Is more diverse always the better? External knowledge source clusters and innovation performance in Germany - Maryam Haji Ali Beigi (Technische Universität Ilmenau, Institut für Volkswirtschaftslehre, 2021)
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 review, search diversity indicates a curvilinear pattern but with a steeper positivity than search breadth's. A prerequisite extension of this paper is to utilize a clustering method among different external sources acting as a reference to codify a diversity index for measuring the new search scheme. Also, the effect of usage of each cluster on innovation is empirically illustrated. This paper 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.
Keywords: 330; Search breadth; External search diversity; Search scope; Knowledge heterogeneity; Source clustering; Innovation performance