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:
A5135491591
ORCID evidence
No valid ORCID is stored.
Observed aliases (1)
- Diar Rachmat (openalex, provider refresh)
Topics and outcomes in this view
Assessment themes
- Adoption: 1 paper
- Productivity: 1 paper
Claim outcomes
- Adoption Rate: 1 paper
- Decision Quality: 1 paper
- Governance And Regulation: 1 paper
- Organizational Efficiency: 1 paper
- Other: 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 |
|---|---|---|---|
| AI can materially boost logistics efficiency through better forecasting, routing and inventory decisions, but real-world gains are often limited by high upfront costs, data-security and governance challenges, and organizational resistance to change.openalex | Diar Rachmat provider id |
2026-05-05 | 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.