The effect of live streaming commerce quality on customers’ purchase intention: extending the elaboration likelihood model with herd behaviour
Qin Yang and
Young-Chan Lee
Behaviour and Information Technology, 2024, vol. 43, issue 5, 907-928
Abstract:
This study examines how technology quality, experience quality, and herd behaviour in live streaming commerce affect customers’ purchase intention. We proposed an integrated research model based on the elaboration likelihood model (ELM) and herd behaviour. This study used covariance-based structural equation modelling (CB-SEM) to analyse data and assess the research model and hypotheses. We surveyed 872 Chinese customers who have experience in live streaming commerce, from which the data of 845 were used to test the hypotheses. Our findings show that good technology and experience quality lead customers to discount their own information and imitate their peers. Customers’ herd behaviour positively affects their purchase intention. Further, discounting own information positively mediates the indirect link between live streaming commerce quality (technology quality and experience quality), imitation, and customers’ purchase intention. This study is the first to combine live streaming commerce quality and herd behaviour to investigate customers’ purchase intention in live streaming commerce. It highlights the value of incorporating herd behaviour into the ELM and adds to the body of knowledge by providing a deeper insight into customers’ purchase intention in live streaming shopping. It also has managerial implications for live streaming commerce practitioners to sever the sustainable growth of e-commerce.
Date: 2024
References: Add references at CitEc
Citations:
Downloads: (external link)
http://hdl.handle.net/10.1080/0144929X.2023.2196355 (text/html)
Access to full text is restricted to subscribers.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:taf:tbitxx:v:43:y:2024:i:5:p:907-928
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/tbit20
DOI: 10.1080/0144929X.2023.2196355
Access Statistics for this article
Behaviour and Information Technology is currently edited by Dr Panos P Markopoulos
More articles in Behaviour and Information Technology from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().