How generative <scp>AI</scp> is (will) change consumer behaviour: Postulating the potential impact and implications for research, practice, and policy

Consumers find it increasingly compelling to immerse themselves in the metaverse, a trend that will likely continue. Although the metaverse has retailing potential, understanding empirically its effects on consumer behavior is still underexplored. Our study investigating consumer interactions in this hyper‐connected shopping environment uses scenario‐based data from 262 consumers and a multimethod quantitative approach to examine the integrative behavioral model, revealing consumer perceptions of metaverse affordances, their impact on self‐efficacy, and the role of trust, immersion, and flow experiences in participation in metaverse shopping platforms. Perceived enjoyment emerges as a critical driver of consumer participation. This study provides convincing empirical evidence of the drivers specific to consumer metaverse experiences, going beyond the current understanding of consumer behavior in the metaverse shopping context, mainly at the conceptual level. The findings provide actionable insights for metaverse practitioners to enhance consumer engagement.

The impact of immersive and flow experiences on consumer participation in hyper‐connected shopping platforms: A metaverse perspective

Zhong,

Hamouda

2024

Exploring AI technology and consumer behavior in retail interactions

Petrescu,

Krishen,

Gironda

et al. 2024

This research systematically reviews artificial intelligence (AI) effects in customer‐interfacing retail applications based on an ecosystem value co‐creation framework. We conduct a bibliometric and conceptual mapping analysis study, focusing on AI‐related implications for consumers' and other stakeholders' well‐being, social interaction, and societal welfare. A co‐citation network visualization of critical AI journal articles is generated, and a network visualization of AI keyword relationships and clustered topic areas is presented and discussed, along with a conceptual map of the relationships between key concepts and substantive AI themes. In an ecosystem context, the multidisciplinary‐based bibliometric and conceptual mapping findings of our analysis reflect the need to focus not only on the positive and negative effects on stakeholder well‐being, social interaction, and societal welfare but also on how effects created in one of these levels impact the value created in the other social layers. Furthermore, the interdisciplinary characteristics necessary in effectively implementing and managing AI technologies emphasize the need for collaboration among multiple organizational departments, technology partners, and other members of the business ecosystem. The findings of this research contribute to assessing both the positive and negative effects of AI and allow for its implementation in a way that is helpful to organizations, employees, consumers, and society. This study should also help managers decide which situations are best suited for using AI and which are not.

Enhancing Trust and Empathy in Marketing: Strategic AI and Human Influencer Selection for Optimized Content Persuasion

Zhang,

Zhu,

Chen

et al. 2024

Compared to human influencers, AI influencers offer advantages such as low cost, high efficiency, and fairer handling of objective tasks. However, they are believed to have shortcomings in perception and empathy abilities. How can companies select the more appropriate promoter between AI influencers and human influencers based on their marketing content? How can enterprises design more persuasive marketing content according to the type of influencer? Three behavioral experiments were conducted in this paper. The results indicate that when AI influencers post marketing content with functional advertising appeal, they can significantly enhance people's perceived trust. When human influencers share marketing content with experiential advertising appeal, they can significantly improve people's perceived empathy. Consumers with lower levels of knowledge are more susceptible to the matching effect of influencer type and advertising appeal type on the persuasive effect of marketing content than those with higher levels of knowledge. The conclusions of this study assist enterprises in scientifically matching influencer types with advertising appeals. By choosing influencers based on the nature of the marketing content or designing suitable marketing content based on the influencer type, companies can maximize marketing effectiveness. This refined marketing strategy not only improves the persuasive effect of the marketing content but also strengthens the brand's market competitiveness.