Evidence map›Paper›PMID 42263083›Full record

ArticlePloS one2026

Embodied intelligence-driven adaptive collaboration in supply chains: A four-dimensional synergy framework and mechanism analysis.

Ziqiao Ding, Hanjiang Lin, Huiying Xu, Xiaolei Zhang, Xinzhong Zhu

Abstract read
In one paragraph

Article in PloS one, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Ziqiao DingZhejiang Key Laboratory of Intelligent Education Technology and Application, Jinhua, China.
Hanjiang LinZhejiang Key Laboratory of Intelligent Education Technology and Application, Jinhua, China.
Huiying XuZhejiang Key Laboratory of Intelligent Education Technology and Application, Jinhua, China.ORCID https://orcid.org/0000-0002-6704-0301
Xiaolei ZhangZhejiang Key Laboratory of Intelligent Education Technology and Application, Jinhua, China.ORCID https://orcid.org/0009-0002-4069-6201
Xinzhong ZhuZhejiang Key Laboratory of Intelligent Education Technology and Application, Jinhua, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Existing research focuses on data-driven algorithm optimization but overlooks the embodied nature of supply chains as physical and digital integrated systems, leading to a disconnect between AI and physical collaboration. This study introduces embodied intelligence into supply chain management, transcending the traditional paradigm to propose an adaptive collaboration framework through embodied perception, contextual reasoning, and physical execution. It deconstructs the core of supply chain embodied intelligence, revealing issues such as fragmented perception and delayed feedback. Based on embodied cognition and complex adaptive systems theory, a four-layer architecture with embodied perception, contextual reasoning, physical execution, and closed-loop feedback is constructed, clarifying its mechanisms. Future directions in theory, technology, and practice are outlined. This work deepens the integration of embodied intelligence with supply chains, bridges the digital and physical divide, and advances supply chain management toward an embodied adaptive paradigm for next-generation intelligent systems.

Indexed as

Artificial IntelligenceCooperative BehaviorAlgorithmsHumansIntelligent Systems

Identifiers

PMID42263083
PMCPMC13249223

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.