<p>Heterogeneity Analysis by Property Rights.</p>

A dataset supporting an empirical study on the differentiated impacts of five digital technology directions on enterprise Total Factor Productivity. The data was created by Peng Song and last updated on April 28, 2026. The 5.5 KB XLS file likely contains results from semantic analysis of A-share listed company annual reports.

Use Cases

• Analyzing the heterogeneous impact of AI, Big Data, and other digital technologies on firm productivity based on the described categorization.
• Testing the mediating role of dynamic capability reconstruction in the digital transformation-TFP relationship as outlined in the theoretical model.
• Conducting industry-level heterogeneity analysis, such as comparing effects in labor-intensive versus technology-intensive sectors mentioned in the description.
• Investigating the 'productivity paradox' by examining the differential significance of various technology directions as reported in the findings.

Strengths

• Dataset is openly licensed under CC-BY-4.0, permitting reuse and redistribution.
• File size is 5.5 KB, indicating a compact and likely focused dataset.
• The underlying research applies a specific theoretical model and LDA topic model analysis to A-share company reports, suggesting a structured methodological approach.

Limitations

• Row count and column-level documentation are unknown, which limits suitability assessment and requires manual inspection after download.
• The dataset is very small (5.5 KB), indicating limited scope and likely containing summary or aggregated results rather than raw underlying data.

Provenance

Source

figshare, author Peng Song.

Collection Method

Likely derived from semantic analysis (LDA topic model) of annual reports from A-share listed companies.

Time Range

null

Freshness

Last updated 2026-04-28 17:48:40; freshness should be verified.

Geography

Focus is on A-share listed companies, suggesting a Chinese corporate context.