Evidence map›Paper›PMID 37520942›Full record

ArticleHeliyon2023

Spatial and temporal evolution of Guangdong tourism economic network structure from the perspective of social networks.

Lijuan Zhang, Azizan Marzuki, Zhenjie Liao, Kaixiong Zhao, Zhihao Huang, Wenfu Chen

Abstract read
In one paragraph

Article in Heliyon, 2023. 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

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

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

6 authors.

Lijuan ZhangSchool of Housing, Building and Planning, Universiti Sains Malaysia, Penang, Malaysia.
Azizan MarzukiSchool of Housing, Building and Planning, Universiti Sains Malaysia, Penang, Malaysia.
Zhenjie LiaoSchool of Management, Guangzhou Huashang College, Guangzhou, China.
Kaixiong ZhaoSchool of Media and Communication, Guangzhou Huashang College, Guangzhou, China.
Zhihao HuangSchool of Management, Guangzhou Huashang College, Guangzhou, China.
Wenfu ChenSchool of Management, Guangzhou Huashang College, Guangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study uses social network analysis and modified gravity model methods to empirically analyse the network spatial correlation structure and spatiotemporal development trend of 21 cities in Guangdong Province from 2000 to 2020 based on tourism economic development data. The findings show that, first, Zhuhai has the greatest potential for growth as the centre of the spatial and temporal evolution trend of the network structure of the tourism economy in Guangdong Province, ahead of Shenzhen, Huizhou, Zhaoqing, Zhongshan, Jiangmen and Dongguan. However, Guangzhou, the capital city of Guangdong Province, is experiencing a decline in such influence and development. Second, there is a counter-trend growth in the number of tourism-related economic links among the 21 cities. Although Guangdong's tourism economic network intensity is strong, there is still room for further optimisation. Third, the results of the overall network indicators show that there is a need for further improvement in network density, grade and efficiency to help reduce the relative development gap of the cities' tourism and effectively improve the overall development of Guangdong's tourism economy. Finally, based on the core-periphery structure, this study proposes relevant suggestions for the sustainable development of Guangdong's tourism industry.

Indexed as

Guangdong provinceNetwork space structureSocial networkSpace–time evolutionTourism economy

Identifiers

PMID37520942
PMCPMC10382668

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.