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
5Unique collaborators
1/1Semantic Scholar citation coverage
Publication span: 2026. Corpus fetch span: 2026.
Identity provenance
Provider IDs
- Semantic Scholar:
2433049832
ORCID evidence
No valid ORCID is stored.
Observed aliases (1)
- Omosuyi Julius, Surulere (semantic scholar, provider refresh)
Topics and outcomes in this view
Assessment themes
- Adoption: 1 paper
- Innovation: 1 paper
Claim outcomes
- Adoption Rate: 1 paper
- Firm Revenue: 1 paper
- Other: 1 paper
- Consumer Welfare: 1 paper
- Task Allocation: 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 |
|---|---|---|---|
| Nigerian retailers using AI plus IoT to personalize green engagement report 25–40% higher customer loyalty and measurable cuts in energy and waste; however, improvements are observationally linked to AI-driven insights rather than established through randomized evaluation.openalex | Omosuyi Julius, Surulere provider id |
2026-05-04 | 0 |
Citation observation summary
Semantic Scholar 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.