Citation

Tan, Su-Mae and Liew, Tze Wei (2022) Multi-Chatbot or Single-Chatbot? The Effects of M-Commerce Chatbot Interface on Source Credibility, Social Presence, Trust, and Purchase Intention. Human Behavior and Emerging Technologies, 2022. pp. 1-14. ISSN 2578-1863

Text 2501538.pdf - Published Version Restricted to Repository staff only Download (1MB)

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.

Item Type:	Article
Uncontrolled Keywords:	Chatbots, artificial intelligence, natural language processing technology
Subjects:	H Social Sciences > HF Commerce
Divisions:	Faculty of Business (FOB) Faculty of Information Science and Technology (FIST)
Depositing User:	Ms Nurul Iqtiani Ahmad
Date Deposited:	25 Nov 2022 02:24
Last Modified:	25 Nov 2022 02:24
URII:	http://shdl.mmu.edu.my/id/eprint/10204

Downloads

Edit (login required)