Evidence map›Paper›PMID 36554356›Full record

ArticleInternational journal of environmental research and public health2022

Influence Mechanism of Polycentric Spatial Structure on Urban Land Use Efficiency: A Moderated Mediation Model.

Di Zhu, Yinghong Wang, Shangui Peng, Fenglin Zhang

Abstract read
In one paragraph

Article in International journal of environmental research and public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

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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

Who cites it

1 citing paper in PubMed.

  1. 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.

Di ZhuSchool of Public Policy and Management, China University of Mining and Technology, Xuzhou 221116, China.ORCID 0000-0001-8557-4131
Yinghong WangSchool of Environment Science and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, China.
Shangui PengSchool of Economics and Management, Shandong Agricultural University, Tai' an 271018, China.ORCID 0000-0002-1012-7764
Fenglin ZhangSchool of Public Policy and Management, China University of Mining and Technology, Xuzhou 221116, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Under the background of green development, the spatial structure of urban agglomerations (UA) has an important impact on urban land use efficiency (ULUE), but few studies have explored the impact mechanism between the two. This research explores the impacts of polycentric development on ULUE of UA, using data for 140 cities in China's top ten key UA covering the period from 2004-2019. The linkage between polycentric development and ULUE is explored by estimating models of determinants of ULUE. This research also examines the mechanism of the polycentric spatial structure of UA on ULUE by using a moderated mediation model. The main findings of the research can be concluded as below. The eastern UAs show a mostly polycentric spatial structure, whereas the central and western UAs show a weak polycentric spatial structure. The polycentric spatial structure of UA has a positive impact on ULUE. An inverted U-shape curve depicts the relationship between the polycentric spatial structure of UA and ULUE. However, the mediating variables, integration of industrial structure and factor mobility have a positive and partially mediating effect between the polycentric spatial structure of UA and ULUE. The infrastructure level has a positive U-shaped regulation effect, in which the impact coefficient of transport infrastructure is more significant. These findings provide empirical evidence for the coordinated development of China's regional space planning and ULUE.

Indexed as

EfficiencyUrbanizationChinaCitiesEconomic Developmentmediating effectmoderating effectpolycentric spatial structureSBMurban agglomerationutilization efficiency of urban land

Identifiers

PMID36554356
PMCPMC9779311

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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.