Evidence map›Paper›PMID 41945555›Full record

ArticlePloS one2026

Spatial heterogeneity of the nonlinear impact of built environment on suburban railway commuting willingness: Taking Guiyang Loop Line Railway as an example.

Rufeng Chen, Hang Zhao

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
–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.

Rufeng ChenSchool of Geography & Environmental Science, Guizhou Normal University, Guiyang, Guizhou, China.ORCID https://orcid.org/0009-0005-1128-3434
Hang ZhaoSchool of Geography & Environmental Science, Guizhou Normal University, Guiyang, Guizhou, China.ORCID https://orcid.org/0000-0002-4016-4574

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study takes the Guiyang Loop Line Railway as a case study and, based on resident commuting survey data, applies an XGBoost model combined with Individual Conditional Expectation (ICE) analysis to examine the threshold effects and non-linear spatial characteristics of the built environment on residents' willingness to commute via the Loop Line Railway. The results indicate that: (1) population density, distance to the nearest bus stop, road network density, and distance to the city center are key built environment factors influencing commuting willingness. Among them, population density and road network density exhibit overall positive effects, whereas distance to the nearest bus stop and distance to the city center show negative effects; (2) the spatial distributions of the threshold effect magnitude (Δy) and the non-linear effect intensity (m) display a heterogeneous pattern broadly characterized by a "city center-suburban-peripheral" gradient, suggesting pronounced spatial non-stationarity in the relationship between the built environment and commuting willingness; (3) compared with the central urban area, residents living around suburban and peripheral stations are more sensitive to changes in bus feeder conditions, road network connectivity, and commuting distance, exhibiting stronger threshold effects and non-linear responses. These findings suggest that enhancing residents' willingness to commute via the Loop Line Railway requires context-sensitive strategies that account for the built environment characteristics of different areas, with targeted improvements in bus-rail integration and road network conditions, rather than adopting uniform development and supporting policies across all stations.

Indexed as

Built EnvironmentRailroadsTransportationChinaCitiesHumansPopulation Density

Identifiers

PMID41945555
PMCPMC13056205

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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.