Digital Transformation Impact on Chinese Enterprise Productivity, 5 Technology Directions

A 5.5 KB Excel dataset by Peng Song, last updated April 2026, containing empirical results on digital transformation's impact on enterprise total factor productivity. The data likely contains results from a study categorizing digital transformation into five technology directions—Artificial Intelligence, Big Data, Cloud Computing, Blockchain, and Digital Technology Application—using LDA topic modeling on A-share listed company reports.

Use Cases

• Analyzing the differential impact of AI, Big Data, and other digital technologies on firm productivity based on the described study results.
• Testing theories of dynamic capability reconstruction as a transmission mechanism for productivity gains.
• Investigating industry heterogeneity in digital transformation effects, such as in labor-intensive or technology-intensive sectors.
• Providing empirical evidence for the 'productivity paradox' in digital technology adoption.

Strengths

• Dataset is openly licensed under CC-BY-4.0.
• The study design is clearly described, involving semantic analysis of annual reports from A-share listed companies.
• Results differentiate impacts across five specific digital technology directions.

Limitations

• Dataset is very small at 5.5 KB, indicating limited scope.
• Row count and column-level documentation are unknown, requiring manual inspection after download.
• The description does not specify the exact temporal coverage of the underlying company reports.

Provenance

Source

Peng Song via figshare.

Collection Method

Data likely derived from LDA topic modeling semantic analysis of annual reports from Chinese A-share listed companies.

Time Range

null

Freshness

Last updated 2026-04-28 17:48:35.

Geography

Likely focuses on Chinese enterprises (A-share listed companies).