Evidence map›Paper›PMID 38352753›Full record

ArticleHeliyon2024

Revisiting tourism in the post-pandemic era: An evaluation study of China's 5A-Class scenic spots.

Hanqing Hu, Hao Lu

Open access · goldAbstract read
In one paragraph

Article in Heliyon, 2024. 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
10.2field-weighted citation impact, top 2% of its field
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, 9 citations in OpenAlex.

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 at 1 institution in 1 country.

Hanqing HuSchool of Economics and Management, Beijing Information Science & Technology University, Beijing, 10092, China.
Hao LuSchool of Economics and Management, Beijing Information Science & Technology University, Beijing, 10092, China.
Beijing Information Science & Technology University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The emergence of the COVID-19 in 2019 has unquestionably had a profound and transformative effect on the tourism industry. Following the easing of COVID-19 prevention and control measures in China, there has been a significant increase in travel demand. Representing the epitome of excellence in Chinese scenic spots, 5A-class scenic areas are primary destinations for travelers. The assessment of these scenic spots plays a crucial role in shaping their tourism reputation. Currently, there is a regional focus in research on the evaluation of 5A-class scenic spots exhibits regional characteristics, with limited attention given to a nationwide assessment. In this study, we collected over 410,000 online comments were gathered from 256 scenic spots classified as 5A-class. Employing the Latent Dirichlet Allocation (LDA) topic model, this study conducted a thematic exploration and applied Grounded Theory for qualitative analysis of evaluation themes. This study focused on analyzing scenic spot evaluations by examining three dimensions: the scenic spot itself, the surrounding facilities, and the perspective of tourists. Study findings reveal: (1)Tourist evaluations of 5A-class scenic spots by tourists undergo changes from the inception of the journey to its conclusion. (2)Tourist assessments of these scenic spots are not confined solely to the attractions themselves, the quality of peripheral amenities also has a significant impact on their assessments. This study differentiates itself from traditional regional analysis and perceptual image perspective analysis by employing a process-oriented approach from the perspective of the tourist. The utilization of text-mining techniques enables the identification of coexisting universal and regional tourism evaluation indicators. The present study makes a valuable contribution to the existing body of knowledge by providing insights into the intricate nature of the tourist evaluation process and the interrelationships among different factors.

Indexed as

5A-class scenic spotsGrounded theoryLDA topic modelPost-pandemic era

Identifiers

PMID38352753
PMCPMC10861982
OpenAlexW4391474211

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.