Aithal, P. S. & Aithal, S. (2023). Key performance indicators (kpi) for researchers at different levels & strategies to achieve it. International Journal of Management, Technology and Social Sciences (IJMTS), 8(3), 294–325.
Alexi, A., Lazebnik, T., & Rosenfeld, A. (2024). The scientometrics and reciprocality underlying co-authorship panels in google scholar profiles. Scientometrics, 129(6), 3303–3313.
Andersen, J. P., Didegah, F., and Schneider, J. W. (2017). The necessity of comparing like with like in evaluative scientometrics: A first attempt to produce and test a generic approach to identifying relevant benchmark units. In STI Conference Paris: Open indicators: innovation, participation and actor-based STI indicators.
Ansari, M., Noruzi, A., Fallah, M., Saedmoucheshi, S., & Valinejadi, A. (2022). Bibliometric Analysis of the Top Ten Percent Iranian Medical Researchers Based on the I10-index and the H-index in Web of Science. Informology, 1(2), 27-40.
Aviv-Reuven, S. & Rosenfeld, A. (2023). A logical set theory approach to journal subject classification analysis: intra-system irregularities and inter-system discrepancies in web of science and scopus. Scientometrics, 128(1), 157–175.
Biryukov, M., & Dong, C. (2010). Analysis of computer science communities based on DBLP. In Research and Advanced Technology for Digital Libraries: 14th European Conference, ECDL 2010, Glasgow, UK, September 6-10, 2010. Proceedings 14 (pp. 228-235). Springer Berlin Heidelberg.
Borchardt, R. & Hartings, M. R. (2018). The academic papers researchers regard as significant are not those that are highly cited. Impact of Social Sciences Blog.
Froghi, S., Ahmed, K., Finch, A., Fitzpatrick, J. M., Khan, M. S., & Dasgupta, P. (2012). Indicators for research performance evaluation: An overview. BJU International-British Journal of Urology, 109(3), 321.
Gusenbauer, M. (2019). Google scholar to overshadow them all? comparing the sizes of 12 academic search engines and bibliographic databases. Scientometrics, 118(1), 177–214.
Hu, Y., Hu, C., Tran, T., Kasturi, T., Joseph, E., & Gillingham, M. (2021). What’s in a name?–gender classification of names with character based machine learning models. Data Mining and Knowledge Discovery, 35(4), 1537-1563.
Ke, Q., Ferrara, E., Radicchi, F., and Flammini, A. (2015). Defining and identifying sleeping beauties in science. Proceedings of the National Academy of Sciences, 112(24), 7426–7431.
Kpolovie, P. J., Onoshagbegbe, E. S.(2017). Research productivity: h-index and i10-index of academics in nigerian universities. International Journal of Quantitative and Qualitative Research Methods, 5(2), 62–123.
Kulczycki, E., Korzen’, M., & Korytkowski, P. (2017). Toward an excellence-based research funding system: Evidence from poland. Journal of Informetrics, 11(1), 282–298.
Kumar, D., Bhowmick, P. K., & Paik, J. (2023). Researcher influence prediction (resip) using academic genealogy network. Journal of Informetrics, 17(2), 101392.
Kusakunniran, W., Ponn, T., Boonsom, N., Wahakit, S., & Thongkanchorn, K. (2021). Construction of h5-index for conference ranking indicator and its correlation to era. Journal of Information & Knowledge Management, 20(01):2150011.
Leibel, C. & Bornmann, L. (2024). What do we know about the disruption index in scientometrics? an overview of the literature. Scientometrics, 129(1), 601–639.
Lippi, G. & Mattiuzzi, C. (2017). Scientist impact factor (sif): a new metric for improving scientists’ evaluation? Annals of Translational Medicine, 5(15).
Liu, Y., Jiang, M., Hu, L., & He, Z. (2023). The statistical nature of h-index of a network node and its extensions. Journal of Informetrics, 17(3):101424.
MacFarland, T. W., Yates, J. M., MacFarland, T. W., & Yates, J. M. (2016). Mann–whitney u test. Introduction to nonparametric statistics for the biological sciences using R, 103-132.
Massucci, F. A. & Docampo, D. (2019). Measuring the academic reputation through citation networks via pagerank. Journal of Informetrics, 13(1), 185–201.
Mavrogenis, A. F., Pećina, M., Chen, W., & Scarlat, M. M. (2020). Useful and useless publications measured by bibliometrics and scientometrics in orthopaedic surgery. Are the relevance of a journal and publication metrics useful enough for the scientific promotion of surgeons?. International Orthopaedics, 44, 1875–1879.
Meneghini, R. & Packer, A. L. (2010). The extent of multidisciplinary authorship of articles on scientometrics and bibliometrics in brazil. Interciencia, 35(7), 510–514.
Minasny, B., Hartemink, A. E., McBratney, A., & Jang, H.-J. (2013). Citations and the h index of soil researchers and journals in the web of science, scopus, and google scholar. PeerJ, 1:e183.
Mryglod, O., Kenna, R., Holovatch, Y., & Berche, B. (2013b). Comparison of a citation-based indicator and peer review for absolute and specific measures of research-group excellence. Scientometrics, 97, 767–777.
Ostertagova, E., Ostertag, O., & Kováč, J. (2014). Methodology and application of the Kruskal-Wallis test. Applied mechanics and materials, 611, 115-120.
Robinson, D. B. T., Hopkins, L., Brown, C., Abdelrahman, T., Powell, A. G., Egan, R. J., & Lewis, W. G. (2019a). Relative value of adapted novel bibliometrics in evaluating surgical academic impact and reach. World Journal of Surgery, 43, 967–972.
Robinson, D. B. T., Hopkins, L., Brown, C., Abdelrahman, T., Powell, A. G., Egan, R. J., & Lewis, W. G. (2019b). Relative value of adapted novel bibliometrics in evaluating surgical academic impact and reach. World Journal of Surgery, 43, 967–972.
Rodríguez‐Navarro, A. (2011). Measuring research excellence: Number of nobel prize achievements versus conventional bibliometric indicators. Journal of Documentation, 67(4), 582–600.
Rotem, N., Yair, G., & Shustak, E. (2021a). Dropping out of master’s degrees: Objective predictors and subjective reasons. Higher Education Research & Development, 40(5), 1070–1084.
Sahudin, Z., Mustaffa, A. H., Abdullah, H., Pramono, S. E., Wijaya, A., & Melati, I. S. (2023). Determinants of academic research productivity in malaysia: An integration of theory of planned behaviour and social capital theory. Asian Journal of University Education, 19(3), 486–505.
Salmi, J. (2011). The road to academic excellence: Lessons of experience. The road to academic excellence: The making of world-class research universities, 323–347.
Serenko, A., Marrone, M., & Dumay, J. (2022). Scientometric portraits of recognized scientists: A structured literature review. Scientometrics, 127(8), 4827–4846.
Singh, P., Piryani, R., Singh, V. K., & Pinto, D. (2020). Revisiting subject classification in academic databases: A comparison of the classification accuracy of web of science, scopus & dimensions. Journal of Intelligent & Fuzzy Systems, 39(2), 2471–2476.
Taheri, S. & Aliakbary, S. (2022). Research trend prediction in computer science publications: a deep neural network approach. Scientometrics, 127(2), 849–869.
Taylor, D. R., Venable, G. T., Jones, G. M., Lepard, J. R., Roberts, M. L., Saleh, N., … & Klimo, P. (2015). Five-year institutional bibliometric profiles for 103 US neurosurgical residency programs. Journal of neurosurgery, 123(3), 547–560.
Tijssen, R., Visser, M., & van Leeuwen, T. (2002). Benchmarking international scientific excellence: Are highly cited research papers an appropriate frame of reference? Scientometrics, 54(3), 381–397.
Transtrum, M. K., & Sethna, J. P. (2012). Improvements to the Levenberg-Marquardt algorithm for nonlinear leastsquares minimization. arXiv preprint arXiv:1201.5885.
Van den Besselaar, P. & Sandström, U. (2019). Measuring researcher independence using bibliometric data: A proposal for a new performance indicator. PloS one, 14(3): e0202712.
Wildgaard, L., Schneider, J. W., & Larsen, B. (2014). A review of the characteristics of 108 author-level bibliometric indicators. Scientometrics, 101, 125–158.