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
0Unique collaborators
1/1OpenAlex citation coverage
Publication span: 2026. Corpus fetch span: 2026.
Identity provenance
Provider IDs
- Openalex:
A5136884311
ORCID evidence
No valid ORCID is stored.
Observed aliases (4)
- Kanzian, Thomas (openalex, provider refresh)
- Kanzian, Thomas (openalex, source metadata)
- Thomas Kanzian (openalex, provider refresh)
- Thomas Kanzian (openalex, source metadata)
Topics and outcomes in this view
Assessment themes
- Adoption: 1 paper
- Innovation: 1 paper
Claim outcomes
- Firm Productivity: 1 paper
- Adoption Rate: 1 paper
Papers in the OpenAlex view
Latest stored OpenAlex 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 |
|---|---|---|---|
| Companies that emphasize quantitative AI work in regulatory filings earn higher long-term market valuations, reflected in Tobin’s Q and enterprise-value multiples; by contrast, AI rhetoric and sentiment do not generate short-term stock gains, suggesting investors treat AI as a durable intangible rather than a speculative signal.openalex | Kanzian, Thomas provider id |
2026-01-26 | 0 |
Citation observation summary
OpenAlex supplied counts for 1 of 1 papers in this view; 0 are missing. The observed paper counts sum to 0 cumulative citations. This is a coverage summary, not an author score or h-index.