Cognitive-Affective Responses to Algorithmic Service Encounters: A Multi-Theoretical Analysis of AI-Mediated Customer Experience, Brand Relationship Quality, and Satisfaction Dynamics in Vietnam's Digital Marketplace

This research investigates the complex interplay between cognitive-affective responses and algorithmic service encounters in Vietnam's rapidly evolving digital marketplace. Through a multi-theoretical lens integrating service-dominant logic, cognitive appraisal theory, technology acceptance model, and relationship marketing frameworks, this study examines how artificial intelligence (AI) mediated customer experiences influence brand relationship quality and satisfaction. Employing a robust mixed-method approach combining structural equation modeling with partial least squares (PLS-SEM) and fuzzy-set Qualitative Comparative Analysis (fsQCA), data from 387 Vietnamese digital consumers were analyzed. Results reveal that algorithmic service personalization significantly enhances cognitive-affective customer experiences, which subsequently strengthen brand relationship quality and satisfaction. Technology readiness moderates these relationships, with higher levels amplifying positive effects of AI-mediated experiences. The fsQCA findings identify multiple configurations of conditions leading to high satisfaction, demonstrating equifinality in satisfaction formation. This research contributes to the literature by developing an integrated theoretical framework explicating the psychological mechanisms through which algorithmic service encounters shape customer outcomes, offering nuanced insights into the digital transformation of service experiences in emerging markets, and identifying optimal configurations for enhancing customer satisfaction in technology-mediated environments.