Searching for partners in open innovation settings: How to overcome the constraints of local search
Meulman, Freek Reymen, Isabelle M. M. J. Podoynitsyna, Ksenia Romme, A. Georges L.
Meulman, Freek
Reymen, Isabelle M. M. J.
Podoynitsyna, Ksenia
Romme, A. Georges L.
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Publication Type
Journal article with impact factor
Editor
Supervisor
Publication Year
2018
Journal
California Management Review
Book
Publication Volume
60
Publication Issue
2
Publication Begin page
71
Publication End page
97
Publication Number of pages
Collections
Abstract
The search for partners in open innovation settings often consumes substantial time and managerial attention. Yet, organizations tend to get trapped in local search, which typically leads to collaboration with partners already known to them. To improve the search for partners, this article develops a tool that exploits the power of state-of-the-art information technology. In a sample of 33 search queries conducted in six innovation intermediaries, it studies differences between search with and without the use of our tool. The tests confirm the tool’s effectiveness and efficiency, and highlight the importance of searching with keywords that represent the core roles and activities of a firm, next to keywords referring to market and technology characteristics. Network visualization and semantic algorithms thus appear to facilitate the effort to identify distant partners. The article also finds that local partners are not that easy to find as commonly assumed.
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Organizational Units
Journal Issue
Keywords
Partner Identification, Local and Distant Search, Open Innovation, Actionable Knowledge