Evidence map›Paper›PMID 40198691›Full record

ArticlePloS one2025

The impact pathway of new quality productive forces on regional green technology innovation: A spatial mediation effect based on intellectual property protection.

Kun Cheng, Jianhui Yin, Feiyan Wang, Min 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. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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

4 authors.

Kun ChengThe 43rd Research Institute of China Electronics Technology Group Corporation, Hefei, China.
Jianhui YinEast University of Heilongjiang, Harbin, China.ORCID https://orcid.org/0009-0007-9566-3737
Feiyan WangAnhui Business and Technology College, Hefei, China.
Min WangAnhui Business and Technology College, Hefei, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Against the backdrop of global economic transformation and sustainable development, green technological innovation has become a core driver for enhancing national competitiveness and addressing environmental challenges. With the profound changes in production methods and technological innovation, new quality productive forces (NQPF) have emerged as a key driver of green technological innovation. This study aims to explore the mechanisms through which NQPF influence Regional Green Technology Innovation (RGTI), with a particular focus on the mediating role of intellectual property protection (IPP). Using panel data from 31 provinces in China from 2011 to 2022, we conduct an empirical analysis employing a spatial Durbin model and a spatial mediation effect model. The results indicate that NQPF significantly promote RGTI, particularly in enhancing resource utilization efficiency and greening production processes. However, the study also identifies an inverted U-shaped relationship between NQPF and green technological innovation, primarily driven by local dynamics, where the positive effect diminishes after reaching a certain threshold. Further analysis reveals that IPP plays a crucial mediating role, not only directly fostering green innovation but also amplifying the positive effects of NQPF by enhancing the efficiency of innovation outcomes. Based on these findings, this study offers policy recommendations for promoting RGTI, emphasizing the need to strengthen support for NQPF, improve IPP mechanisms, and build a regional collaborative innovation system.

Indexed as

Intellectual PropertyInventionsSustainable DevelopmentTechnologyChinaConservation of Natural ResourcesHumans

Identifiers

PMID40198691
PMCPMC11978015

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.