ArticlePloS one2025
The impact of travel live streaming on tourists' travel intention on the spot.
Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
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.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The objective of this study is to examine the mechanisms that influence tourists' intentions to travel in the context of live streaming. The utilization of text mining techniques in this research endeavor has yielded two critical dimensions, namely, the characteristics of live streamers and the attributes of live streaming content, as discerned from user comments. The present study proposes a model grounded in the Stimulus-Organism-Response (SOR) theoretical framework. Subsequently, a series of questionnaires were disseminated through various digital platforms, including WeChat, QQ, and TikTok. This endeavor yielded a total of 511 valid responses from audiences within China's travel live streaming sector. Subsequently, structural equation modeling (SEM) was employed to analyze the data. The findings indicate that live streamer characteristics (e.g., professionalism, image, charm), live streaming content characteristics (e.g., tourist destination information), perceived emotional value, and perceived utilitarian value can directly influence tourists' intention to travel on the spot. Furthermore, live streamer characteristics and live streaming content characteristics directly impact perceived emotional value and perceived utilitarian value, and indirectly influence travel intention through double intermediaries.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.