Int. J. of Technology Intelligence and Planning   »   2016 Vol.11, No.1

 

 

Title: How to win innovation races in high-tech industries? An evolutionary optimisation model

 

Authors: Kalevi Kyläheiko; Pasi Luukka; Ari Jantunen; Torsten Heinrich

 

Addresses:
Lappeenranta University of Technology, P.O. Box 20, FI-53851 Lappeenranta, Finland
Lappeenranta University of Technology, P.O. Box 20, FI-53851 Lappeenranta, Finland
Lappeenranta University of Technology, P.O. Box 20, FI-53851 Lappeenranta, Finland
Institute for Institutional and Innovation Economics (IINO), Department of Business Studies & Economics, University of Bremen, P.O. Box 33 04 40, 28334 Bremen, Germany

 

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.

 

Keywords: appropriability; absorptive capacity; innovation; patents; tacitness; evolutionary optimisation; high-tech industries; high technology; knowledge base; partnerships; differential evolution; simulation; resource allocation.

 

DOI: 10.1504/IJTIP.2016.074240

 

Int. J. of Technology Intelligence and Planning, 2016 Vol.11, No.1, pp.62 - 91

 

Available online: 18 Jan 2016

 

 

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