Evidence map›Paper›PMID 40097540›Full record

ArticleScientific reports2025

Exploring the relationship between the tourist behavior and the spatial characteristics for rural tourism.

Ka Li, YiNa Zou, Hao Wang, Shuolei Chen

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. 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.

Ka LiCollege of Landscape Architecture, Nanjing Forestry University, Nanjing, 210037, China.
YiNa ZouCollege of Landscape Architecture, Nanjing Forestry University, Nanjing, 210037, China.
Hao WangCollege of Landscape Architecture, Nanjing Forestry University, Nanjing, 210037, China.
Shuolei ChenCollege of Landscape Architecture, Nanjing Forestry University, Nanjing, 210037, China. shuoleichen@njfu.edu.cn.

Funding

National Key Research and Development Program of China 2019YFD1100404National Natural Science Foundation of China 52308066Natural Science Youth Foundation of Jiangsu Province BK20230401
6 · The paper itself

Abstract

With global urbanization, rural tourism has become a thriving trend for urban-rural sustainable development in addition to the urban landscape. However, research on rural landscape planning is still lacking. The topography of the rural areas is complex, with mountains and buildings arranged in accordance with the terrain, and pedestrian data is difficult to collect. Therefore, this study adopts mixed methods to obtain high-precision data. This study aims to investigate the relationships between tourist behavior and spatial characteristics. The results indicated that (1) Different rural spaces formed an uneven distribution of tourists' spatial-temporal behavior characteristics, which could be attributed to three potential factors: easy space accessibility, good visual permeability, and herd mentality; (2) Visual space had a strong influence on guiding tourists compared to the passable space; (3) Historical trees, heritage buildings and cultural legacy are the positive influencing cultural factors for tourist attraction in spaces. Furthermore, these findings provided rationales to mobilize the utilization of the rural landscape resources and enhance the sustainable urban-rural development. These findings and methods improve our understanding of the temporal-spatial tourist behavior in rural tourism, which is of great significance for rural tourism planning and cultural legacy protection.

Indexed as

Rural PopulationTourismHumansTravelUrbanizationCultural legacyRural tourismSpatial characteristicSustainable urban and rural developmentTourist behaviorUAV

Identifiers

PMID40097540
PMCPMC11914689

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.