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
2Unique collaborators
1/1OpenAlex citation coverage
Publication span: 2026. Corpus fetch span: 2026.
Identity provenance
Provider IDs
- Openalex:
A5134683438
ORCID evidence
No valid ORCID is stored.
Observed aliases (2)
- Dony Waluya Firdaus (openalex, provider refresh)
- Dony Waluya Firdaus (openalex, source metadata)
Topics and outcomes in this view
Assessment themes
- Adoption: 1 paper
- Innovation: 1 paper
- Org Design: 1 paper
Claim outcomes
- Adoption Rate: 1 paper
- Decision Quality: 1 paper
- Firm Productivity: 1 paper
- Other: 1 paper
- Organizational Efficiency: 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 |
|---|---|---|---|
| Combining accounting systems with machine learning can turn MSME transaction data into predictive intelligence that supports business-model innovation and organisational agility, offering a pathway to sustainable competitive advantage — but resource, skills and institutional barriers must be addressed and the framework remains untested in the field.openalex | Dony Waluya Firdaus provider id |
2026-07-30 | 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.