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In the digital entertainment landscape, AI-enhanced video streaming services like Netflix and Hulu significantly shape user experiences through AI-based recommendations. This study examines customer perceptions of these AI-driven suggestions, focusing on factors such as Perceived Interactivity, Service Quality, Commitment, Trust, and Personalization. Using data from a diverse sample in Klang Valley, Malaysia, the study employs Partial Least Squares Structural Equation Modeling (PLS-SEM) and Necessary Condition Analysis (NCA). PLS-SEM models complex relationships to predict customer satisfaction, while NCA identifies essential conditions for desired outcomes in customer experience. Findings reveal that Personalization significantly influences satisfaction (path coefficient = 0.34), with Trust enhancing the impact of Perceived Interactivity (mediation effect size = 0.15). Expectancy confirmation also moderates the relationship between service attributes and satisfaction (β = 0.09). The results highlight the importance of tailored personalization and robust trust mechanisms in AI systems, emphasizing strategies to improve viewer retention and overall satisfaction.
Ahmed et al. (Wed,) studied this question.
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