Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/37899
Title: Convergence of Impact Measures and Impact Bundles
Authors: EGGHE, Leo 
Issue Date: 2022
Publisher: SCIENDO
Source: Journal of Data and Information Science (Warsaw), 7 (3) , p. 5 -19
Status: Early view
Abstract: Purpose: A new point of view in the study of impact is introduced. Design/methodology/approach: Using fundamental theorems in real analysis we study the convergence of well-known impact measures. Findings: We show that pointwise convergence is maintained by all well-known impact bundles (such as the h-, g-, and R-bundle) and that the mu-bundle even maintains uniform convergence. Based on these results, a classification of impact bundles is given. Research limitations: As for all impact studies, it is just impossible to study all measures in depth. Practical implications: It is proposed to include convergence properties in the study of impact measures. Originality/value: This article is the first to present a bundle classification based on convergence properties of impact bundles.
Notes: Egghe, L (corresponding author), Hasselt Univ, Campus Diepenbeek, B-3590 Diepenbeek, Belgium.
leo.egghe@uhasselt.be
Keywords: Pointwise and uniform convergence of impact measures and bundles;Second Dini theorem;Arzela's theorem;Bundle classification;Generalized h- and g-indices;percentiles
Document URI: http://hdl.handle.net/1942/37899
ISSN: 2096-157X
e-ISSN: 2543-683X
DOI: 10.2478/jdis-2022-0014
ISI #: 000827179100001
Rights: 2022 Leo Egghe, published by Sciendo This work is licensed under the Creative Commons Attribution 4.0 International License. This is an open access article under the CC-BY license (https://creativecommons.org/licenses/by/4.0/).
Category: A1
Type: Journal Contribution
Appears in Collections:Research publications

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