Descriptive Statistics of Main Variables for Digital Transformation and TFP Study

Descriptive statistics likely supporting a study on the heterogeneous impact of digital transformation directions on enterprise total factor productivity. The dataset is a 5.5 KB Excel file authored by Peng Song and last updated on 2026-04-28. It is associated with research that categorized digital transformation into five directions using LDA topic modeling on annual reports of A-share listed companies.

Use Cases

• Analyzing the differential impact of AI, Big Data, and Digital Technology Application on TFP based on the study's findings.
• Investigating the mediating role of dynamic capability reconstruction in digital transformation based on the described mechanism.
• Comparing productivity effects across labor-intensive, technology-intensive, and manufacturing industries based on the heterogeneity analysis.

Strengths

• Dataset is small (5.5 KB), facilitating quick download and inspection.
• Released under a permissive CC-BY-4.0 license for reuse.
• Associated with a specific theoretical model and empirical test described in the metadata.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• The description is research-focused; the actual data content and structure require manual inspection.

Provenance

Source

figshare, authored by Peng Song.

Collection Method

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

Time Range

null

Freshness

Last updated 2026-04-28 17:48:30; freshness should be verified.

Geography

Focus on A-share listed companies suggests data is likely from China.