Investigating AI-based service quality in online shopping: a dual lens of perceived value and need for cognition

Purpose Through the lens of expectation confirmation theory (ECT), this study aims to look into and confirm the various dimensions of artificial intelligence (AI)-based service quality in online shopping platforms. It looks at the expectation-based dimensions such as personalized recommendation and human-like empathy, as well as perceived performance aspects such as information quality and technology quality. This study also investigates the mediating role of perceived value and the moderating role of need for cognition (NFC). Design/methodology/approach This study undertakes a descriptive, cross-sectional approach and focuses on online customers. An online survey using purposive and snowball sampling was taken into consideration to get 667 valid replies. Confirmatory factor analysis and CB-SEM were used to check the measurement and structural models. Findings The results indicated the impact of AI-based service quality and perceived value on repurchase intention of customers. Furthermore, perceived value partially mediates the relationship between AI-based service quality and repurchase intention. The analysis further confirmed the moderating role of NFC, demonstrating its impact on the strength of the link between AI-based service quality and repurchase intention. Originality/value This research enhances the ECT by incorporating the AI-based dimensions into the evaluation of service quality in online shopping. The results offer theoretical insights into service quality and online shopping literature as well as practical implications for online retailers seeking to improve customer retention by inducing repurchase intention.