Evidence map›Paper›PMID 40989219›Full record

ArticleJournal of eye movement research2025

How Visual Style Shapes Tourism Advertising Effectiveness: Eye-Tracking Insights into Traditional and Modern Chinese Ink Paintings.

Fulong Liu, Xiheng Shao, Zhengwei Tao, Nurul Hanim Md Romainoor, Mohammad Khizal Mohamed Saat

Abstract read
In one paragraph

Article in Journal of eye movement research, 2025. 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

5 authors.

Fulong LiuSchool of Arts, Universiti Sains Malaysia, Gelugor 11700, Malaysiahanim.romainoor@usm.my (N.H.M.R.).
Xiheng ShaoCentre for Instructional Technology and Multimedia, Universiti Sains Malaysia, Gelugor 11700, Malaysia; shaoshao@student.usm.my.
Zhengwei TaoSchool of Fine Arts and Design, Hechi University, Hechi 546300, China.
Nurul Hanim Md RomainoorSchool of Arts, Universiti Sains Malaysia, Gelugor 11700, Malaysiahanim.romainoor@usm.my (N.H.M.R.).ORCID https://orcid.org/0000-0003-4482-1364
Mohammad Khizal Mohamed SaatSchool of Arts, Universiti Sains Malaysia, Gelugor 11700, Malaysiahanim.romainoor@usm.my (N.H.M.R.).

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study investigates how traditional versus modern Chinese ink painting styles in tourism advertisements affect viewers' visual attention, aesthetic evaluations, and tourism intentions. Using eye-tracking experiments combined with surveys and interviews, the researchers conducted a mixed-design experiment with 80 Chinese college students. Results indicate that traditional ink-style advertisements attracted longer total fixation durations, higher aesthetic evaluations, and stronger cultural resonance in natural landscape contexts, while modern ink-style advertisements captured initial attention more quickly and performed better aesthetically in urban settings. Qualitative analyses further revealed cultural familiarity and aesthetic resonance underpinning preferences for traditional style, whereas modern style mainly attracted attention through novelty and creativity. These findings expand Cultural Schema Theory and the aesthetic processing model within advertising research, suggesting practical strategies for tourism advertising to match visual styles appropriately with destination types and audience characteristics to enhance promotional effectiveness.

Indexed as

advertisingaesthetic evaluationeye movementtourism intentiontraditional Chinese painting

Identifiers

PMID40989219
PMCPMC12452646

What OpenQuestion holds

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LicenceCC BY
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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.