<![CDATA[This article examines the temporal dynamics of customer journey emotions and proposes a continuous-time modeling approach to better understand how emotions evolve throughout the customer experience. Traditional customer journey models often rely on static, stage-based representations that fail to capture the continuous and interconnected nature of emotional responses. Drawing on a narrative literature review across marketing, psychology, and data science, this study highlights the importance of viewing emotions as dynamic trajectories shaped by ongoing interactions. Key findings emphasize the role of emotional peaks, troughs, critical moments, and lag effects in influencing overall customer perceptions and behavioral outcomes. The study introduces a continuous-time modeling framework that integrates customer interactions as inputs, emotional state changes as processes, contextual and psychological factors as mediators, and outcomes such as satisfaction and loyalty. Additionally, moderating factors including customer characteristics, interaction channels, timing, and external context are identified as crucial in shaping emotional dynamics. The article contributes theoretically by integrating temporal perspectives with customer experience research and offers practical insights for real-time monitoring and adaptive experience design. Future research should focus on empirical validation and the application of advanced analytics to capture real-time emotional changes in customer journeys.]]>
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