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Bibliometric data and actual development in technology life cycles: flaws in assumptions

Bibliometric data and actual development in technology life cycles: flaws in assumptions Purpose – Motivated with the ever growing number of bibliometric trend extrapolation studies, the purpose of this paper is to demonstrate through two technologies how the selection of an upper limit of growth affects the correlation and causality of technology development measured with bibliometric data. Design/methodology/approach – The paper uses Gompertz and Fisher‐Pry curves to model the technological development of white light emitting diodes and flash memory, and show with extrapolation results from several bibliometric sources how a typical bias is caused in trend extrapolations. Findings – The paper shows how drastic an effect the decision to set an upper bound has on trend extrapolations, to be used as a reference for applications. The paper recommends carefully examining the interconnection of actual development and bibliometric activity. Originality/value – Despite increasing interest in modelling technological data using this method, reports rarely discuss basic assumptions and their effects on outcomes. Since trend extrapolations are applied more widely in different disciplines, the basic limitations of methods should be explicitly expressed. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png foresight Emerald Publishing

Bibliometric data and actual development in technology life cycles: flaws in assumptions

foresight , Volume 16 (1): 17 – Mar 4, 2014

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References (58)

Publisher
Emerald Publishing
Copyright
Copyright © 2014 Emerald Group Publishing Limited. All rights reserved.
ISSN
1463-6689
DOI
10.1108/FS-03-2013-0007
Publisher site
See Article on Publisher Site

Abstract

Purpose – Motivated with the ever growing number of bibliometric trend extrapolation studies, the purpose of this paper is to demonstrate through two technologies how the selection of an upper limit of growth affects the correlation and causality of technology development measured with bibliometric data. Design/methodology/approach – The paper uses Gompertz and Fisher‐Pry curves to model the technological development of white light emitting diodes and flash memory, and show with extrapolation results from several bibliometric sources how a typical bias is caused in trend extrapolations. Findings – The paper shows how drastic an effect the decision to set an upper bound has on trend extrapolations, to be used as a reference for applications. The paper recommends carefully examining the interconnection of actual development and bibliometric activity. Originality/value – Despite increasing interest in modelling technological data using this method, reports rarely discuss basic assumptions and their effects on outcomes. Since trend extrapolations are applied more widely in different disciplines, the basic limitations of methods should be explicitly expressed.

Journal

foresightEmerald Publishing

Published: Mar 4, 2014

Keywords: Forecasting; Modelling

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