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Cited by 335

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Knowledge absorptive capacity and innovation performance in high-tech companies: A multi-mediating analysis

Xie, Xuemei, Zou, Hailiang, Qi, Guoyou·2018·Journal of Business Research

Abstract

Abstract Building upon the knowledge-based view (KBV) and using data from 379 high-tech companies in China, we examine the underlying, mediating mechanisms in the relationship between knowledge absorptive capacity and firms' innovation performance. We find that there are positive relationships between four dimensions of knowledge absorptive capacity (i.e., knowledge acquisition, knowledge assimilation, knowledge transformation, and knowledge exploitation) and firms' innovation performance. Additionally, we discover that both firms' knowledge transformation capacity and knowledge exploitation capacity mediate the relationship between knowledge acquisition and firms' innovation performance, as well as between knowledge assimilation and firms' innovation performance. Our results shed light on knowledge absorptive capacity research and knowledge management theory by theoretically and empirically demonstrating how knowledge absorptive capacity affects firms' innovation outputs from a multi-mediating perspective.

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Metadata

Authors
Xie, X., Zou, H., & Qi, G.
Venue
Journal of Business Research
Publisher
Elsevier BV
Published
2018-07
Volume
88
Pages
289-297
ISSN
0148-2963 (ISSN-L)
OpenAlex
W2786484532
Cited by
335
References
2
FWCI
40.64
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Knowledge absorptive capacity and innovation performance in high-tech companies: A multi-mediating analysis. https://app.cochat.ai/papers/10.1016/j.jbusres.2018.01.019
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Xie, X., Zou, H., & Qi, G. (2018). Knowledge absorptive capacity and innovation performance in high-tech companies: A multi-mediating analysis. Journal of Business Research. https://doi.org/10.1016/j.jbusres.2018.01.019

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.