The impact of e-commerce development on the supply chain competitiveness of a-share listed companies in China
Why this work is in the frame
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Bibliographic record
Abstract
In China’s modern economic system, e-commerce has become a crucial driver for the development of businesses and supply chains. To clarify the impact and mechanisms of e-commerce development on the competitiveness of corporate supply chains, this study conducts an empirical analysis using data from A-share listed companies between 2010 and 2022. The results indicate that: (1) The development of e-commerce significantly enhances the competitiveness of corporate supply chains, with results remaining robust after endogenous and robustness tests; (2) The level of e-commerce development can further promote the improvement of supply chain competitiveness by improving resource integration, alleviating financing constraints, and increasing R&D investment; (3) The effects of e-commerce development exhibit heterogeneity: in state-owned enterprises and firms with lower competition, the influence of e-commerce on supply chains is more significant; in regions with high-speed rail (HSR) connectivity, e-commerce not only stabilizes customer relationships but also promotes corporate innovation, whereas in areas without HSR, e-commerce development may significantly mitigate issues related to capital occupation. The core innovation of this paper lies in the construction of a “e-commerce—resource integration/financing constraints/innovation investment—supply chain competitiveness” three-dimensional driving framework, establishing a multi-indicator evaluation system, and conducting heterogeneity and mechanism analyses from multiple perspectives. This provides systematic empirical evidence for the role of e-commerce in enhancing supply chain resilience and competitive advantage, offering policy recommendations for businesses to effectively improve their competitiveness.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it