MAKING SENSE OF NIRF 2022 DATA USING SCIENTOMETRIC AND ECONOMETRIC APPROACHES

Authors

DOI:

https://doi.org/10.34256/

Keywords:

Bibliometric, Scientometric, eXergy

Abstract

Quality content needs to be ranked highly, just as knowledge of any person or civilization indicates the order in which it has progressed, intuitively. The Indian Institution Ranking Framework (NIRF) was the first and most prominent ranking system for Indian educational institutions. Based on publications, research expenditure, and faculty strength, researchers created construct validity maps for the top 30 engineering institutes in India using NIRF 2022 data. IIT Madras is India's best engineering Institute and is excessively simplistic.

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Author Biographies

  • Dr Pawan K Saini, School of Social Science, Indira Gandhi National Open University (IGNOU) Maidan Garhi, New Delhi-110068

    Assistant professor, Faculty of Library and Information Science

  • Dillip Kumar Parida, Indian Institute of Technology, Bhubaneswar, Odisha

    Library Information Superintendent  

  • Ayush Kumar Patel, Physical Research Laboratory, Department of Space, Navrangpura, Ahmedabad- 380009, Gujarat, India

    Library Assistant- A

  • Satyajit Nayak, CSIR-Central Road Research Institute, New Delhi

    Technical Assistant, Knowledge Resource Centre

References

Prathap, G. (2017). Making scientometric and econometric sense out of NIRF 2017 data. Current Science, 1420-1423. doi: 10.18520/cs/v113/i07/1420-1423

Prathap, G. (2013). Benchmarking research performance of the IITs using" Web of Science" and" Scopus" bibliometric databases. Current Science, 1134-1138.

Prathap, G. (2017). Making scientometric sense out of NIRF scores. Current Science, 1240-1242. doi: 10.18520/cs/v112/i06/1240-1242

Abramo, G., & D’Angelo, C. A. (2014). How do you define and measure research productivity?. Scientometrics, 101(2), 1129-1144. https://doi.org/10.1007/s11192-014-1269-8

Prathap, G. (2017). Danger of a single score: NIRF rankings of colleges. Current Science, 550-553.

Abramo, G., & D’Angelo, C. A. (2016). A farewell to the MNCS and like size-independent indicators. Journal of Informetrics, 10(2), 646-651. https://doi.org/10.1016/j.joi.2016.04.006

NIRF Ranking (n.d.) Retrieved on 25th July 2022 from https://www.nirfindia.org/2022/EngineeringRanking.html

Scopus Database (n.d.) Retrieved on 25th July 2022 from https://www.scopus.com/search/form.uri?display=basic#basic

Web of Science Database Retrieved on 25th July 2022 from https://www.webofscience.com/wos/woscc/basic-search

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Published

2026-01-01

Issue

Vol. 61 No. 04 (2025)

Section

Articles

License

Copyright (c) 2026 Journal of Indian Library Association

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

How to Cite

MAKING SENSE OF NIRF 2022 DATA USING SCIENTOMETRIC AND ECONOMETRIC APPROACHES (D. P. K. . Saini, D. K. Parida, A. K. . Patel, & S. Nayak , Trans.). (2026). Journal of Indian Library Association, 61(04), 525-533. https://doi.org/10.34256/