Data · dataset · 2026
AI Authorship and Investor Allocation Dataset
Listed in Teesside University Research Data Repository
This dataset supports an experimental study examining how investors respond to AI-generated versus CEO-prepared earnings communication and to the disclosure of formal governance review.
Description
The study uses a 2×2 between-subjects randomized design with four conditions: CEO-prepared/no formal review, CEO-prepared/formal review, AI-generated/no formal review, and AI-generated/formal review. The experiment was designed to separate the effects of AI authorship from the effects of governance oversight, addressing whether investor reactions are driven by skepticism toward AI-generated communication, by the presence of formal review, or by the interaction between both factors.
The analytic dataset includes anonymized respondent-level observations from investment-experienced participants. Variables include experimental condition indicators, portfolio allocation outcomes across common stock, corporate bond, and risk-free asset alternatives, and behavioral perception measures including trust/credibility, perceived accountability, governance oversight, expected return, perceived risk, investment attractiveness, and decision confidence.
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The dataset also includes basic investor background controls such as investment experience, financial knowledge, risk tolerance, familiarity with AI, and general trust in AI. The workbook contains a concise README/codebook, the cleaned analysis dataset, and a compact results summary. It is intended to support replication, transparency, and robustness checks for the associated manuscript on AI authorship, governance review, and investor allocation behavior in earnings communication.
Links
Where it is published
- DOI doi.org/10.17632/n5swpzgzxv.1 ↗
DOI / persistent id · from researchdata tees ac uk
Catalogue records · 1
- OAI-PMH record data.mendeley.com/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai%3Adata… ↗
metadata API · from researchdata tees ac uk
Topics
Provenance · 1 source records, 14 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| Teesside University Research Data Repository | oai:data.mendeley.com/n5swpzgzxv.1 | 11 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].anzsrc:group:4602 | mapping · researchdata tees ac uk | vocabulary-mapper@1.0.0 | keywords['Artificial Intelligence'] |
| concepts[field].local:field:computer-science-ai | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:earth-environmental | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:economics-finance | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:engineering | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:humanities | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:life-sciences | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:psychology-behavioral | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:social-science | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| description | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/description |
| license | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/rights |
| publication_date | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| title | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/title |