A1 Journal article (refereed), original research

How to win innovation races in high-tech industries? An evolutionary optimization model


Publication Details
Authors: Kyläheiko Kalevi, Luukka Pasi, Jantunen Ari, Heinrich Torsten
Publication year: 2016
Language: English
Related Journal or Series Information: International Journal of Technology Intelligence and Planning
Volume number: 11
Issue number: 1
Start page: 62
End page: 91
JUFO-Level of this publication: 1
Open Access: Not an Open Access publication

Abstract
In this paper, we will present the firm’s knowledge base function and introduce an optimization problem, in which the firm seeks to maximize its profits with its scarce knowledge assets. In this, it has to share its knowledge resources between activities that help to increase the firm’s knowledge base and activities that are needed to protect and exploit the existing value creating knowledge base. In addition to these choices, the firm meets a question of whether and how to use partnerships when trying to maximize profits based on the knowledge. We will present these optimization problems from the perspectives of one company, two companies and three companies and introduce a differential evolution algorithm-based solution to the optimization problems. Our simulation results show that by proper optimization of knowledge assets, a company can achieve competitive advantage compared to its rivals.

Last updated on 2018-19-10 at 08:49