The Driving Mechanism of Artificial Intelligence Applications on Firm Ambidextrous Innovation: The Mediating Role of Organizational Learning and the Moderating Effect of Knowledge Integration Capability

Jingyi Wang (), Hao Xue (), Qinhe Yu (), Minghan He () and Heshi Zhang ()
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Jingyi Wang: Tianjin University of Finance and Economics
Hao Xue: Tianjin University of Finance and Economics
Qinhe Yu: Tianjin University of Finance and Economics
Minghan He: Tianjin University of Finance and Economics
Heshi Zhang: Tianjin University of Finance and Economics

A chapter in Proceedings of the 2026 11th International Conference on Social Sciences and Economic Development (ICSSED 2026), 2026, pp 593-604 from Springer

Abstract: Abstract This study investigates how artificial intelligence (AI) applications drive firm ambidextrous innovation, focusing on the mediating role of organizational learning and the moderating effect of knowledge integration capability. Drawing on organizational learning theory and the knowledge-based view, we develop a moderated mediation model that conceptualizes AI as cognitive infrastructure reshaping organizational learning pathways. Based on two-phase survey data from 414 Chinese firms, we employ structural equation modeling to test our hypotheses. The results reveal that AI applications positively influence both exploitative innovation (β = 0.347, p

Keywords: Artificial Intelligence Applications; Organizational Learning; Firm Ambidextrous Innovation; Knowledge Integration Capability; Structural Equation Modeling (search for similar items in EconPapers)
Date: 2026
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DOI: 10.2991/978-94-6239-701-9_61

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