This study investigated the impact of Generative AI (GenAI) applications in after-sales services on customer repurchase behavior, using the Stimulus-Organism-Response (SOR) model and customer pleasure as a mediating variable. The background context highlighted the growing adoption of GenAI in customer service and its potential to enhance customer satisfaction and loyalty. The study aimed to examine how personalization, anthropomorphism, and privacy concerns—key features of GenAI—stimulate emotional engagement and drive repurchase intentions. A quantitative approach was employed, utilizing Partial Least Squares Structural Equation Modeling (PLS-SEM) to analyze survey data collected from 437 customers in Vietnam who interacted with GenAI-driven after-sales services. The results revealed that personalization and anthropomorphism significantly enhanced customer pleasure, which mediated their effect on repurchase intentions. Privacy concerns also influenced customer pleasure positively when managed transparently. The findings confirmed the applicability of the SOR model in understanding customer behavior in AI-mediated services. It was concluded that businesses could leverage GenAI to foster emotional engagement, balancing personalization with privacy and incorporating human-like AI features to optimize after-sales interactions. This study contributes to both the theoretical understanding and practical implementation of AI in customer service strategies.

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The Role of Generative Artificial Intelligence in After-Sales Services: Enhancing Customer Repurchase Behavior Through the SOR Model and Customer Pleasure

  • Tran Trong Huynh,
  • Bui Thanh Khoa

摘要

This study investigated the impact of Generative AI (GenAI) applications in after-sales services on customer repurchase behavior, using the Stimulus-Organism-Response (SOR) model and customer pleasure as a mediating variable. The background context highlighted the growing adoption of GenAI in customer service and its potential to enhance customer satisfaction and loyalty. The study aimed to examine how personalization, anthropomorphism, and privacy concerns—key features of GenAI—stimulate emotional engagement and drive repurchase intentions. A quantitative approach was employed, utilizing Partial Least Squares Structural Equation Modeling (PLS-SEM) to analyze survey data collected from 437 customers in Vietnam who interacted with GenAI-driven after-sales services. The results revealed that personalization and anthropomorphism significantly enhanced customer pleasure, which mediated their effect on repurchase intentions. Privacy concerns also influenced customer pleasure positively when managed transparently. The findings confirmed the applicability of the SOR model in understanding customer behavior in AI-mediated services. It was concluded that businesses could leverage GenAI to foster emotional engagement, balancing personalization with privacy and incorporating human-like AI features to optimize after-sales interactions. This study contributes to both the theoretical understanding and practical implementation of AI in customer service strategies.