Long-Run Forecasting of Emerging Technologies with Logistic Models and Growth of Knowledge

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dc.contributor.author Kucharavy, D.
dc.contributor.author Schenk, E.
dc.contributor.author De Guio, R.
dc.contributor.editor Rajkumar Roy
dc.contributor.editor Essam Shehab
dc.date.accessioned 2009-10-01T14:14:20Z
dc.date.available 2009-10-01T14:14:20Z
dc.date.copyright 2009
dc.date.issued 2009-03-31
dc.identifier.citation D. Kucharavy, E. Schenk, R. De Guio, Long-Run Forecasting of Emerging Technologies with Logistic Models and Growth of Knowledge, Proceedings of the 19th CIRP Design Conference – Competitive Design, Cranfield University, 30-31 March 2009, pp277 en_UK
dc.identifier.isbn 978-0-9557436-4-1
dc.identifier.uri http://hdl.handle.net/1826/3730
dc.description Organised by: Cranfield University en_UK
dc.description.abstract In this paper applications of logistic S-curve and component logistics are considered in a framework of longterm forecasting of emerging technologies. Several questions and issues are discussed in connection with the presented ways of studying the transition from invention to innovation and further evolution of technologies. First, the features of a simple logistic model are presented and diverse types of competition are discussed. Second, a component logistic model is presented. Third, a hypothesis about the usability of a knowledge growth description and simulation for reliable long-term forecasting is proposed. Some interim empirical results for applying networks of contradictions are given. en_UK
dc.description.sponsorship Mori Seiki – The Machine Tool Company en_UK
dc.language.iso en en_UK
dc.publisher Cranfield University Press en_UK
dc.relation.ispartof Proceedings of the 19th CIRP Design Conference – Competitive Design
dc.rights Copyright: Cranfield University 2009
dc.subject Component logistic model en_UK
dc.subject Innovation process en_UK
dc.subject Knowledge acquisition en_UK
dc.subject OTSM-TRIZ en_UK
dc.title Long-Run Forecasting of Emerging Technologies with Logistic Models and Growth of Knowledge en_UK
dc.type Conference paper en_UK


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