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How livestreaming increases product sales

Role of trust transfer and elaboration likelihood model

Bibliographic Data

ID21452972
AuthorsChun-Der Chen (0000-0002-2840-984X, Ming Chuan University), Qun Zhao (0000-0002-2082-4192, Ningbo University, corresponding author), Jin-Long Wang (0000-0001-9240-5600, Ming Chuan University)
Year2022
Volume41
Issue3
Pages558-573
Publication date2022-02-17
Peer ReviewedYes
Open AccessNo
TypeARTICLE
VenueBehaviour and Information Technology (JOURNAL)
Journal identifiersISSN: 0144-929X • E-ISSN: 1362-3001
PublisherInforma UK Limited (PUBLISHER • GB)
DOI10.1080/0144929x.2020.1827457
OpenAlexW3091504604
LanguageEN
Citations received42
References cited59

With the ever-increasing popularity of livestreaming commerce, understanding how livestreaming contributes to online consumption becomes crucial to social commerce. However, studies pertain to livestreaming commerce are still at a nascent stage. Based on the elaboration likelihood model and trust transfer theory, we aim to examine the underlying mechanism of how livestreaming influences consumers’ trust building and purchasing intention. The determinants, process and consequences of trust are discussed. More than 545 experienced livestreaming commerce users participated in this study in China. Our findings show two different routes through which consumers’ trust can be built and affect their purchase intention and willingness to pay more. We also verify the trust transfer effect exists from trust in the streamer to trust in product in livestreaming commerce. We hope this study will bring more insight into trust and the underlying mechanism of how livestreaming increases product sales

Advertising · Affect (linguistics) · Business · Consumption (sociology) · Elaboration likelihood model · Mechanism (biology) · Persuasion · Popularity · Product (mathematics) · Purchasing · Social commerce · Social media · Computer Science · Customer Service Quality and Loyalty · Digital Marketing and Social Media · Marketing · Psychology · Social Psychology · Technology Adoption and User Behaviour

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Unique citing works42
Citations per year8,4
Citation span2021 - 2026 (6)
Citation velocitycurrent
Highly citedNo
Citation typesNeutral: 38

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