The Effect of Affordance of Online Shopping Chatbot Curation Services on Continuous Usage Intention

Abstract

Purpose: In this paper, we aim to analyze the effects of affordance characteristics of online shopping chatbot curation services on Chinese consumers' social presence and intention to continue using, focusing on the moderating effect of individual innovativeness. Composition/Logic: In this study, a two-step survey was designed. First, the survey was subdivided through a pre-survey that targeted 40 consumers. Second, this was followed by the primary online survey, conducted from April 12th to April 30th, 2023, which yielded 348 valid responses. The study considered demographic factors and focused on three tiers of cities to control for regional variations. Data analysis was conducted using SPSS and AMOS. The research began with examining demographic characteristics and usage trends, assessed reliability and validity, and concluded with structural equation modeling to validate the direct effects between variables. Findings: This study explored the intricate relationship between affordances and social presence in online shopping mall chatbot services. The results of the empirical analysis showed that both practical and relational affordances positively affected cognitive and emotional presence. On the other hand, pleasurable affordance had a positive effect only on emotional presence and had no significant impact on cognitive presence. In addition, individual innovativeness was confirmed to be an important moderating variable that can strengthen the relationship between affordance and social presence. This influence is important for understanding continued usage intentions in online shopping mall chatbot services. Originality/Value: The uniqueness of this study lies in integrating affordance theory with individual innovativeness to explain the ongoing engagement with online shopping chatbots. By demonstrating the moderating effect of individual innovativeness, this research contributes to a more nuanced understanding of user behavior in the rapidly evolving field of online retail technologies.