Consumer reactions to AI design: Exploring consumer willingness to pay for AI‐designed products

Abstract

Companies are increasingly using artificial intelligence (AI) technology to generate promising concepts for new products which are then marketed to consumers as "AIdesigned." Drawing on four studies and follow-up studies, this paper explores consumer perceptions of AI design. Based on the information gap model, the studies determine that, compared with professional-designed products, consumers are more willing to pay for products designed by AI, in which process curiosity plays an intermediary role (Study 1). Crucially, this research also predicts the boundary conditions for the positive effects of AI design. High levels of consumer knowledge lead to an attenuation in consumer curiosity regarding AI design, thereby decreasing the willingness to pay (Study 2), while the product type also has a moderating effect on the influence of the product design sources. Consumers are more willing to pay for utilitarian products designed by AI than hedonic products (Study 3). In addition, we reverify that consumers prefer AI-designed products through a field study (Study 4). Finally, the research sheds light on how to utilize AI to promote the success of new product innovation from a marketing perspective, providing important theoretical knowledge and actionable managerial implications for future research.

Me and my AI: Exploring the effects of consumer self‐construal and AI‐based experience on avoiding similarity and willingness to pay

“…Whereas recognition value assesses whether the AI tool provides a sense of uniqueness to consumers, hedonic value captures consumers' internal and subjective responses while interacting with the AI tool. Our findings add to the growing literature on the AI‐consumer experience (e.g., Foroudi et al, 2018; Zhang et al, 2022), indicating that, beyond the importance of the experience's hedonic value, recognition of consumer uniqueness is equally important when interacting with branded AI tools.…”

“…During interactions with AI‐based technology, we expect individuals who express independent self‐construal will focus on extracting experiential value from the AI tool, ultimately displaying more favorable attitudes and behaviors related to what the brand offers (Zhang et al, 2022). As part of our research hypotheses, we discuss this idea in the following section.…”

“…Despite the interest in branded AI tools, extant research on marketing focused on conceptualizing how consumers interact with this technology (e.g., Mariani et al, 2022; van Doorn et al, 2017) and determining at which level AI‐based stimuli affect consumers' experience, attitudes, adoption, satisfaction, and behavior (e.g., Belanche et al, 2019; Flavián et al, 2022; Kim et al, 2021; Zhang et al, 2022).…”

“…In sum, the main contribution of this investigation is the expansion of extant research on AI-human experiences (e.g., Sands et al, 2022;Zhang et al, 2022) by opening a new avenue to deepen our understanding of AI-based technology's capacity to appeal to consumer uniqueness and spending behavior.…”

When cool hospitality brand meets AI: exploring the matching effect of service agents and brand images on brand attitude

“…These AI traits correspond to cool subculture and extraordinariness (Sundar et al , 2014; Warren and Campbell, 2014). Secondly, AI offers unique services, stimulating curiosity (Zhang et al , 2022a) and enhancing coolness (Tiwari et al , 2021). In contrast, human staff are common, lacking novelty.…”