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View corpus contextCorporate digital transformation improves the substance—not just the format—of Chinese polluters' carbon reporting, raising disclosure quality via stronger media and audit scrutiny; gains are largest where competition, state ownership or digital infrastructure amplify monitoring.
Environmental Transparency Through Digital Transformation: Evidence on Carbon Disclosure Quality From China's Heavy‐Polluting Firms
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correlational
medium evidence
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Greater firm digital transformation is associated with higher quality carbon information disclosure among Chinese listed heavy‑polluting firms (2017–2024), primarily via strengthened external monitoring and concentrated in substantive disclosure content, with stronger effects in SOEs and regions with better digital infrastructure.
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ABSTRACT The rise of digital transformation (DT) has become an important driver of transparency in corporate environmental disclosure. Whether and how DT is related to the improvement of carbon information disclosure quality, particularly in heavily polluting firms that may have both information and symbolic roles, is still controversial. Based on the resource‐based view, information asymmetry theory, and signaling theory, this study examines the association between DT and carbon information disclosure quality in Chinese A‐share listed heavy‐polluting firms from 2017 to 2024. Using a multidimensional CIDQ index and panel data models, this study finds that DT is positively associated with carbon information disclosure quality. Additional analyses suggest that this relationship is linked to external monitoring channels, including media attention and audit effort, is stronger under higher product market competition, and is further strengthened when external monitoring and competition jointly increase. The results at the component level also reveal that the association is more obvious in carbon‐related business practices, carbon governance, and carbon performance rather than the disclosure carrier, which illustrates that DT may be more strongly associated with the content of carbon disclosure than with its reporting format or disclosure channel. Further analyses suggest a positive association between DT‐enabled disclosure quality and firms' environmental performance. Other analyses highlight that such an effect is more evident in state‐owned enterprises and areas with more advanced digital infrastructure. The study contributes to research on DT and environmental disclosure by showing both the transparency‐enhancing potential and the limitations of digitalized carbon reporting.
Summary
Main Finding
Digital transformation (DT) is positively associated with higher carbon information disclosure quality (CIDQ) among Chinese A‑share listed heavy‑polluting firms (2017–2024). The effect operates mainly through strengthened external monitoring (media attention, audit effort), is amplified by product‑market competition (especially when competition and monitoring increase together), and is concentrated in substantive disclosure content (carbon‑related business practices, governance, and performance) rather than reporting format or channels. DT‑enabled higher disclosure quality is also linked to better environmental performance, with stronger effects in state‑owned enterprises and regions with better digital infrastructure.
Key Points
- Sample/population: Chinese A‑share listed heavy‑polluting firms, 2017–2024.
- Main result: Greater firm DT → higher multidimensional CIDQ (panel data evidence).
- Mechanisms: External monitoring channels (media attention and audit effort) mediate/enhance the DT → CIDQ link.
- Moderation:
- Stronger DT effect under higher product‑market competition.
- Joint increases in external monitoring and competition further strengthen the effect.
- Component heterogeneity:
- Larger DT associations for substantive disclosure items: carbon‑related business practices, carbon governance, carbon performance.
- Smaller/noisy association for disclosure carrier (format/channel).
- Outcomes and heterogeneity:
- Higher DT‑driven CIDQ correlates with improved environmental performance.
- Effects are more pronounced in state‑owned enterprises (SOEs) and in areas with more advanced digital infrastructure.
- Interpretation: DT raises transparency and content quality of carbon reporting but has limits (less impact on format/carrier and potential symbolic reporting).
Data & Methods
- Data: Panel of Chinese A‑share listed heavy‑polluting firms, 2017–2024.
- Dependent variable: Multidimensional Carbon Information Disclosure Quality (CIDQ) index covering content elements (business practice, governance, performance) and disclosure carrier.
- Independent variable: Firm digital transformation measures (composite indicators of DT adoption/digital practices).
- Empirical approach: Panel data models with robustness and heterogeneity checks.
- Additional analyses:
- Mediation/interaction tests for external monitoring (media attention, audit effort) and product‑market competition.
- Component‑level regressions to separate content vs. carrier effects.
- Tests linking DT‑driven CIDQ to firms’ measured environmental performance.
- Subsample analyses by ownership (SOE vs. non‑SOE) and regional digital infrastructure.
Implications for AI Economics
- For modeling firm behavior and disclosure:
- DT (including AI and data analytics) materially reduces information asymmetry by improving the content quality of environmental disclosures; economic models of disclosure should incorporate digital capability as a state variable that affects signaling costs and credibility.
- Heterogeneous effects (stronger in SOEs, competitive markets, better infrastructure) imply adoption and impact are context‑dependent—models should allow for regional/ownership heterogeneity and complementary institutions (media, auditors).
- For asset pricing and risk assessment:
- Higher‑quality, DT‑enabled carbon disclosures improve observable firm environmental signals that investors and ML models can use to price climate risk more accurately; this affects cost of capital and valuations for high‑polluting firms.
- Since DT mainly improves substantive content rather than format, NLP/ML pipelines should prioritize extracting content indicators (governance, performance metrics) over surface features of reports.
- For policy and regulation:
- Policies that promote digital infrastructure, auditing standards, and media transparency can amplify DT’s benefits for disclosure quality and environmental performance.
- Regulators should incentivize digital systems that produce verifiable, machine‑readable substantive disclosures (not just digital report formats) to reduce symbolic reporting.
- For research on AI/digital tools:
- Open questions: causal identification of DT effects (endogeneity of DT adoption), the distinct roles of AI vs. other digital technologies, generalizability beyond China, and the channel from improved disclosure to actual emissions reductions.
- Opportunity for applied work: evaluate how specific AI tools (automated monitoring, anomaly detection, digital twins, blockchain verification) change disclosure credibility and market outcomes.
Assessment
Paper Typecorrelational
Evidence Strengthmedium — Findings are supported by firm-level panel models, multiple robustness and heterogeneity checks, and mediation/interaction analyses that bolster a plausible mechanism (external monitoring). However, causal inference is limited because no exogenous variation (natural experiment, IV, or difference‑in‑differences with plausibly exogenous treatment) is described, so endogeneity and reverse causality remain concerns.
Methods Rigormedium — The study uses panel data, multidimensional outcome construction, and a suite of robustness, mediation, and heterogeneity tests (strengths). But the absence of a clearly exogenous identification strategy, potential measurement error in composite DT and CIDQ indices, and limited information on controls, fixed effects, and dynamic specifications reduce causal credibility.
SampleFirm‑year panel of Chinese A‑share listed heavy‑polluting firms for 2017–2024; dependent variable is a constructed multidimensional Carbon Information Disclosure Quality (CIDQ) index (content and carrier subcomponents); independent variable is composite firm digital transformation (DT) measures; analyses include mediation (media attention, audit effort), interaction with product‑market competition, component‑level regressions, environmental performance outcomes, and subsamples by ownership and regional digital infrastructure.
Themesgovernance adoption innovation
IdentificationPanel regression analysis of firm-level panel data (2017–2024) linking firm-level digital transformation (DT) measures to a constructed multidimensional Carbon Information Disclosure Quality (CIDQ) index, with robustness checks, mediation/interaction tests (media attention, audit effort), component-level regressions, and subsample heterogeneity analysis; no explicit exogenous shock, instrument, or quasi‑experimental source of variation reported in the supplied text.
GeneralizabilityResults pertain only to listed Chinese heavy‑polluting firms and may not generalize to non‑listed firms or non‑polluting industries., China's regulatory, ownership (SOE prevalence), media, and auditing environment differs from other countries, limiting cross‑country generalizability., Period 2017–2024 may capture specific regulatory or market trends in China; effects could differ in other periods., DT measure is a composite—heterogeneity across specific technologies (AI vs. other digital tools) is not disentangled., Observational design limits causal extrapolation to settings with different endogeneity structures or measurement quality.
Claims (8)
| Claim | Direction | Outcome | Confidence & Evidence | Details |
|---|---|---|---|---|
| Digital transformation is positively associated with higher carbon information disclosure quality among Chinese A-share listed heavy-polluting firms during 2017–2024. Output Quality | positive | Multidimensional carbon information disclosure quality |
Reading fidelity
high
Study strength
medium
|
not reported
|
| The positive relationship between digital transformation and carbon information disclosure quality operates mainly through strengthened external monitoring, particularly media attention and audit effort. Output Quality | positive | Carbon information disclosure quality |
Reading fidelity
high
Study strength
medium
|
not reported
|
| Product-market competition strengthens the positive association between digital transformation and carbon information disclosure quality. Output Quality | positive | Carbon information disclosure quality |
Reading fidelity
high
Study strength
medium
|
not reported
|
| Joint increases in external monitoring and product-market competition further strengthen the positive effect of digital transformation on carbon information disclosure quality. Output Quality | positive | Carbon information disclosure quality |
Reading fidelity
high
Study strength
medium
|
not reported
|
| Digital transformation has stronger positive associations with substantive carbon disclosure components—carbon-related business practices, carbon governance, and carbon performance—than with the disclosure carrier or reporting format/channel. Output Quality | mixed | Component-level carbon information disclosure quality |
Reading fidelity
high
Study strength
medium
|
not reported
|
| Higher digital-transformation-driven carbon information disclosure quality is associated with improved environmental performance. Firm Productivity | positive | Firm environmental performance |
Reading fidelity
high
Study strength
medium
|
not reported
|
| The positive effects of digital transformation on carbon information disclosure quality and related environmental outcomes are more pronounced among state-owned enterprises than among non-state-owned enterprises. Output Quality | positive | Carbon information disclosure quality and related environmental performance |
Reading fidelity
high
Study strength
medium
|
not reported
|
| The positive effects of digital transformation are stronger for firms located in regions with more advanced digital infrastructure. Output Quality | positive | Carbon information disclosure quality and related environmental performance |
Reading fidelity
high
Study strength
medium
|
not reported
|