The double-edged sword of external search in collaboration networks: embeddedness in knowledge networks as moderators
Journal of Knowledge Management, ISSN: 1758-7484, Vol: 23, Issue: 10, Page: 2135-2160
2019
- 72Citations
- 119Captures
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Article Description
Purpose: The purpose of this paper is to analyze the inverted U-shaped relationship between external search in the collaboration network and firm innovation outcomes. It also seeks to explore whether these curvilinear relationships are moderated by the network centrality and structural holes in the knowledge network. Design/methodology/approach: In this empirical research, the authors collected a sample of patents in the smartphone industry over the period of 2000-2017. Then the authors examined the direct roles of external search breadth and depth in the collaboration network and the moderating role of network embeddedness in the knowledge network by using negative binomial regression. Findings: Results found that external search in the collaboration network contributes more to firm innovation outcomes when the breadth and depth of the external search are moderate rather than high or low. Furthermore, both network centrality and structural holes in the knowledge network have positive effects on the external search breadth – innovation outcomes and external search depth – innovation outcomes relationships. Research limitations/implications: The authors collected the patent data within the single industry and excluded other types of industries. This may limit the generalization of the findings. Practical implications: The paper has practical implications for adopting appropriate search strategies in the collaboration network and developing a better understanding of the effect of network embeddedness in the knowledge network on firm innovation outcomes. The findings suggest future directions for technology-intensive industries to improve their innovation output. Originality/value: This study adds value to open innovation literature by pointing out a curvilinear relationship (inverted U-shaped) between external search breadth/depth and innovation outcomes in collaboration networks, in contrast to studies focused on firms’ external collaboration strategies in a certain industry context. Furthermore, this study reinforces the key contingent role of embeddedness in knowledge networks. This study provides a valuable theoretical framework of innovation outcome determinants by connecting the network perspective of open innovation theory with an embeddedness view.
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