聊天机器人
拥挤
情境伦理学
心理学
产品(数学)
社会化媒体
社会心理学
计算机科学
认知心理学
万维网
几何学
数学
作者
Jiaji Zhu,Yushi Jiang,Xiaoxuan Wang,Suying Huang
出处
期刊:Journal of Research in Interactive Marketing
[Emerald (MCB UP)]
日期:2023-08-30
卷期号:17 (5): 641-662
被引量:1
标识
DOI:10.1108/jrim-01-2022-0007
摘要
Purpose Driven by artificial intelligence technology, chatbots have begun to play an important customer service role in the online retail environment. This study aims to explore how conversational styles improve the interaction experience between consumers and chatbots in different social crowding environments, and the moderating role of product categories is considered. Design/methodology/approach Three studies are conducted to understand the influences of conversational styles, social crowding and product categories on consumer acceptance, assessed using situational experiments and questions. Findings In a low social crowding environment, consumers prefer chatbots with a social-oriented (vs. task-oriented) conversational style, while in a high social crowding environment, consumers prefer a task-oriented (vs. social-oriented) conversational style, and warmth and competence mediate these effects. The moderating effect of product categories is supported. Originality/value This study expands the application of the stereotype content model to improve the interaction experience level between consumers and chatbots in online retail. The findings can provide managerial suggestions for retailers to select a chatbot's conversational style and promote a more continuous interaction between consumers and chatbots.
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