Scientometrics
Volume/Issue:
Volume 25: Issue 1
Classification of growth models based on growth rates and its applications
Authors:
L. Egghe LUC Universitaire Campus B-3590 Diepenbeek (Belgium) Universitaire Campus B-3590 Diepenbeek (Belgium)

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and
I. Ravichandra Rao

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Pages:
5–46
Online Publication Date:
13 Aug 2005
Publication Date:
26 Sep 1992
Article Category:
Research Article
DOI:
https://doi.org/10.1007/bf02016845
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Abstract  

In this paper, growth models are classified and characterised using two types of growth rates: from time t to t+1 and from time t to 2t. They are interesting in themselves but can also be used for a quick prediction of the type of growth model that is valid in a particular case. These ideas are applied on 20 data sets collected byWolfram, Chu andLu. We determine (using the above classification as well as via nonlinear regression techniques) that the power model (with exponent>1) is the best growth model for Sci-Tech online databases, but that Gompertz-S-shaped distribution is the best for social sciences and humanities online databases.

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Cover Scientometrics
Scientometrics
Print ISSN:
0138-9130
Online ISSN:
1588-2861

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Scientometrics
Language English
Size B5
Year of
Foundation		 1978
Volumes
per Year		 1
Issues
per Year		 12
Founder Akadémiai Kiadó
Founder's
Address		 H-1117 Budapest, Hungary 1516 Budapest, PO Box 245.
Publisher Akadémiai Kiadó
Springer Nature Switzerland AG
Publisher's
Address		 H-1117 Budapest, Hungary 1516 Budapest, PO Box 245.
CH-6330 Cham, Switzerland Gewerbestrasse 11.
Responsible
Publisher		 Chief Executive Officer, Akadémiai Kiadó
ISSN 0138-9130 (Print)
ISSN 1588-2861 (Online)

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