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 listed firms (2012–2022). The effect is stronger for substantive green innovation (actual environmentally beneficial R&D and technologies) than for strategic green innovation (symbolic/labeling or reputation‑oriented activities). Carbon information disclosure (CID) is a key mediating channel: SCD raises the likelihood and quality of CID, which in turn promotes substantive green innovation. Effects are larger for state‑owned enterprises and big firms. Results are robust to firm, industry, and year fixed effects, DID identification using a 2018 SCD pilot, and multiple checks.
Key Points
- Definitions
- Substantive green innovation: concrete environmental R&D outputs and technologies (e.g., green patents).
- Strategic green innovation: signaling or compliance‑oriented activities with weaker substantive environmental impact.
- Core empirical finding: SCD → higher green innovation; effect magnitude greater for substantive than strategic innovation.
- Mediating mechanism: SCD → better carbon information disclosure → greater substantive green innovation. CID does not significantly mediate strategic innovation.
- Heterogeneity: stronger SCD effects in state‑owned enterprises (SOEs) and large firms, attributed to better resources and strategic orientation.
- Identification & robustness: quasi‑natural experiment using China’s 2018 “Supply Chain Innovation and Application Pilot Program” and difference‑in‑differences (DID); controls for unobserved heterogeneity and runs robustness tests to mitigate endogeneity.
- Limitations noted by authors: single‑country, listed‑firm sample; measurement of digitalization and innovation from secondary data may miss internal qualitative aspects.
Data & Methods
- Sample: Chinese A‑share listed firms, 2012–2022 panel.
- Treatment: designation as pilot enterprises under the 2018 Supply Chain Innovation and Application Pilot Program (used as an exogenous shock to SCD).
- Outcome variables: measures of green innovation (substantive vs strategic); carbon information disclosure indicators.
- Econometric approach:
- Difference‑in‑differences (DID) specification comparing treated vs control firms pre/post‑2018.
- Regression models include firm, industry, and year fixed effects; firm‑level controls included.
- Mediation analysis to test CID as a pathway from SCD to green innovation.
- Heterogeneity analyses by ownership (SOE vs non‑SOE) and firm size.
- Robustness checks: alternative specifications and checks to address potential confounders and endogeneity.
- Data limitations: reliance on administrative/secondary datasets for digitalization and innovation proxies; possible measurement error in capturing internal digital practices.
Implications for AI Economics
- AI as an accelerator of SCD: The findings imply that digitalization of supply chains—of which AI (predictive analytics, demand forecasting, route optimization, anomaly detection) is a central component—can produce measurable welfare‑relevant innovation outcomes (environmental R&D). AI investments in supply chains may therefore have positive externalities by reducing information frictions and enabling green investment.
- Information disclosure and market discipline: Improved CID induced by SCD suggests digital/AI systems can increase transparency that influences firms’ investment in substantive innovation. For AI economists, this highlights feedback loops where AI‑enabled disclosure affects capital allocation, cost of capital, and incentives for green technology adoption.
- Heterogeneous diffusion and inequality: Larger firms and SOEs capture more of the SCD→green innovation gains. From an AI economics perspective, this raises questions about distributional effects of AI adoption across firm sizes and ownership types, market concentration, and potential barriers for SMEs to access AI‑driven SCD benefits.
- Policy design: The quasi‑experimental evidence supports targeted pilot programs to spur digitalization as a policy lever for green innovation. AI‑specific policies (subsidies for AI adoption in supply chains, standards for carbon data interoperable across platforms, and disclosure mandates) can amplify these effects. Designing disclosure standards that make AI‑derived emissions estimates verifiable will be important.
- Measurement and methods for future research: The paper’s use of DID with policy shocks is a strong causal approach; AI economists can extend this by:
- Using granular digital trace data (platform logs, sensor/IoT streams) and AI methods (text mining, NLP) to better measure digitalization and green innovation.
- Evaluating causal impacts of specific AI applications (e.g., ML forecasting vs. optimization) on green outcomes.
- Studying dynamic spillovers: how AI‑driven SCD diffuses through supplier networks and affects industry‑level green technology adoption.
- Financial and market implications: If SCD increases CID and substantive innovation, markets may start pricing firms’ AI‑driven digital capabilities into valuations, sustainability premia, and access to green finance. AI economists should study how disclosure quality (potentially improved by AI) affects borrowing costs, investor behavior, and carbon markets.
- Research agenda suggestions:
- Cross‑country comparisons to test external validity and regulatory interactions (e.g., disclosure laws, data privacy).
- Firm‑level surveys and randomized trials to isolate specific AI/digital capabilities.
- Using NLP to classify patent texts or disclosures to refine substantive vs strategic innovation measurement.
- Modeling strategic adoption of AI/SCD under competitive dynamics and heterogeneous firm constraints.
If you want, I can: (a) draft specific hypotheses for an AI‑focused follow‑up study, (b) propose variables and data sources for measuring AI components of SCD, or (c) sketch an empirical design (RCT/DID/instrumental variable) to isolate causal effects of particular AI tools on green innovation. Which would you prefer?
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) |
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| 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
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| 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 |
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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 |
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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) |
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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) |
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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 |
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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) |
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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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