Title: A benefit segmentation approach for innovation-oriented university-business collaboration
Authors: Tobias Kesting; Wolfgang Gerstlberger; Thomas Baaken
Addresses: Science-to-Business Marketing Research Centre, Münster University of Applied Sciences, Johann-Krane-Weg 27, D-48149 Münster, Germany ' Department of Marketing and Management, Faculty of Business and Social Sciences, Centre for Integrative Innovation Management, University of Southern Denmark, Campusvej 55, DK-5230 Odense M, Denmark ' Science-to-Business Marketing Research Centre, Münster University of Applied Sciences, Johann-Krane-Weg 27, D-48149 Münster, Germany
Abstract: Increasing competition in the light of globalisation imposes challenges on both academia and businesses. Universities have to compete for additional financial means, while companies, particularly in high technology business environments, are facing a stronger pressure to innovate. Universities seek to deal with this situation by academic engagement, hereby providing external research support for businesses. Relying on the market segmentation approach, promoting beneficial exchange relations between academia and businesses enables the integration of both perspectives and may contribute to solving current challenges. Transferring the segmentation approach and the customer benefit perspective to university-business collaboration (UBC), this paper develops a multi-step segmentation framework aimed at identifying research customer segments in technical textile industries in Western Europe. This novel view helps to promote UBC and benefits both actors and society.
Keywords: university-business collaboration; UBC; academic engagement; universities; industrial enterprises; textile industries; market segmentation; benefit segmentation; innovation collaboration; R&D; small and medium-sized enterprises; SMEs; inter-organisational collaboration.
International Journal of Technology Management, 2018 Vol.76 No.1/2, pp.58 - 80
Received: 16 Feb 2015
Accepted: 13 Jan 2016
Published online: 15 Dec 2017 *