The Indirect Influence of Authenticity: How Streamers’ Dialect Use Shapes Viewers’ Behavior Intentions

This study investigates the impact of streamers using dialects in tourism live streaming on viewers’ behavioral intentions, perceived streamer authenticity, and destination authenticity. Through two independent experiments, the study verified the role of dialects in enhancing viewers’ behavioral intentions and uncovered the underlying mediation mechanisms. The findings revealed that streamers using local dialects more effectively strengthen viewers’ behavioral intentions ( M Dialect = 5.278, M Mandarin = 5.014, t (143) = 2.946, p = .004; M Dialect = 5.490, M Mandarin = 5.167, F (1, 90) = 2.527, p = .012) and their perceptions of authenticity regarding both the streamer ( M Dialect = 5.916, M Mandarin = 4.757, F (1, 90) = 8.726, p < .001) and the destination ( M Dialect = 5.927, M Mandarin = 5.423, F (1, 90) = 4.189, p < .001) compared to those using Mandarin. Furthermore, the perception of streamer authenticity was found to be a critical factor influencing viewers’ behavioral intentions (indirect effect = 0.2203; 95% CI [0.0860, 0.3772]), whereas the mediating effect of perceived destination authenticity was not significant (indirect effect = −0.1245; 95% CI [−0.2752, 0.015]). The study also found that the use of dialect by streamers first enhances the perception of streamer authenticity, which in turn boosts viewers’ perception of destination authenticity (indirect effect = 0.4565; 95% CI [0.2433, 0.7137]). This research offers actionable insights for tourism marketing strategies to maximize authenticity perceptions through dialect-based streaming.

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Publication Details

Journal
SAGE Open
Published
2025-10-01
DOI
https://doi.org/10.1177/21582440251391240
Citations
1
Primary Topic
Diverse Aspects of Tourism Research
Type
article
Field-Weighted Citation Impact
4.20
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article

The Indirect Influence of Authenticity: How Streamers’ Dialect Use Shapes Viewers’ Behavior Intentions

Lifang Liang, Gang Wu
1 citations
SAGE Open
Diverse Aspects of Tourism Research
4.20
article

The Indirect Influence of Authenticity: How Streamers’ Dialect Use Shapes Viewers’ Behavior Intentions

Lifang Liang, Gang Wu
article en
1 citations

Abstract

This study investigates the impact of streamers using dialects in tourism live streaming on viewers’ behavioral intentions, perceived streamer authenticity, and destination authenticity. Through two independent experiments, the study verified the role of dialects in enhancing viewers’ behavioral intentions and uncovered the underlying mediation mechanisms. The findings revealed that streamers using local dialects more effectively strengthen viewers’ behavioral intentions ( M Dialect = 5.278, M Mandarin = 5.014, t (143) = 2.946, p = .004; M Dialect = 5.490, M Mandarin = 5.167, F (1, 90) = 2.527, p = .012) and their perceptions of authenticity regarding both the streamer ( M Dialect = 5.916, M Mandarin = 4.757, F (1, 90) = 8.726, p < .001) and the destination ( M Dialect = 5.927, M Mandarin = 5.423, F (1, 90) = 4.189, p < .001) compared to those using Mandarin. Furthermore, the perception of streamer authenticity was found to be a critical factor influencing viewers’ behavioral intentions (indirect effect = 0.2203; 95% CI [0.0860, 0.3772]), whereas the mediating effect of perceived destination authenticity was not significant (indirect effect = −0.1245; 95% CI [−0.2752, 0.015]). The study also found that the use of dialect by streamers first enhances the perception of streamer authenticity, which in turn boosts viewers’ perception of destination authenticity (indirect effect = 0.4565; 95% CI [0.2433, 0.7137]). This research offers actionable insights for tourism marketing strategies to maximize authenticity perceptions through dialect-based streaming.

SAGE OpenVol. 15(4)
Jiangsu Normal University (CN), Shanghai Business School (CN)
Openalex Percentile: Top 5%
Diverse Aspects of Tourism Research
4.20
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The Indirect Influence of Authenticity: How Streamers’ Dialect Use Shapes Viewers’ Behavior Intentions — Lifang Liang, Gang Wu · SAGE Open (2025) | TGRS Research Map | TGRS