Can AI chatbots recover service failures? Exploring user experience and continuance intentions

Saule Yolcu, Alperen Şahin, Aslı Erdoğdu, Taşkın Dirsehan

2026

Full text Open access: Hybrid Metadata (CSL-JSON)
DOI 10.1007/s12525-026-00918-8
Data confidence 70 medium
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Abstract

Abstract Mobile food ordering applications (MFOAs) increasingly use AI-powered chatbots for customer interaction, making the quality of the user experience crucial for adoption and continued use. This study explores how user experience (UX) with MFOA chatbots influences satisfaction and continuance intention. It aims to reveal how both pragmatic (functional) and hedonic (emotional) UX dimensions shape ongoing user engagement with these AI-driven service technologies. A quantitative online survey was administered via Qualtrics between April and May 2025, targeting MFOA chatbot users in Turkey. Participants were recruited using convenience sampling and were screened to ensure prior experience with chatbot-based complaint handling in MFOAs. Data from 227 valid responses were analyzed using PLS-SEM. The results indicate that user experience, comprising both pragmatic and hedonic dimensions, significantly and positively affects satisfaction. Satisfaction fully mediates the relationship between user experience and continuance intention, with no significant direct effect of UX on continuance intention observed, thereby confirming satisfaction’s central role in sustaining post-adoption behavior. This research contributes empirical evidence by integrating UX theory with post-adoption models in the context of AI-enabled service interactions. The findings emphasize the practical necessity for managers and developers to design chatbot experiences that balance functionality and enjoyment, thereby strengthening customer engagement and loyalty in mobile service environments.