Citations optimal growth path: A tool to analyze sensitivity to citations of h-like indexes

• Published in: Journal of informetrics Vol. 15; no. 4; p. 101215
• Main Authors: Chen, Meiqian, Guo, Zhaoxia, Dong, Yucheng, Chiclana, Francisco, Herrera-Viedma, Enrique
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.11.2021
• Subjects: bibliometrics; h-index; optimal growth path; sensitivity analysis; h-index; optimal growth path; sensitivity analysis; bibliometrics
• ISSN: 1751-1577; 1875-5879
• DOI: 10.1016/j.joi.2021.101215

•We propose the citations optimal growth path (OGP) problems for the selected h-like indexes.•We present some interesting properties of the OGP-allocated strategies of citations.•We compare the sensitivity to citations of the selected h-like indexes.•We analyze the combination of the h-index with another h-like index. The h-index is a citation-based metric with extensive applications, and several variants have been developed to complement it. This study formulates the optimal growth path (OGP) models of selected h-like indexes, that is, the h-index, g-index, A-index, R-index, and e-index, and analyzes their OGP-allocated strategies of citations. It is argued that the OGP is a useful tool for analyzing the sensitivity of these h-like indexes to citations. Through simulation experiments with both real and random data, the sensitivity of the selected h-like indexes to citations is compared. Interestingly, it is found that the h-index performs the worst according to the OGP. Further, it is shown that combining the h-index with the A-index decreases the sensitivity to the citations of the h-index. In summary, this study provides new insights into how to evaluate scientific outputs based on h-like indexes.