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TRUVACE RECORD VERSION
record: TRV-2026-2739
version: 1
kind: certified
reason: Certified into the record
timestamp: 2026-11-12T17:17:03.014962Z
status: published
lens: trace
sector: labor
headline: Meta analytic study of human AI co decision systems and workforce intelligence in enhancing sustainability performance in circular supply chains
dek: Abstract The shift to circular supply chains (CSC) in the context of Industry 4.0 has further driven the adoption of artificial intelligence (AI) for production planning, logistics and sustainability considerations. But an increasing body of evidence suggests that the environmental implications are less a matter of AI adoption and more about how effectively AI complements human judgment and human skills. The paper contributes by introducing a meta-analysis on the function of human–AI co-decision systems and labo…
gain_title: A meta-analysis of 269 empirical studies (2018 to 2025) found human-AI co-decision systems were significantly and positively linked to circular behaviour and better environmental performance in supply chains.
problem_title: The same 269-study meta-analysis found economic gains from human-AI co-decision systems in circular supply chains were rather modest, well below the social sustainability gains, pointing to real trade-offs.
trace_subject: Human-AI co-decision systems in circular supply chains
gain_reading: A meta-analysis of 269 empirical studies (2018 to 2025) found human-AI co-decision systems were significantly and positively linked to circular behaviour and better environmental performance in supply chains.
gain_evidence: robust and positive association with statistical significance between human–AI co-decision systems and the adoption of circular behavior, which ultimately enhances environmental performance
problem_reading: The same 269-study meta-analysis found economic gains from human-AI co-decision systems in circular supply chains were rather modest, well below the social sustainability gains, pointing to real trade-offs.
problem_evidence: economic gains are rather modest, proving real-world trade-offs in implementation
quick_read: A meta-analysis of 269 Scopus-indexed empirical studies published from 2018 to 2025 examined how human-AI co-decision systems affect circular supply chains. It found a statistically significant positive association between these systems and circular behaviour, which in turn improved environmental performance.

Workforce intelligence, meaning digital skills, collaborative capability and organisational learning readiness, strengthened these links. Models built on close human-AI collaboration outperformed both AI-dominant models and heavily assistive systems.

Social sustainability outcomes improved the most, while economic gains were rather modest, which the authors describe as real-world trade-offs. They argue the results point to human-centred AI design and workforce readiness as drivers of resilient supply chains.
limitation: The authors note that economic gains were modest and that implementation involves real-world trade-offs, so benefits were uneven across sustainability dimensions.
tag: Dual reading
key_points: The review screened and meta-analysed 269 Scopus-indexed empirical studies published between 2018 and 2025. | It followed the PRISMA-2020 checklist and used a random-effects meta-analytic method. | Human-AI co-decision systems were significantly and positively associated with circular behaviour and environmental performance. | Digital skills, collaborative capability and organisational learning readiness strengthened the relationship. | Closely collaborative human-AI models outperformed AI-dominant and highly assistive systems. | Social sustainability outcomes improved most, while economic gains were modest.
rundown: The study responds to the spread of AI in production planning, logistics and sustainability work within circular supply chains under Industry 4.0. It argues environmental effects depend less on whether firms adopt AI and more on how well AI complements human judgment and skills.

Using a systematic PRISMA-2020 screening of 269 studies and a random-effects meta-analysis, the authors tested whether co-decision systems and workforce intelligence support circular economy practice in production systems.

The results favour designs where humans and AI work closely together over systems dominated by AI or limited to assisting. The gains were largest for social sustainability, with only modest economic returns.
sources:
- peer_reviewed | Discover Sustainability | https://doi.org/10.1007/s43621-026-04157-x | 2026-08-06
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