Machines vs. humans: The evolving role of artificial intelligence in livestreaming e-commerce
Haixia Yuan,
Kevin Lü and
Wenting Fang
Journal of Business Research, 2025, vol. 188, issue C
Abstract:
As the capability of artificial intelligence (AI) improves, online retailers are exploring AI-based agents to communicate with viewers in live streaming, which is referred to as AI stremer. However, it is unclear where, what, and when the implementation of AI stremer is more effective than human beings in live-streaming e-commerce. To explore the dynamic interrelationships and temporal evolution between AI and human streamers and viewer engagement, this study examined the evolving role of AI streamers in live-streaming e-commerce. We utilised the linear mixed model (LMM) and the time-varying effect model (TVEM) to examine whether AI and human streamers differ in both monetary and non-monetary engagement activities. Additionally, we investigated how these differences change over time and whether such changes are consistent across different consumption contexts. The dataset consists of 924,036 products from 21,190 live streaming shows in 123 live broadcasting rooms over a period of four months was used in this study. The results suggest that AI streamers can substitute for humans in monetary activities in the context of utilitarian consumption but not in hedonic consumption. However, the substitute effect of AI may gradually diminish over time. In addition, in a hedonic context, AI exhibits an increasing effect on viewer engagement over time.
Keywords: AI; Consumption type; Viewer engagement; Live streaming e-commerce; TVEM (search for similar items in EconPapers)
Date: 2025
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0148296324005812
Full text for ScienceDirect subscribers only
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:eee:jbrese:v:188:y:2025:i:c:s0148296324005812
DOI: 10.1016/j.jbusres.2024.115077
Access Statistics for this article
Journal of Business Research is currently edited by A. G. Woodside
More articles in Journal of Business Research from Elsevier
Bibliographic data for series maintained by Catherine Liu ().