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How to win innovation races in high-tech industries? An evolutionary optimisation model
by Kalevi Kyläheiko; Pasi Luukka; Ari Jantunen; Torsten Heinrich
International Journal of Technology Intelligence and Planning (IJTIP), Vol. 11, No. 1, 2016

 

Abstract: In this paper, we will present the firm's knowledge base function and introduce an optimisation problem where the firm seeks to maximise its profits with scarce knowledge assets. In this, it has to share its knowledge assets between activities that help to increase the firm's knowledge base and activities that are needed to protect and exploit the knowledge. In addition to these choices, the firm meets a question of whether and how to use partnerships when trying to maximise profits based on the knowledge assets that can be more or less protected. We will present the evolutionarily inspired optimisation problems as perspectives of one company, two companies and three companies and introduce the differential evolution algorithm as a solution to the optimisation problems. Our simulation results show that by proper optimisation of resource allocations, a company can achieve a sustainable advantage compared with other companies.

Online publication date: Mon, 18-Jan-2016

 

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