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How to Leverage Big Data Analytic Capabilities for Innovation Ambidexterity: A Mediated Moderation Model

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  • Suqin Liao

    (School of Management, Zhejiang University of Technology, Hangzhou 310000, China)

  • Qianying Hu

    (School of Management, Zhejiang University of Technology, Hangzhou 310000, China)

  • Jingjing Wei

    (School of Management, Zhejiang University of Technology, Hangzhou 310000, China)

Abstract

Building upon the knowledge-based dynamic capabilities view, this study seeks to examine how big data analytic capabilities can be leveraged to improve innovation ambidexterity by developing a mediated moderation framework. Survey data were collected from 199 Chinese big data companies to test our model. The results indicate that the dynamic decision-making capability mediates the relationship between big data analytic capabilities and innovation ambidexterity, and this mediating relationship is conditional on the moderator variable of cross-functional integration. This study enriches the literature about big data analytic capabilities and innovation ambidexterity by clarifying how big data analytic capabilities are positively related to innovation ambidexterity and uncovering the driver for pursuing innovation ambidexterity in a digital context. It also contributes to this line of research by revealing contingent factors to leverage big data analytic capabilities from the knowledge-based dynamic capabilities perspective.

Suggested Citation

  • Suqin Liao & Qianying Hu & Jingjing Wei, 2023. "How to Leverage Big Data Analytic Capabilities for Innovation Ambidexterity: A Mediated Moderation Model," Sustainability, MDPI, vol. 15(5), pages 1-19, February.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:5:p:3948-:d:1076162
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