Matching generative AI word-of-mouth with product type: Impact on consumer adoption and trust

Generative artificial intelligence word-of-mouth (AI WOM), as a new way of information exchange, has become a marketing tool for many e-commerce companies. However, limited attention has been paid to its application scenarios and the adoption of different AI WOM forms in previous studies. This study investigated whether consumers are more likely to adopt AI WOM for utilitarian versus hedonic products when exposed to unidirectional versus interactive forms. It also analyses the psychological processes behind adoption through cognitive and affective dimensions. Four studies were conducted to test the hypotheses. Findings revealed that consumers are more likely to adopt unidirectional AI WOM for utilitarian products and interactive AI WOM for hedonic products. This matching effect is mediated by functional and human-like trust in AI WOM, respectively. Moreover, consumer privacy concerns moderate the matching effect. These findings clarify the conditions under which different types of AI WOM are effective for specific product types and provide theoretical support for companies in selecting appropriate AI WOM strategies based on product characteristics.