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View corpus contextListed Chinese food firms that adopt digital technologies exhibit stronger supply-chain resilience, with gains linked to improved transparency, easier financing, and reduced supplier/customer concentration; effects are largest for innovative firms in stable, marketized regions.
Can digital technology adoption enhance supply chain resilience? Evidence from listed food firms in China
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Using Chinese A-share listed food firms (2009–2024), the authors find that higher text-measured digital technology adoption is associated with greater firm-level supply chain resilience, with evidence that improved information transparency, eased financing constraints, and lower supply-chain concentration partially mediate the effect and that benefits are larger for more innovative firms, in more marketized regions, and under lower environmental uncertainty.
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View corpus contextAs a sector vital to national welfare and people’s livelihoods, the food industry has supply chains characterized by perishable raw materials, pronounced seasonality, stringent safety standards, extended chain structures, and highly fragmented participants. These features make food supply chains particularly vulnerable to external shocks, making the enhancement of supply chain resilience essential for safeguarding food safety and industrial and supply chain security. Using a sample of food firms listed on the Shanghai and Shenzhen A-share markets from 2009 to 2024, we systematically examine the effect of digital technology adoption on supply chain resilience, its potential channels, and heterogeneous effects. First, digital technology adoption significantly enhances the supply chain resilience of food firms. Second, digital technology adoption is significantly associated with greater information transparency, weaker financing constraints, and lower supply chain concentration. Third, this resilience-enhancing effect is more pronounced among firms facing lower environmental uncertainty, firms with stronger corporate innovation capability, and firms located in regions with a higher level of regional marketization. Focusing on the unique context of the food industry, we examine the potential channels and heterogeneous effects of digital technology adoption and provide micro-level empirical evidence for advancing the digital transformation of food firms, safeguarding food safety, and maintaining stable supply.
Summary
Main Finding
Digital technology adoption by Chinese listed food firms (2009–2024) significantly strengthens firm-level supply chain resilience. The effect operates in part through increased information transparency, eased financing constraints, and reduced supply‑chain concentration, and is stronger for firms with lower environmental uncertainty, higher innovation capability, and those located in more marketized regions.
Key Points
- Paper: Li & Zhu (2026), Frontiers in Sustainable Food Systems — sample: food firms listed on Shanghai and Shenzhen A‑share markets, 2009–2024.
- Theoretical anchor: dynamic capability theory — firms need timely risk information, financing to respond, and flexible supplier/customer relationships to be resilient.
- Main empirical finding: measurable digital technology adoption is positively and significantly associated with a composite supply‑chain resilience index.
- Proposed channels and empirical evidence:
- Information transparency: digital adoption → better information flow/visibility.
- Financing constraints: digital adoption → alleviates financing frictions.
- Supply‑chain concentration: digital adoption → lowers dependence on concentrated suppliers/customers.
- Heterogeneity: the resilience benefit is larger when (a) environmental uncertainty is lower, (b) firms have stronger innovation capability, and (c) the regional marketization level is higher.
- Contributions: focuses on the food sector (high perishability/safety sensitivity), tests three complementary channels (information, finance, structure), and documents boundary conditions for the effect.
Data & Methods
- Sample: Chinese listed food firms on Shanghai and Shenzhen A‑share markets, 2009–2024.
- Digital adoption measure: textual analysis of firm annual reports; frequency of digital‑technology related keywords (AI, blockchain, cloud, big data, IoT, etc.).
- Dependent variable: firm‑level supply‑chain resilience constructed as a composite index (entropy method) across five dimensions — resistance capability, recovery capability, operational capability, supply–demand matching, and renewal capability.
- Empirical strategy: panel regressions with two‑way fixed effects (firm and year) to estimate the effect of digital adoption on resilience; tests for mediation/associations with information transparency, financing constraints, and supply‑chain concentration; subgroup analyses for heterogeneous effects.
- Robustness: multiple channels examined and heterogeneity explored (paper reports consistent, significant results).
Implications for AI Economics
- Micro‑level evidence that AI and related digital technologies (big data, cloud, blockchain, IoT) act as general‑purpose technologies that enhance firms’ ability to absorb shocks — an important channel by which digitalization affects sectoral resilience and economic stability.
- Mechanism clarity: AI/digital adoption reduces information asymmetries (improving visibility), which has downstream effects on financing costs and access; this links technology adoption to financial market outcomes (credit allocation, risk assessment).
- Complementarities matter: the payoff to AI adoption depends on firm capabilities (innovation) and institutional context (regional marketization, environmental uncertainty). Models of technology diffusion and productivity should incorporate such complementarities and heterogeneity.
- Policy and market implications:
- For regulators and policymakers: targeted digital support for food firms (traceability, predictive analytics, cold‑chain optimization) is likely to raise supply‑chain resilience—particularly effective when combined with innovation support and market reforms.
- For financiers and insurers: digital adoption signals reduced information frictions and potentially lower supply‑chain risk; this could inform lending standards, pricing of supply‑chain finance, and insurance products.
- For firms and platform providers: investments in AI/data platforms yield resilience returns beyond efficiency gains; however, returns are higher when firms can absorb technology (innovation capabilities) and operate in supportive market environments.
- Research directions for AI economics: quantify welfare gains from resilience improvements, disaggregate effects by specific digital technologies (AI vs blockchain vs IoT), explore causal identification (natural experiments, instruments), examine upstream/downstream spillovers, and model interactions between digitalization, finance, and network structure in production networks.
Assessment
Paper Typecorrelational
Evidence Strengthmedium — Uses a long firm-year panel (2009–2024) and firm and year fixed effects, which control for time-invariant firm heterogeneity and common time shocks, and examines plausible mechanisms; however, identification relies on observational within-firm variation without exogenous shocks, instruments, or quasi-experimental variation, leaving open time-varying omitted variables, reverse causality, and measurement error concerns.
Methods Rigormedium — Careful measurement approach (textual keyword-based adoption index; entropy-based composite resilience index) and panel FE regressions are standard and appropriate for firm-level longitudinal data; the paper also investigates mediation channels and heterogeneity. But the approach lacks a clear strategy to rule out endogeneity from time-varying confounders or reverse causation, and the digital adoption measure (keyword frequency) can be noisy or subject to strategic reporting.
SampleFirm-year panel of food firms listed on the Shanghai and Shenzhen A-share markets, 2009–2024; digital adoption measured via keyword frequency in annual reports; supply chain resilience constructed as a composite (entropy) index across five dimensions; exact N (number of firms/observations) not provided in the excerpt.
Themesadoption innovation org_design
IdentificationPanel two-way fixed effects (firm and year) regression using within-firm variation in a text-derived measure of digital technology adoption (keyword frequency from annual reports); mechanisms explored via associations with proxies for information transparency, financing constraints, and supply chain concentration; no instrumental variables, regression discontinuity, or natural experiment reported in the provided text.
GeneralizabilityLimited to publicly listed food firms in China (A-share market) — may not generalize to SMEs, unlisted firms, or non-Chinese contexts., Food-industry specific (perishability, seasonality); findings may not apply to other sectors., Text-based measure of digital adoption aggregates heterogeneous technologies (AI, blockchain, cloud, big data) and may not capture actual technology deployment or intensity., Possible time-period-specific effects (2009–2024 includes major shocks like COVID-19) that may influence estimated relationships., Regional institutional and marketization variation in China may limit transferability to countries with different institutional environments.
Claims (7)
| Claim | Direction | Outcome | Confidence & Evidence | Details |
|---|---|---|---|---|
| Digital technology adoption significantly enhances the supply chain resilience of food firms listed on the Shanghai and Shenzhen A-share markets. Organizational Efficiency | positive | Supply chain resilience |
Reading fidelity
high
Study strength
medium
|
not reported
|
| Digital technology adoption is significantly associated with greater information transparency among food firms. Organizational Efficiency | positive | Information transparency |
Reading fidelity
high
Study strength
medium
|
not reported
|
| Digital technology adoption is significantly associated with weaker financing constraints among food firms. Organizational Efficiency | positive | Financing constraints |
Reading fidelity
high
Study strength
medium
|
not reported
|
| Digital technology adoption is significantly associated with lower supply chain concentration among food firms. Organizational Efficiency | positive | Supply chain concentration |
Reading fidelity
high
Study strength
medium
|
not reported
|
| The resilience-enhancing effect of digital technology adoption is more pronounced among food firms facing lower environmental uncertainty. Organizational Efficiency | positive | Supply chain resilience |
Reading fidelity
high
Study strength
medium
|
not reported
|
| The resilience-enhancing effect of digital technology adoption is more pronounced among firms with stronger corporate innovation capability. Organizational Efficiency | positive | Supply chain resilience |
Reading fidelity
high
Study strength
medium
|
not reported
|
| The resilience-enhancing effect of digital technology adoption is more pronounced among firms located in regions with higher levels of regional marketization. Organizational Efficiency | positive | Supply chain resilience |
Reading fidelity
high
Study strength
medium
|
not reported
|