Baseline Regression of Main Effects for Digital Transformation and Enterprise Productivity

5.5 KB of regression data supporting a study on the heterogeneous economic impacts of digital transformation. The dataset, authored by Peng Song and last updated in April 2026, likely contains empirical results testing the effects of five digital technology directions on Total Factor Productivity (TFP) of A-share listed companies. The analysis uses LDA topic modeling on corporate annual reports to categorize transformation into Artificial Intelligence, Big Data, Cloud Computing, Blockchain, and Digital Technology Application.

Use Cases

• Analyzing the differential impact of AI versus Blockchain on productivity based on the five technology directions mentioned.
• Testing the mediating role of dynamic capabilities in digital transformation based on the described transmission path.
• Conducting heterogeneity analysis across labor-intensive and technology-intensive industries based on the study's findings.
• Investigating the 'productivity paradox' in digital adoption using the provided micro-evidence framework.

Strengths

• Dataset is openly licensed under CC-BY-4.0.
• The underlying study employs a specific methodological approach using LDA topic modeling on annual reports.
• Focuses on a clearly defined theoretical model linking digital transformation, dynamic capability, and TFP.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• The dataset is very small at 5.5 KB, indicating limited scope, likely containing only summary regression results.

Provenance

Source

Peng Song via figshare.

Collection Method

Empirical analysis using LDA topic modeling on annual reports of A-share listed companies.

Time Range

null

Freshness

Last updated 2026-04-28 17:48:31; freshness should be verified.

Geography

Likely focuses on Chinese A-share listed companies, but not explicitly stated.