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.
Highlights
Chatbots are computer programs that utilize text-based dialogue systems to simulate conversational engagement with humans [1,2,3]
Drawing on the literature review, the dependent variables of this study are perceived agent expertise, m-commerce trusting beliefs, intention to purchase through the mcommerce platform, and perceived social presence in the m-commerce platform
This study revealed that participants attributed a stronger sense of social presence and trusting beliefs toward the mcommerce platform when engaging with the single-chatbot interface than the multi-chatbot interface
Summary
Chatbots are computer programs that utilize text-based dialogue systems to simulate conversational engagement with humans [1,2,3]. Chatbots have been deployed to perform various functions, including taking product orders from customers, providing answers to frequently asked questions, and dispensing product recommendations across m-commerce domains such as food (Pizza Hut), apparel (Zalora), travels (Malaysia Airlines), banking services (Bank of America), and multicategorical products (eBay). Some of the popular product recommender chatbot agents implemented in mobile messaging applications are eBay ShopBot, Chatbot Sephora, Chatbot Castorama, and Chatbot H&M. These chatbots simulate the role of a product advisor by first asking a series of questions to users about their preferences, followed by offering personalized product recommendations based on users’ responses
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