抗性(生态学)
适度
独创性
风格(视觉艺术)
心理学
文字(数理逻辑)
价值(数学)
社会心理学
人工智能
营销
计算机科学
业务
创造力
历史
考古
机器学习
生物
生态学
算法
作者
Yupeng Mou,Yixuan Gong,Zhihua Ding
出处
期刊:Marketing Intelligence & Planning
[Emerald (MCB UP)]
日期:2024-03-27
卷期号:42 (4): 647-665
被引量:1
标识
DOI:10.1108/mip-04-2023-0187
摘要
Purpose Artificial intelligence (AI) is experiencing growth and prosperity worldwide because of its convenience and other benefits. However, AI faces challenges related to consumer resistance. Thus, drawing on the user resistance theory, this study explores factors that influence consumers’ resistance to AI and suggests ways to mitigate this negative influence. Design/methodology/approach This study tested four hypotheses across four studies by conducting lab experiments. Study 1 used a questionnaire to verify the hypothesis that AI’s “substitute” image leads to consumer resistance to AI; Study 2 focused on the role of perceived threat as an underlying driver of resistance to AI. Studies 3–4 provided process evidence by the way of a measured moderator, testing whether AI with servant communication style and literal language style is resisted less. Findings This study showed that AI’s “substitute” image increased users' resistance to AI. This occurs because the substitute image increases consumers’ perceived threat. The study also found that using servant communication and literal language styles in the interaction between AI and consumers can mitigate the negative effects of AI-substituted images. Originality/value This study reveals the mechanism of action between AI image and consumers’ resistance and sheds light on how to choose appropriate image and expression styles for AI products, which is important for lowering consumer resistance to AI.
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