产品(数学)
感知
偏爱
创造力
快时尚
服装设计
时尚产业
产品设计
营销
心理学
新产品开发
产品创新
过程(计算)
联合分析
消费者行为
考试(生物学)
产品类别
业务
品牌偏好
抗性(生态学)
计算机科学
知识管理
研究设计
解构(建筑)
作者
Garim Lee,Jung-Keun Kim,Kihyon Kim,Jennifer Yeeun Huh,Jaehyun Park
标识
DOI:10.1108/jfmm-11-2024-0431
摘要
Purpose One of the major barriers to implementing artificial intelligence (AI) in fashion design is possibly higher consumer reluctance to accept AI-designed (vs. human-designed) products. How can brands alleviate the negative responses to AI-designed products? To answer this question, this research tests the role of product innovativeness in determining the levels of consumer resistance to AI designs. Design/methodology/approach The hypotheses were developed based on the literature on algorithm aversion and appreciation, fashion design evaluation, and mind perception theory. To test the hypotheses, we conducted three online experiments using Amazon Mturk through CloudResearch platform. Findings While a general preference for human designs over AI designs was found, the negative attitudes toward AI designs were stronger for low-innovative products but weaker for high-innovative products. This is because, according to the conditional process analysis, participants perceived AI-designed products as less original compared to human-designed products when innovativeness level was low. However, this pattern was not shown when innovativeness level was high. Practical implications The findings show the potential for overcoming aversion to AI-designed fashion products. Brands utilizing AI in design are recommended to aim for highly innovative designs, characterized by deconstruction fashion and avant-garde approaches and emphasize innovativeness values when promoting AI-designed products. Originality/value This research sheds light on how and why consumers' negative responses to AI designs vary depending on the final product design, contributing to the discourse on fashion creativity in the era of generative AI from consumers' perspectives.
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