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Is more diverse always the better? External knowledge source clusters and innovation performance in Germany

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  • Maryam Hajialibeigi

Abstract

This study gives a new identity to a knowledge search mode named search diversity and investigates how it is more rigorous in capturing knowledge heterogeneity in comparison to general assessment of search breadth. By distinguishing between diversifying and expanding search domain as building blocks of broadening search scope, this study proposes a hybrid search strategy when it comes to analysis of the link between external search and innovation performance. While a positive trend is found for search breadth and innovation in this article, search diversity indicates a curvilinear pattern but with a steeper positivity than search breadth. A prerequisite extension of this article is to use a clustering method among different external sources acting as a reference to codify a diversity index for measuring the new search scheme. In addition, the effect of usage of each cluster on innovation is empirically illustrated. This article suggests that the optimal hybrid search outlook in respect to innovation is built up by initially increasing diversity in search up to the downturn point and then shifting into usage of same source clusters without helping diversity. This analysis provides practitioners with additional insights for managing external sourcing strategies and leveraging innovativeness.

Suggested Citation

  • Maryam Hajialibeigi, 2023. "Is more diverse always the better? External knowledge source clusters and innovation performance in Germany," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 32(5), pages 663-681, July.
  • Handle: RePEc:taf:ecinnt:v:32:y:2023:i:5:p:663-681
    DOI: 10.1080/10438599.2021.2007093
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