ISSN 0439-755X
CN 11-1911/B

Acta Psychologica Sinica ›› 2025, Vol. 57 ›› Issue (11): 1914-1932.doi: 10.3724/SP.J.1041.2025.1914

• Reports of Empirical Studies • Previous Articles     Next Articles

When design meets AI: The impact of AI design products on consumers’ response patterns

LI Bin1,2, RUI Jianxi1, YU Weinan1,3, LI Aimei1(), YE Maolin1()   

  1. 1School of Management, Jinan University, Guangzhou 510632, China
    2Research Institute on Brand Innovation and Development of Guangzhou, Guangzhou 510632, China
    3Zhejiang Natural Resources Group Co., Ltd, Hangzhou 31000, China
  • Received:2023-12-31 Published:2025-11-25 Online:2025-09-25
  • Contact: Aimei Li, E-mail: tliaim@jnu.edu.cn;Maolin Ye, E-mail: maolinye@163.com.
  • Supported by:
    Fundamental Research Funds for the Central Universities(23JNQMX11);Ministry of Education Humanities and Social Sciences Research Youth Fund Project(22YJCZH074);Guangdong Philosophy and Social Science Foundation Regular Project(GD22CGL05);National Natural Science Foundation of China(71601084);National Natural Science Foundation of China(71971099);Foundation of Research Institute on Brand Innovation and Development of Guangzhou(22JNZS72)

Abstract:

With the rapid development of Artificial Intelligence (AI) technology, utilizing AI to design products and innovate is a major trend in the future. Based on the stereotype content model, this article explored the effects, mechanisms, and boundary conditions of design source (human vs. AI) and product type (nostalgic vs. innovative) on consumer response patterns (appreciation vs. aversion) through six progressive Studies (N = 1418). The results showed that for nostalgic products, consumers preferred human design, showing AI aversion; for innovative products, consumers preferred AI design, showing AI appreciation, which produced a matching effect of “human design-nostalgic products” and “AI design-innovative products”. Further analysis revealed that processing fluency played a mediating role in this matching effect process; warmth perception and competence perception were key factors that led to processing fluency. In addition, the AI-human collaborative design mode, AI anthropomorphic features, and consumer self-construction types all played a moderating role. This article not only revealed the response patterns and deep mechanisms of consumers' appreciation or aversion towards different types of products designed by AI but also provided references for strategic planning and marketing strategies of AI+ design in the new era of artificial intelligence.

Key words: artificial intelligence, source of design, product types, consumer response patterns, AI aversion or AI appreciation