Direction, evidence grade, and study type are AI-generated labels (gpt-5-mini), not human-verified. Syntheses are LLM-written. "Tensions" are machine-detected candidates, not confirmed contradictions. A research-acceleration tool, not peer review.
How this is built →
1Distinct papers
4Unique collaborators
1/1Semantic Scholar citation coverage
Publication dates unavailable. Corpus fetch span: 2026.
Identity provenance
Provider IDs
- Semantic Scholar:
2283209089
ORCID evidence
No valid ORCID is stored.
Observed aliases (1)
- Feng Wan (semantic scholar, provider refresh)
Topics and outcomes in this view
Assessment themes
- Innovation: 1 paper
- Org Design: 1 paper
- Productivity: 1 paper
Claim outcomes
- Firm Productivity: 1 paper
- Innovation Output: 1 paper
- Organizational Efficiency: 1 paper
Papers in the Semantic Scholar view
Latest stored Semantic Scholar author observations only. Citation counts below are from the same provider and are not combined with other services.
Scroll the table horizontally to see every column.
| Paper | Author evidence | Date | Provider citations |
|---|---|---|---|
| ByteDance used AI that learns across products and an adaptive organizational structure to scale and diversify at once, reversing the usual trade-off between specialization and expansion; diversification amplified the value of its AI assets rather than diluting them.semantic_scholar | Feng Wan provider id |
Fetched 2026-04-25 | 1 |
Citation observation summary
Semantic Scholar supplied counts for 1 of 1 papers in this view; 0 are missing. The observed paper counts sum to 1 cumulative citations. This is a coverage summary, not an author score or h-index.