Big data thinking of top executives and corporate innovation: based on machine learning

Xuesong Tang, Qiang Liao, Wen Li and Wang Liao

China Journal of Accounting Studies, 2024, vol. 12, issue 4, 801-838

Abstract: Corporate top executives’ adaptation to big data technological trends and timely transformation of traditional cognitive patterns play crucial roles in driving corporate innovation. Grounded in the expansion logic of big data technology and upper echelons theory, this study investigates how executives’ big data thinking influences corporate innovation. Utilising machine learning methods to construct a big data thinking index for corporate executives, we find that such thinking significantly enhances corporate innovation levels. Mechanism analysis reveals that big data thinking improves organisational capabilities in complex information environments, manifested by more pronounced innovation-enhancing effects when firms face information complexity or management teams lack sophisticated information processing capabilities. Further analysis demonstrates that executives’ big data thinking effectively improves innovation quality. This research extends the investigation into economic consequences of big data development from a cognitive perspective, provides empirical evidence for stimulating corporate innovation potential, and offers policy implications for promoting high-quality economic development.

Date: 2024
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DOI: 10.1080/21697213.2025.2482613

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