Informational cues in negative reviews: how valence intensity and linguistic expressions shape restaurant visit intentions

Purpose This study examines how negative valence intensity and linguistic expressions in negative online reviews influence restaurant visit intentions through perceived information diagnosticity and perceived risk. Design/methodology/approach An online experiment using a 2 (negative valence intensity: low vs. high) × 2 (linguistic expressions: emotion-based vs. fact-based) between-subjects design was conducted. Data were analyzed using a series of two-way ANOVAs and PROCESS macro analyses to test the hypothesized effects. Findings High negative valence intensity and fact-based expressions significantly increased perceived information diagnosticity, with linguistic expressions exerting the stronger effect. No interaction was found. Separate serial mediation analyses showed that high negative valence intensity and fact-based expressions increased perceived information diagnosticity, which subsequently increased perceived risk and reduced restaurant visit intentions. Practical implications Restaurant managers should tailor responses to review characteristics, using specific corrective actions for fact-based reviews and empathetic reassurance for emotion-based reviews. Restaurants and review platforms should also provide clear, trustworthy diagnostic cues to reduce consumer uncertainty and perceived risk. Originality/value This study integrates negative valence intensity and linguistic expressions within a cue-driven decision framework and demonstrates that these review characteristics operate as distinct, rather than interactive, informational cues.

Authors

Institutions

Publication Details

Journal
Journal of Hospitality and Tourism Insights
Published
2026-11-04
DOI
https://doi.org/10.1108/jhti-04-2026-0510
Primary Topic
Digital Marketing and Social Media
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Informational cues in negative reviews: how valence intensity and linguistic expressions shape restaurant visit intentions

Sejin Ha, Ah-Min Kwon
Journal of Hospitality and Tourism Insights
Digital Marketing and Social Media
article

Informational cues in negative reviews: how valence intensity and linguistic expressions shape restaurant visit intentions

Sejin Ha, Ah-Min Kwon
article en

Abstract

Purpose This study examines how negative valence intensity and linguistic expressions in negative online reviews influence restaurant visit intentions through perceived information diagnosticity and perceived risk. Design/methodology/approach An online experiment using a 2 (negative valence intensity: low vs. high) × 2 (linguistic expressions: emotion-based vs. fact-based) between-subjects design was conducted. Data were analyzed using a series of two-way ANOVAs and PROCESS macro analyses to test the hypothesized effects. Findings High negative valence intensity and fact-based expressions significantly increased perceived information diagnosticity, with linguistic expressions exerting the stronger effect. No interaction was found. Separate serial mediation analyses showed that high negative valence intensity and fact-based expressions increased perceived information diagnosticity, which subsequently increased perceived risk and reduced restaurant visit intentions. Practical implications Restaurant managers should tailor responses to review characteristics, using specific corrective actions for fact-based reviews and empathetic reassurance for emotion-based reviews. Restaurants and review platforms should also provide clear, trustworthy diagnostic cues to reduce consumer uncertainty and perceived risk. Originality/value This study integrates negative valence intensity and linguistic expressions within a cue-driven decision framework and demonstrates that these review characteristics operate as distinct, rather than interactive, informational cues.

Journal of Hospitality and Tourism Insights
University of Tennessee at Knoxville (US)
Openalex Percentile: Top 8%
Digital Marketing and Social Media
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Laika access coming soon