EconPapers    
Economics at your fingertips  
 

Measuring scholarly performance using comprehensive standardized research-teaching (RT) score

Nicola Scafetta ()
Additional contact information
Nicola Scafetta: University of Naples Federico II

Scientometrics, 2025, vol. 130, issue 5, No 5, 2595-2616

Abstract: Abstract University faculty members and participants in scientific competitions are typically evaluated based on metrics derived from their published works and other relevant academic activities. However, designing a robust mathematical algorithm to process bibliometric information is challenging, and accessible computer codes are often scarce. Consequently, evaluation committees may resort to improvised, mathematically inadequate, poorly standardized, and overly simplistic evaluation methods, which can yield unfair and not-transparent outcomes. This paper introduces a novel algorithm, the “RT-score”, designed to assess and rank the research and teaching performance of a group of academics. The RT-score builds upon the “C-score”, which is currently used to generate the “Stanford/Elsevier World Top 2% Most Influential Scientists” list. The RT-score incorporates several complementary bibliometric indicators, including productivity (number of publications), impact (citations), and the involvement of the individual researcher in the published works. The RT-score also emphasizes the most recent and impactful publications while incorporating parameters that account for variations in the number of articles and citation density across different scientific disciplines, funding, and other pertinent aspects. Finally, it combines these metrics with a measure of teaching experience and other academic activities. The RT-score aims to address key recommendations from DORA, CoARA, and the Leiden Manifesto concerning research assessment reform. The supplement provides a MATLAB code that implements the proposed algorithm.

Keywords: Scholarly performance; Citation metrics; Teaching metrics; Faculty rank (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s11192-025-05317-y Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:scient:v:130:y:2025:i:5:d:10.1007_s11192-025-05317-y

Ordering information: This journal article can be ordered from
http://www.springer.com/economics/journal/11192

DOI: 10.1007/s11192-025-05317-y

Access Statistics for this article

Scientometrics is currently edited by Wolfgang Glänzel

More articles in Scientometrics from Springer, Akadémiai Kiadó
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().

 
Page updated 2025-06-03
Handle: RePEc:spr:scient:v:130:y:2025:i:5:d:10.1007_s11192-025-05317-y