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How does the ambidexterity of technological learning routine affect firm innovation performance within industrial clusters? The moderating effects of knowledge attributes

Jingjing Guo, Bin Guo, Jianghua Zhou and Xiaobo Wu

Technological Forecasting and Social Change, 2020, vol. 155, issue C

Abstract: This paper focuses on the influence of the ambidexterity of technological learning routine on firm innovation performance within industrial clusters. Specifically, this study seeks to examine how the combined dimension and the balance dimension of the ambidexterity of technological learning routine affect innovation performance of cluster firms. In addition, this study examines the moderating effect of knowledge tacitness and knowledge heterogeneity on the relationship between the ambidexterity of technological learning routine and innovation performance. Survey data from 217 industrial cluster firms in China reveals that the combined ambidexterity of technological learning routine promotes firm innovation performance, whereas the effect of the balance ambidexterity of technological learning routine on innovation performance is not supported. Besides, knowledge tacitness moderates the relationship between the ambidexterity of technological learning routine and firm innovation performance within industrial clusters, while the moderating effects of knowledge heterogeneity on the relationship between combined or balance ambidexterity of technological learning routine and innovation performance are not supported. This paper brings greater theoretical insights into the notion of technological learning routine by applying the ambidexterity perspective, and advances the understanding of the contextual factors between the routine ambidexterity-innovation performance relationship through elucidating the moderating role of knowledge attributes.

Keywords: Ambidexterity; Technological learning routine; Knowledge tacitness; Knowledge heterogeneity; Innovation performance (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:tefoso:v:155:y:2020:i:c:s0040162519304032

DOI: 10.1016/j.techfore.2020.119990

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