Centralization or Decentralization? How Can Digital Transformation Empowers Firm Performance?
Bibliographic record
Abstract
Digitalization is a systematic shift driven by information technology. It is a long-term strategy aimed at improving firms' economic performance and fostering sustainable development. In this study, we utilize big data from China's A-share listed enterprises spanning from 2007 to 2022 to empirically examine the mechanisms through which digitalization affects firm performance. Research indicates that firm digitalization has a positive impact on firm performance. Specifically, for every 1 unit increase in the degree of firm digitalization, its performance increases by 0.36% in the current year and 0.26% in the following year. The result remains robust after undergoing a series of robustness tests. Furthermore, ownership concentration exerts positive moderating effects. When the ownership concentration increases by 1 unit, the positive impact of digitalization on enterprise performance will increase by 0.0001 unit. This study provides practical recommendations for businesses to effectively utilize digital technologies and achieve high-quality development.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.004 | 0.008 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".