Firms that pair digital upgrades (including AI-related capabilities) with green transformation convert R&D into innovation outputs more efficiently; the gain is clearest for private, finance‑constrained firms and those backed by steady institutional investors, and it disproportionately raises strategic and breakthrough innovation.

Main Finding

Digital-green synergy — the coordinated adoption of digital capabilities with green-oriented transformation — is positively associated with corporate innovation efficiency among Chinese GEM-listed firms (2009–2023). Both internally integrated (within-firm) and externally realized (market/ network/ disclosure-related) digital-green synergies improve the conversion of innovation inputs into outputs, with larger effects for non-state-owned firms, firms facing higher financing constraints, and those with stable institutional investors. The synergy particularly boosts strategic, breakthrough, and exploitative innovation more than substantive, incremental, and exploratory innovation.

Key Points

• Theoretical framing: draws on the Porter hypothesis (environmental regulation can spur innovation) and synergy theory (complementary resources yield greater joint returns).
• Two forms of synergy:
  • Internal digital-green synergy: integration of a firm’s own digital capabilities with green transformation activities — enhances knowledge flows and absorptive capacity.
  • External digital-green synergy: openness/interaction with external stakeholders, reflected in greater information transparency and higher disclosure quality — reduces information asymmetry and increases external recognition of green innovation.
• Heterogeneous effects:
  • Stronger positive association for non-state-owned enterprises (organizational flexibility).
  • Stronger for firms with higher financing constraints (resource pressure amplifying the value of coordination).
  • Stronger for firms with stable institutional investors (governance and investor stability supporting long-term transformation).
• Innovation type differences:
  • Digital-green synergy correlates more with strategic and breakthrough innovation as well as exploitative innovation than with substantive, incremental, or exploratory innovation.

Data & Methods

• Data: panel dataset of Chinese firms listed on the Growth Enterprise Market (GEM), covering 2009–2023.
• Core variables:
  • Dependent variable: firm-level innovation efficiency (conversion of R&D and other innovation inputs into outputs).
  • Key independent variables: measures capturing internal and external digital-green synergy (paper decomposes synergy into internal vs external components).
• Empirical approach: panel-level econometric analysis examining associations between digital-green synergy and innovation efficiency, with routine robustness and heterogeneity analyses (firm types, financing constraints, investor stability) and comparisons across innovation types.
• Mechanism tests: examine mediating channels such as knowledge flows/absorptive capacity (internal channel) and information transparency/disclosure quality/reduced information asymmetry (external channel).

(Note: the summary reports the methods and empirical strategy at a high level as described in the study; the original paper likely reports specific variable constructions, fixed-effects/specification choices, and robustness tests in detail.)

Implications for AI Economics

• For firms and managers:
  • Investing in AI and other digital capabilities alongside green investments can raise the productivity of R&D and innovation spending — especially valuable for non-state firms and those under financing pressure.
  • Coordinate internal digital transformation (AI-enabled knowledge management, data integration) with green strategies to strengthen absorptive capacity and accelerate commercialization of green innovations.
• For investors and governance:
  • Stable institutional investors magnify returns to coordinated digital-green transformation; investors seeking impact or long-term value should prioritize firms showing integrated digital–green strategies.
  • Improved disclosure and transparency enabled by digital tools reduces information asymmetry and can lead to greater external recognition and financing support for green innovation.
• For policymakers:
  • Policies encouraging simultaneous digitalization and green transition (e.g., subsidies, tax incentives, standards for green IT adoption and green reporting) can increase innovation efficiency at the firm level.
  • Target support to firms likely to benefit most (SMEs/non-state firms, financially constrained firms) to amplify overall economy-wide innovation gains.
• For AI economics research:
  • Digital capabilities (including AI) are not neutral: their value depends on complementarity with firm objectives like decarbonization. Empirical work should treat digital adoption and green transformation as joint treatments rather than separate controls.
  • When estimating returns to AI or digital investments, account for interaction effects with environmental strategy, governance, and financing constraints to avoid biased welfare and productivity assessments.
  • The stronger link to strategic and breakthrough innovation implies AI–green coordination may shift firm-level innovation portfolios toward higher-impact innovations; models of technological change should incorporate such compositional effects.

If you want, I can (a) extract likely operationalizations and variable definitions typically used for digital-green synergy and innovation efficiency, (b) propose an econometric specification or robustness checks suitable for replication, or (c) summarize policy recommendations tailored to a particular stakeholder (firm, investor, or regulator).