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http://bura.brunel.ac.uk/handle/2438/30307
Title: | Machines vs. humans: The evolving role of artificial intelligence in livestreaming e-commerce |
Authors: | Yuan, H Lü, K Fang, W |
Keywords: | AI;consumption type;viewer engagement;live streaming e-commerce;TVEM |
Issue Date: | 25-Nov-2024 |
Publisher: | Elsevier |
Citation: | Yuan, H., Lü, K. and Fang, W. (2025) 'Machines vs. humans: The evolving role of artificial intelligence in livestreaming e-commerce', Journal of Business Research, 2024, 188 (February 2025), 115077, pp. 1 - 16. doi: 10.1016/j.jbusres.2024.115077. |
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. |
Description: | Data availability: Data will be made available on request. |
URI: | https://bura.brunel.ac.uk/handle/2438/30307 |
DOI: | https://doi.org/10.1016/j.jbusres.2024.115077 |
ISSN: | 0148-2963 |
Other Identifiers: | ORCiD: Kevin Lü https://orcid.org/0000-0002-2588-9059 115077 |
Appears in Collections: | Brunel Business School Research Papers |
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FullText.pdf | Copyright © 2024 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY license ( https://creativecommons.org/licenses/by/4.0/ ). | 2.02 MB | Adobe PDF | View/Open |
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