China’s supply‑chain digitalization pilot nudged listed firms toward real green innovation by improving carbon disclosure; the gains are concentrated in state‑owned and large companies, and are larger for substantive environmental R&D than for symbolic green signalling.
HRMARS - With the rapid expansion of the digital economy, the application of digital technologies has become an essential strategic choice for enterprise development. Against the backdrop of pollution reduction and carbon mitigation, green innovation has emerged as a crucial pillar supporting corporate sustainability. Drawing on a sample of Chinese A-share listed firms from 2012 to 2022, this study investigates the impact of supply chain digitalization (SCD) on corporate green innovation, distinguishing between substantive and strategic forms of innovation. Building on this framework, the study further examines the mediating mechanisms underlying these effects—with a focus on carbon information disclosure (CID) as a novel mediating pathway. The findings reveal that supply chain digitalization significantly fosters corporate green innovation, with a more pronounced effect on substantive innovation compared to strategic innovation. Moreover, heterogeneity arises depending on ownership structure and firm size, with stronger effects observed in state-owned and large enterprises. Additional analysis indicates that supply chain digitalization enhances substantive green innovation through strengthened carbon disclosure practices, thereby promoting overall corporate green innovation. All regression models include firm, industry, and year fixed effects to control for unobserved heterogeneity, and robustness tests confirm the stability of findings. Purpose: This study aims to empirically examine how supply chain digitalization (SCD) influences corporate green innovation, with a particular focus on distinguishing between substantive and strategic forms of innovation. Furthermore, it explores the mediating role of carbon information disclosure (CID) in this relationship—a mechanism underexplored in prior literature—thereby providing a deeper understanding of how digitalization drives green innovation in enterprises. Design/methodology/approach: Using panel data from Chinese A-share listed firms between 2012 and 2022, the study employs a quasi-natural experimental design based on the designation of pilot enterprises for supply chain innovation (China’s "Supply Chain Innovation and Application Pilot Program," launched in 2018). A difference-in-differences (DID) approach combined with regression models (incorporating firm, industry, and year fixed effects) is applied to estimate the impact of SCD on various dimensions of green innovation. Carbon information disclosure is incorporated as a mediating variable, and heterogeneity analyses are conducted with respect to ownership structure and firm size to assess moderating effects. To mitigate endogeneity, the study leverages the exogenous policy shock of the pilot program, includes comprehensive firm-level controls, and conducts robustness tests. Findings: The results reveal that supply chain digitalization significantly enhances corporate green innovation, with a more pronounced effect on substantive green innovation compared to strategic green innovation. Carbon information disclosure plays a mediating role in this relationship: SCD increases firms’ likelihood of disclosing carbon information, which in turn promotes substantive green innovation but not strategic innovation. The positive effects of SCD are stronger for state-owned enterprises and large enterprises, reflecting their superior resource endowments and strategic orientation toward green development. Robustness tests further confirm the stability of these findings. Research limitations/implications:The study focuses exclusively on Chinese A-share listed firms, which may limit the generalizability of the findings to other contexts. Additionally, the measurement of digitalization and innovation relies on secondary data, which may not fully capture qualitative aspects of internal practices. Future research could employ cross-country comparisons, survey data, or advanced methods such as text mining to explore additional mediating mechanisms (e.g., green absorptive capacity or digital collaboration) and dynamic effects over time. Practical implications: The findings provide actionable insights for managers and policymakers. Firms should actively embed digital technologies into supply chain operations to enhance transparency, reduce information asymmetry, and alleviate financing constraints, thereby stimulating green innovation. Policymakers should expand digital supply chain pilot programs and encourage voluntary carbon disclosure to improve environmental governance. Large and state-owned enterprises should leverage their advantages to lead the construction of green supply chain ecosystems and foster industry-wide sustainable development. Originality/value: This study contributes to the literature by integrating supply chain digitalization into the corporate green innovation framework, distinguishing between substantive and strategic innovation, and identifying carbon information disclosure as a novel mediating mechanism. It enriches the understanding of how digital transformation drives sustainability-oriented innovation and provides evidence-based insights into the heterogeneity of these effects across different types of firms.
Summary
Main Finding
Supply chain digitalization (SCD) significantly increases corporate green innovation among Chinese A‑share firms (2012–2022). The effect is larger for substantive (technology-driven, long‑term) green innovation than for strategic (symbolic, short‑term) green innovation. Carbon information disclosure (CID) partially mediates the positive effect of SCD on substantive green innovation (but not on strategic innovation). Effects are stronger in state‑owned enterprises and large firms. Results are estimated using a quasi‑natural experiment (2018 supply chain innovation pilot), DID models with firm/industry/year fixed effects, and a variety of robustness checks.
Key Points
- Direction and magnitude
- SCD → positive and significant rise in overall green innovation.
- Larger impact on substantive green innovation than on strategic green innovation.
- Mediating mechanism
- SCD increases carbon information disclosure.
- CID in turn promotes substantive green innovation, explaining part of the SCD → green innovation channel.
- CID does not significantly mediate the SCD → strategic innovation link.
- Heterogeneity
- Stronger SCD effects for state‑owned enterprises and larger firms (resource endowments, strategic orientation).
- Methodological rigor and limitations
- Uses exogenous policy shock (Supply Chain Innovation and Application Pilot Program, 2018) as quasi‑experiment.
- DID with firm, industry, and year fixed effects; comprehensive firm controls and robustness checks.
- Limitations: sample restricted to Chinese listed firms; reliance on secondary proxies for digitalization and innovation; qualitative internal practices not fully observed.
Data & Methods
- Sample: Panel of Chinese A‑share listed companies, 2012–2022.
- Identification strategy:
- Quasi‑natural experiment exploiting 2018 designation of pilot enterprises in China’s Supply Chain Innovation and Application Pilot Program.
- Difference‑in‑differences (DID) models comparing treated vs control firms before/after policy.
- Model controls and specifications:
- Firm, industry, and year fixed effects to control unobserved heterogeneity.
- Extensive firm‑level control variables (financial and governance characteristics).
- Robustness tests (alternative specifications, placebo tests, etc.) reported to confirm stability.
- Mediator and heterogeneity analysis:
- Carbon information disclosure (CID) modeled as a mediating variable.
- Heterogeneity checks by ownership type (state vs non‑state) and firm size.
- Measurement notes:
- Green innovation disaggregated into substantive vs strategic forms (paper distinguishes but relies on secondary indicators).
- SCD measured through policy treatment status and likely complementary secondary metrics (details in full paper).
Implications for AI Economics
- For theory and modeling
- Digitalization (including AI, IoT, blockchain) in supply chains has measurable positive externalities on sustainability‑oriented innovation; economic models of AI adoption should include environmental innovation outcomes as endogenous responses.
- Heterogeneous treatment effects matter: firm ownership and scale moderate returns to digitization—models studying AI diffusion should incorporate institutional and firm‑size heterogeneity.
- Mediating channels such as non‑financial disclosure (CID) are important transmission mechanisms; AI economics studies should analyze indirect pathways (transparency, signaling, financing) by which AI affects firm behavior.
- For empirical research
- Quasi‑experimental designs (policy shocks, pilot programs) are useful to identify causal effects of digital/AI adoption on broader economic outcomes (innovation, financing).
- Measure non‑financial outcomes (disclosure, reputational signals) alongside traditional outputs (patents, productivity) to capture full AI/digitalization impact.
- Consider long‑run dynamics: substantive innovation requires persistent investment—short‑run gains may differ from long‑run technological adoption patterns.
- For policy and practice
- Policymakers can leverage targeted digital supply chain pilot programs to accelerate green innovation; encourage standardized carbon disclosure to amplify benefits.
- Support for smaller and non‑state firms may be required to realize broad adoption benefits—subsidies, technical assistance, or disclosure incentives can reduce scale/ownership gaps.
- AI and digital infrastructure investments that improve transparency and information sharing can reduce financing frictions and unlock green R&D.
- Research opportunities for AI economists
- Cross‑country comparisons of SCD → green innovation to assess institutional interactions with AI adoption.
- Micro‑level studies combining firm surveys and text‑mining of disclosures to refine measurement of substantive vs strategic innovation.
- Explore other mediators (green absorptive capacity, digital collaboration networks, supply‑chain financing instruments) and welfare implications of digitalization‑driven green innovation.
Assessment
Claims (9)
| Claim | Direction | Confidence | Outcome | Details |
|---|---|---|---|---|
| Supply chain digitalization (SCD) significantly increases corporate green innovation among Chinese A-share listed firms (2012–2022). Innovation Output | positive | high | corporate green innovation (aggregate measures of green innovation such as green patents / environmentally oriented R&D outputs) |
0.48
|
| The positive effect of SCD on green innovation is stronger for substantive green innovation (actual environmentally beneficial R&D and technologies) than for strategic green innovation (symbolic/labeling or reputation‑oriented activities). Innovation Output | positive | high | substantive green innovation (green patents, concrete environmental R&D outputs) vs. strategic green innovation (signaling/compliance-oriented measures) |
0.48
|
| Carbon information disclosure (CID) is a key mediating channel: SCD increases the likelihood and quality of CID, which in turn promotes substantive green innovation. Innovation Output | positive | medium | mediator: carbon information disclosure (CID) metrics; outcome: substantive green innovation |
0.29
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| CID does not significantly mediate the relationship between SCD and strategic green innovation. Innovation Output | null_result | medium | strategic green innovation (signaling/compliance-oriented measures) and CID as mediator |
0.29
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| The SCD → green innovation effects are larger for state‑owned enterprises (SOEs). Innovation Output | positive | medium | corporate green innovation (subgroup: state‑owned enterprises) |
0.29
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| The SCD → green innovation effects are larger for large firms (by firm size). Innovation Output | positive | medium | corporate green innovation (subgroup: large firms) |
0.29
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| The main results are robust to inclusion of firm, industry, and year fixed effects, DID identification using the 2018 SCD pilot, and multiple robustness checks addressing potential confounders and endogeneity. Research Productivity | positive | high | robustness of estimated SCD effects on corporate green innovation |
0.48
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| The 2018 Supply Chain Innovation and Application Pilot Program can be used as a quasi‑natural experiment (treatment) to identify causal effects of SCD on firm outcomes. Research Productivity | positive | medium | causal identification of SCD effects on corporate outcomes (green innovation, CID) |
0.29
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| Study limitations include single-country (China) listed‑firm sample and reliance on secondary/administrative proxies for digitalization and innovation, which may miss internal qualitative aspects and introduce measurement error. Research Productivity | null_result | high | external validity and measurement quality of SCD and innovation proxies |
0.48
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