Evidence map›Paper›PMID 40847111›Full record

ArticleScientific reports2025

Spatiotemporal patterns and drivers of coupling coordination between digital technological innovation and economic resilience in the Yangtze river economic belt.

Libin Guo, Kang Liu

Abstract read
In one paragraph

Article in Scientific reports, 2025. 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

2 authors.

Libin GuoOffice of Research Affairs, Chongqing University of Education, Chongqing, China.
Kang LiuChongqing Digital Economy and Intelligent Governance Research Center, Chongqing, China. lk_ctbu@163.com.

Funding

Chongqing Key Science and Technology Project KJZD-K202301601Chongqing Social Science Planning Major Project 2022ZDSC11
6 · The paper itself

Abstract

The synergistic evolution of digital technological innovation (DTI) and urban economic resilience (UER) has become an inherent requirement for the high-quality development of urban agglomerations. Based on panel data at the prefecture-level city scale from 2011 to 2022, this paper explores the spatiotemporal patterns and driving factors of the coupling coordination between DTI and UER across the three major urban agglomerations in the Yangtze River Economic Belt (YREB). The study yields the following key findings: First, during the study period, the coupling coordination degree between digital innovation and UER experienced a fundamental shift from disorder to coordination, but high-quality coupling coordination has not yet been fully achieved. Second, the spatial distribution of coupling coordination exhibits a clear upstream-downstream gradient, with higher coordination in the upper reaches and lower coordination in the middle and lower reaches, forming a distinct core-periphery structure within each agglomeration. Third, the overall inequality in coupling coordination shows a declining trend, but inter-agglomeration differences remain the primary source of inequality. Finally, economic development, fiscal pressure, innovation capacity, and scientific research support are identified as the key driving factors influencing coupling coordination. Based on these findings, the study recommends: promoting regional collaboration, enhancing fiscal support, and optimizing the spillover effects of core cities to foster more balanced and resilient development across the YREB.

Indexed as

Coupling coordinationDigital technological innovationEconomic resilienceUrban agglomerationsYangtze river economic belt

Identifiers

PMID40847111
PMCPMC12373814

What OpenQuestion holds

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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.