Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/193746
Authors: 
Kasa, Richard
Year of Publication: 
2015
Citation: 
[Journal:] Investigaciones Europeas de Dirección y Economía de la Empresa (IEDEE) [ISSN:] 1135-2523 [Volume:] 21 [Year:] 2015 [Issue:] 1 [Pages:] 35-46
Abstract: 
In a remarkably short time, economic globalisation has changed the world's economic order, bringing new challenges and opportunities to SMEs. These processes pushed the need to measure innovation capability, which has become a crucial issue for today's economic and political decision makers. Companies cannot compete in this new environment unless they become more innovative and respond more effectively to consumers' needs and preferences - as mentioned in the EU's innovation strategy. Decision makers cannot make accurate and efficient decisions without knowing the capability for innovation of companies in a sector or a region. This need is forcing economists to develop an integrated, unified and complete method of measuring, approximating and even forecasting the innovation performance not only on a macro but also a micro level. In this recent article a critical analysis of the literature on innovation potential approximation and prediction is given, showing their weaknesses and a possible alternative that eliminates the limitations and disadvantages of classical measuring and predictive methods.
Subjects: 
Innovation potential
Approximation
Neural networks
Fuzzy logic
JEL: 
C45
C51
C65
C32
Persistent Identifier of the first edition: 
Creative Commons License: 
http://creativecommons.org/licenses/by-nc-nd/3.0/
Document Type: 
Article
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