Evidence map›Paper›PMID 40743253›Full record

ArticlePloS one2025

Does an improved HDI trigger tourism outflows for China? New evidence from the ARDL cointegration approach.

Ahsan Akbar, Farrukh Nawaz, Xie Hui, Irfan Ullah, Minhas Akbar, Veronika Zidova, Asokan Vasudevan

Abstract read
In one paragraph

Article in PloS one, 2025. 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

5 · Who and what money

Authors and funding

7 authors.

Ahsan AkbarInternational Business School, Guangzhou City University of Technology, Guangzhou, China.
Farrukh NawazFaculty of Business Studies, Arab Open University, Riyadh, Saudi Arabia.
Xie HuiSchool of Jewelry, Guangzhou City University of Technology, Guangzhou, China.ORCID https://orcid.org/0009-0000-0440-8837
Irfan UllahReading Academy, Nanjing University of Information Science and Technology, Nanjing, People's Republic of China.
Minhas AkbarDepartment of Recreology and Tourism, Faculty of Informatics and Management, University of Hradec Kralove, Hradec Kralove, Czechia.ORCID https://orcid.org/0000-0002-6639-0553
Veronika ZidovaDepartment of Recreology and Tourism, Faculty of Informatics and Management, University of Hradec Kralove, Hradec Kralove, Czechia.
Asokan VasudevanFaculty of Business and Communications, INTI International University, Nilai, Negeri Sembilan, Malaysia.ORCID https://orcid.org/0000-0002-9866-4045

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Extant studies have predominantly focused on understanding the effects of inbound tourism on economic growth. At the same time, it ignores the key factors that promote outbound tourism in a country. Outbound tourism not only plays a crucial role in the sustainable development of the host country but also helps foster an understanding of cross-cultural similarities and differences, promoting goodwill towards the home country. It also provides an opportunity to experience the cuisine, weather, and working habits of different geographical locations. Therefore, this study aims to investigate the relationship between the Human Development Index and tourism outflows in the context of China. We use data from the period 1995-2020 to estimate the relationship between the Human Development Index (HDI) and tourism outflows. The short-run and long-run Autoregressive Distributed Lag (ARDL) results indicate that improving China's Human Development Index (HDI) has a positive impact on tourism outflows. More precisely, a 1 unit increase in the HDI index will increase tourism outflow by 5.25%. Furthermore, the results of individual HDI show that life expectancy, per capita income, and education considerably promote China's tourism outflows. Policy prescriptions are outlined regarding the spillover effects of China's human development on the tourism-led economic growth of recipient countries.

Indexed as

TourismChinaEconomic DevelopmentHumansIncomeLife Expectancy

Identifiers

PMID40743253
PMCPMC12312959

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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.