Evidence map›Paper›PMID 40455738›Full record

ArticlePloS one2025

Resilience factors and mechanisms in the coal power supply chain: A quantitative analysis using fuzzy DEMATEL, ISM, and ANP methods.

Yingchen Wang, Mingkang Li, Linlin Sun, Jiaqing Liu, Yiran Wang

Abstract read
In one paragraph

Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

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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

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0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Yingchen WangSchool of Management Engineering and Business, Hebei University of Engineering, Handan, Hebei Province, China.
Mingkang LiSchool of Management Engineering and Business, Hebei University of Engineering, Handan, Hebei Province, China.
Linlin SunSchool of Management Engineering and Business, Hebei University of Engineering, Handan, Hebei Province, China.ORCID https://orcid.org/0009-0002-1155-3957
Jiaqing LiuSchool of Management Engineering and Business, Hebei University of Engineering, Handan, Hebei Province, China.
Yiran WangSchool of Management Engineering and Business, Hebei University of Engineering, Handan, Hebei Province, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Under the influence of global energy market fluctuations, policy changes, and natural disasters, the coal power supply chain faces significant risks. However, existing research on supply chain resilience management, particularly regarding the identification and quantitative analysis of resilience factors in the coal power supply chain, remains insufficient. Therefore, this study aims to identify the key factors influencing the resilience of the coal power supply chain and analyze the mechanisms of interaction between these factors. This study first conducted a literature review to identify 20 factors classified into three dimensions: adaptive capacity, restorative capacity, and absorptive capacity. Secondly, an innovative approach integrating fuzzy DEMATEL, ISM, and ANP was introduced to systematically identify the key influencing factors of coal power supply chain resilience and analyze their mechanisms. The results reveal that electricity demand forecasting capability, government intervention and coordination capacity, and technological level of the coal industry are the primary causal factors affecting supply chain resilience, playing critical roles in ensuring supply chain stability and adaptability. Additionally, factors such as risk prevention and maintenance level and information transmission efficiency also serve as important supporting elements. This research constructs a cause-degree-centeredness diagram and a hierarchical model for coal power supply chain resilience, providing theoretical support and practical recommendations for optimizing the supply chain structure and enhancing the capacity to cope with uncertainties in the coal power industry.

Indexed as

CoalPower PlantsFuzzy LogicHumansModels, TheoreticalCoal

Identifiers

PMID40455738
PMCPMC12129186

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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.