Ego–network stability or ego–network expansion? The effects of ego–network dynamics on recombinant innovation under heterogeneous knowledge base

本我、自我与超我 知识管理 独创性 知识库 心理学 重组DNA 计算机科学 自我耗竭 社会心理学 业务 人工智能 生物 创造力 生物化学 自我控制 基因
作者
Jianyu Zhao,Cheng Fu
出处
期刊:Journal of Knowledge Management [Emerald Publishing Limited]
卷期号:28 (5): 1278-1308 被引量:3
标识
DOI:10.1108/jkm-05-2023-0386
摘要

Purpose This paper aims to investigate the antecedents of recombinant innovation from the perspective of ego–network dynamics, and further disentangle whether ego–network stability or ego–network expansion is more conducive to recombinant innovation under heterogeneous knowledge base. Design/methodology/approach This paper uses 1,801 patent data in China’s biotechnology field as a sample and adopts fixed effects regression model to examine the effects of ego–network dynamics on recombinant innovation and further uses the Wald tests to discern which ego–network dynamic is more conducive to recombinant innovation under heterogeneous knowledge base. Findings The empirical results indicate that ego–network dynamics have a positive impact on recombinant innovation. Specifically, for firms with high knowledge breadth and high knowledge depth as well as high knowledge breadth and low knowledge depth, ego–network stability is more conducive to recombinant innovation. By contrast, for firms with low knowledge breadth and high knowledge depth, recombinant innovation benefits more from ego–network expansion. As for firms with low knowledge breadth and low knowledge depth, both ego–network stability and ego–network expansion can promote recombinant innovation, while the effects are not significant. Practical implications This research may enlighten managers to choose suitable ego–network dynamics strategies for recombinant innovation based on their knowledge base. Originality/value This research not only contributes to the literature on recombinant innovation by revealing the impact of different ego–network dynamics on recombinant innovation but also contributes to network dynamics theory by exploring whether ego–network stability or ego–network expansion is more conducive to recombinant innovation under a heterogeneous knowledge base.
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