Understanding the drivers of customers' continuance intention to use AI chatbots in e-commerce
Year: 2025
Type: article
Study design: Observational Study
Abstract: The e-commerce experience has been transformed by artificial intelligence, which has also opened new avenues for customer communication through chatbots. This study aims to examine how chatbot characteristics influence continuance intention in e-commerce. Specifically, it explores how interactivity, compatibility, information quality, and service quality affect users' perceptions of chatbot usefulness and enjoyment. A quantitative approach using Partial Least Squares Structural Equation Modeling (PLS-SEM) was employed for data analysis. The main findings reveal that (i) information quality and service quality positively influence both perceived usefulness and perceived enjoyment of chatbots, which in turn enhance continuance intention; (ii) compatibility positively affects perceived enjoyment but not perceived usefulness; and (iii) interactivity moderates the relationship between information quality and both perceived usefulness and enjoyment. This study extends the Technology Acceptance Model by incorporating service-related and interactive factors, contributing to the growing body of knowledge on consumer behavior and technology adoption in e-commerce. The findings offer valuable insights for chatbot designers, managers, and customer service practitioners.
Author: Quang Huy Trần
Institution: I-Shou University
Language: English
Topic: AI in Service Interactions
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $129
OpenAlex ID: W4413232375