Evidence map›Paper›PMID 41160535›Full record

ArticlePloS one2025

The impact of urban low-carbon incentive policy on enterprise transformation and upgrading: Evidence from a quasi-natural experiment in China.

Yuanrui He, Mingzeng Yang

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. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
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

2 authors.

Yuanrui HeSchool of Accountancy, Shandong University of Finance and Economics, Jinan, Shandong, China.ORCID https://orcid.org/0009-0008-3142-6668
Mingzeng YangSchool of Accountancy, Shandong University of Finance and Economics, Jinan, Shandong, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

As carbon emissions in China continue to rise and the cost advantage in the global value chain diminishes, enterprise transformation and upgrading has emerged as a new engine for economic growth. By implementing low carbon incentive policies, the government aims to spur corporate self‑innovation and phase out obsolete capacity, thereby boosting resource use efficiency and curbing environmental pollution. This paper examines the impact of China's low carbon incentive policies on enterprise transformation and upgrading, with a particular focus on the role and mechanisms of urban environmental policy in this process. Employing a multi-period difference in differences approach, we analyze how the low carbon city policy affects the transformation and upgrading of Chinese listed firms. The results show that the low carbon city policy significantly enhances enterprise transformation and upgrading at the 1% level: participation in the low carbon city policy raises the composite index of enterprise transformation and upgrading by 0.012. We further explore the moderating role of enterprise green development level by incorporating it into our model of low carbon city policy effects. The findings reveal that firms exhibiting higher green total factor productivity, as well as those adopting green innovation and green management practices, display stronger adaptability to the low carbon city policy. Finally, both heterogeneity and dynamic analyses indicate that, over the medium to long term, the low carbon city policy continues to promote enterprise transformation and upgrading. In sum, the low carbon city policy not only provides exogenous momentum for enterprise transformation and upgrading but also interacts synergistically with firms' green development to guide them toward more efficient and sustainable transformation and upgrading.

Indexed as

CarbonEnvironmental PolicyChinaCitiesEconomic DevelopmentHumansCarbon

Identifiers

PMID41160535
PMCPMC12571261

What OpenQuestion holds

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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.