Data-driven sustainable transformation: Big Data policies and corporate green innovation

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🔬研究者:Provides causal evidence on big data policy effects on green innovation, with mechanisms and heterogeneity analysis.

🏢実務担当者:Highlights the role of data policies in enhancing green innovation, useful for corporate strategy in digitalizing economies.

🏛政策担当者:Informs design of data-driven environmental policies, suggesting tax incentives and patent quality platforms.

Research background: Amid global pressures to align digital transformation with environmental sustainability, big data policies have emerged as pivotal drivers of green innovation. These policies leverage advanced data analytics to foster eco-friendly technological advancements, yet their long-term impact on corporate innovation across diverse economic contexts remains underexplored. The potential of big data policies to transform environmental constraints into innovation opportunities underscores the need to examine their role in promoting sustainable development, particularly in rapidly digitizing economies. Purpose of the article: The study assesses the role of big data policies in promoting corporate green innovation—measured by green invention patent authorizations as quantity—and their contribution to sustainable technological advancements, utilizing innovation systems theory to rigorously investigate the diverse mechanisms influencing innovation performance in quantity, influence, quality, and diversity dimensions. Methods: Utilizing patent data from 4,728 Chinese listed firms in big data pilot and non-pilot regions to evaluate green innovation outcomes across quantity, influence, quality, and diversity. Using China’s National Big Data Comprehensive Pilot Zones (NBDCPZ) policy as a quasi-natural experiment, it applies innovation systems theory to examine mechanisms—including financial channels, policy attention, and R&D incentives—while heterogeneity tests assess variations by firm ownership, innovation capacity, and regional economic conditions, with robustness ensured through placebo tests and instrumental variable approaches. Findings & value added: Findings reveal that the big data policy boosts green innovation quantity by 4.5%, driven by enhanced financing, subsidies, and reduced information asymmetry, with stronger effects in non-state-owned and high-innovation firms. However, its impact on influence, quality, and diversity is limited, suggesting a quantitative focus. The study advocates tax incentives and patent quality platforms to enhance transformative innovation. By illuminating data-driven pathways to sustainability, this research offers strategies for emerging economies and contributes to the global policy-innovation nexus, laying groundwork for future studies on technology-enabled green development.

• semanticscholar https://doi.org/10.24136/eq.3761first seen 2026-05-15 20:57:07 · last seen 2026-07-01 05:53:00