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From perception to intention

Exploring perceived value in Chinese-language podcast platforms

Bibliographic Data

ID21790205
AuthorsJiangtao Pan (Shandong University), Jie Xin (0000-0002-7084-6103, Shandong University), Zhiyuan Yu (0000-0002-2178-6423, Shandong University), Wan Ni (0000-0002-8456-6559, Shandong University, corresponding author)
Year2026
Volume19
Issue1
Pages20-37
Publication date2026-01-02
Peer ReviewedYes
Open AccessNo
TypeARTICLE
VenueChinese Journal of Communication (JOURNAL)
Journal identifiersISSN: 1754-4769 • E-ISSN: 1754-4750
PublisherInforma UK Limited (PUBLISHER • GB)
DOI10.1080/17544750.2025.2467970
OpenAlexW4408109936
LanguageEN
References cited56

In recent years, podcasts have become an integral part of daily life for many individuals. However, a significant gap remains in our understanding of the usage intentions of Chinese-language podcast users. Utilizing a mixed-method approach, this research addressed this gap by applying the value-based adoption model of technology (VAM) to explore the factors that influence these intentions. A comprehensive model was developed through qualitative exploration and then tested using structural equation modeling (SEM) with data from 753 survey responses. Notably, this research extended the VAM framework by introducing “perceived concomitance” as an antecedent variable and “past behavior” as a moderating variable. The findings revealed that perceived usefulness, enjoyment, ease of use, and concomitance positively influenced perceived value and usage intention among users. For nonusers, social influence played a significant role in shaping perceived value and usage intention. In both groups, perceived value partially mediated these effects. Additionally, past behavior negatively moderated the relationship between perceived value and usage intention, indicating that platform migration requires changes in audio listening habits. This research enriches our understanding of user intentions on Chinese-language podcast platforms and provides strategic insights for the future development of the podcast industry

Perception · Computer Science · Digital Marketing and Social Media · Psychology · Radio, Podcasts, and Digital Media · Technology Adoption and User Behaviour

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