Evidence map›Paper›PMID 42054300›Full record

ArticlePloS one2026

A game-theoretic analysis of production and coordination under combined carbon policies.

Ao Qiao, Siyu Zeng, Jianing Wang

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
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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

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

3 authors.

Ao QiaoSchool of Logistics, Chengdu University of Information Technology, Chengdu, China.ORCID https://orcid.org/0000-0002-6597-3829
Siyu ZengSchool of Logistics, Chengdu University of Information Technology, Chengdu, China.
Jianing WangSchool of Logistics, Chengdu University of Information Technology, Chengdu, China.ORCID https://orcid.org/0009-0007-2424-1967

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To mitigate the growing threat of global warming, countries have increasingly adopted carbon policies to control industrial carbon emissions. Although previous research has analysed the effectiveness of individual carbon policies, such as cap-and-trade and subsidy schemes, the combined effects of these policies remain largely unexplored. Moreover, existing studies often overlook detailed production processes, such as lot-sizing decisions, which significantly influence total emissions of the manufacturer. To bridge these gaps, this study examines the coordination between a manufacturer and a retailer under a combined carbon policy framework, incorporating both cap-and-trade and low-carbon subsidy policies. A Stackelberg game model is developed to explore the strategic decisions of supply chain members. The manufacturer's production process is modelled using queuing theory to capture the impact of operational details on carbon emissions. Supply chain scenarios are compared and analysed under different combinations of carbon policies and contractual arrangements. The results demonstrate that a combined carbon policy can enhance both profitability and sustainability across the supply chain. Among subsidy schemes, the green investment subsidy is more effective than product subsidy in emissions reduction. Additionally, while revenue-sharing contracts yield greater emissions reductions, cost-sharing contracts offer a better balance between economic and environmental objectives. These findings offer practical implications for policymakers and supply chain managers aiming to design integrated strategies that simultaneously achieve profitability and sustainability.

Indexed as

CarbonEnvironmental PolicyGame TheoryGlobal WarmingCarbon

Identifiers

PMID42054300
PMCPMC13127933

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LicenceCC BY
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Registered trials

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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.