1547459. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.