Multi-Chatbot or Single-Chatbot? The Effects of M-Commerce Chatbot Interface on Source Credibility, Social Presence, Trust, and Purchase Intention

Abstract

Most chatbot interfaces in contemporary m-commerce platforms feature a single chatbot that provides recommendations for all product categories. Nonetheless, there is an emerging research interest in multi-chatbot systems designating multiple chatbots as product/domain-specific advisers. Given the dearth of studies investigating the effects of multi-chatbot versus single-chatbot in the m-commerce context, we addressed this research gap by conducting an online between-subjects experiment to explore how the m-commerce chatbot interface types can differently influence source credibility, social presence, trusting beliefs, and purchase intention. Based on 154 valid responses, the single-chatbot interface led to higher social presence and trusting beliefs toward the m-commerce platform than the multi-chatbot interface. Males attributed the chatbot with higher competence and reported higher purchase intention through the m-commerce platform when engaging with the single-chatbot interface than the multi-chatbot interface. These findings suggest that designating chatbots as product-specific advisers in a multi-chatbot interface without labels to accentuate expertise could not evoke the users to categorize them as product specialists. Moreover, the multi-chatbot interface could have imposed user confusion and unfamiliarity cues, decreasing trust in the m-commerce platform. These findings’ theoretical, design, and managerial implications are discussed through the lens of the computers-are-social-actors paradigm, source credibility theory, source specialization, multiple source effect, and m-commerce behavioral research.