Data · dataset · 2026
From artificial intelligence empowerment to platform ecosystem restructuring:A study on value destruction and value co-creation
Listed in ScienceDB
This dataset is a supporting research data for the study of platform ecosystem reconstruction under the empowerment of artificial intelligence.
Description
It focuses on high-tech industries with high digitalization and prominent ecological collaboration characteristics (covering fields such as electronic information and communication equipment), and takes high-tech enterprises in the Yangtze River Delta region (Jiangsu, Zhejiang, Shanghai, and Anhui) with platform foundation and ecological collaboration practices as the research objects.
The survey will be conducted from September 2024 to early November 2025, targeting mid to senior level managers and business leaders familiar with the platform business and ecological cooperation of the enterprise. The questionnaire was designed based on mature scales at home and abroad, revised and improved through expert interviews and small sample pre surveys. It was distributed through multiple channels such as on-site distribution, email delivery, and online questionnaires.
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After strictly excluding invalid questionnaires, 340 valid questionnaires were finally obtained and measured using a Likert 7-level rating system. The dataset includes raw questionnaire data in SPSS format, complete survey scales, and regression analysis results from various stages of research, which can effectively support empirical research and in-depth analysis on topics such as artificial intelligence empowerment and platform ecosystem reconstruction.
Links
Where it is published
- DOI doi.org/10.57760/sciencedb.j00289.00029 ↗
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
- Computer Science & AI · Earth & Environmental Science · Engineering · Humanities · Life Sciences · Mathematics & Statistics · Social Science
- Inferred from text
- Ecological applications 73%
Provenance · 1 source records, 12 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| ScienceDB | 10.57760/sciencedb.j00289.00029 | 12 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| concepts[field].anzsrc:group:4102 | enrichment · scidb cn | taxonomy-embedding@1.0.0 | title+keywords+description (73%) |
| concepts[field].local:field:computer-science-ai | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| 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:mathematics-statistics | 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 |