Data · dataset · 2026
A Study of the Impact of Big Data Policies on Total Factor Productivity of Manufacturing Enterprises
Listed in ScienceDB
This dataset is derived from Chinese A-share listed manufacturing companies in Shanghai and Shenzhen from 2010 to 2023.
Description
The original raw data are obtained from the CSMAR database and the Wind database, and the list of National Big Data Comprehensive Pilot Zones comes from the official website of the Ministry of Industry and Information Technology. The data processing procedure includes: screening manufacturing enterprises, excluding those with missing key financial indicators, incomplete data, or being in ST or *ST status, ultimately obtaining 15,205 valid observations.
To reduce the impact of outliers, all continuous variables are winsorized at the 1st and 99th percentiles. The dependent variable is total factor productivity (TFP), measured by the LP method, with the OP and OLS methods used for robustness checks. The core independent variable is the policy dummy variable for the National Big Data Comprehensive Pilot Zone (bigdata), which is assigned a value of 1 if the region where the enterprise is registered is included in the pilot zone in and after the year of policy implementation, and 0 otherwise.
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Control variables include firm size, leverage ratio, net profit ratio, asset turnover ratio, cash flow ratio, fixed asset ratio, loss dummy, board size, ownership concentration, and Tobin’s Q. Mechanism variables include internal control index (from the DIB database), management efficiency (management and sales expense ratio), market competition (Herfindahl index), and supply chain resilience (supplier concentration).
The data cover the period from 2010 to 2023, with a spatial scope across China, covering enterprises in the eastern, central, and western regions. The temporal resolution is annual, and there is no spatial resolution requirement.
Links
Where it is published
- DOI doi.org/10.57760/sciencedb.j00289.00178 ↗
DOI / persistent id · from scidb cn
Catalogue records · 1
- OAI-PMH record scidb.cn/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=10.57760%2… ↗
metadata API · from scidb cn
Topics
- From keywords
- Earth & Environmental Science · Engineering · Humanities · Life Sciences · Social Science
- Inferred from text
- Manufacturing engineering 68%
Provenance · 1 source records, 10 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| ScienceDB | 10.57760/sciencedb.j00289.00178 | 12 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| concepts[field].anzsrc:group:4014 | enrichment · scidb cn | taxonomy-embedding@1.0.0 | title+keywords+description (68%) |
| concepts[field].local:field:earth-environmental | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:engineering | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:humanities | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:life-sciences | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:social-science | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| description | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/description |
| license_text | source · scidb cn | connector:scidb_cn@1.0.0 | |
| publication_date | source · scidb cn | connector:scidb_cn@1.0.0 | |
| title | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/title |