This study aims to analyze the influence of algorithms and live streaming on the impulse buying behavior of fashion consumers on TikTok Shop. The study employed a quantitative approach using primary data collected through an online questionnaire distributed via Google Forms to 100 respondents selected using a purposive sampling technique. Data were analyzed using SPSS version 30 through validity testing, reliability testing, classical assumption testing, multiple linear regression analysis, t-test (partial), F-test (simultaneous), and the coefficient of determination (R Square). The results indicate that the algorithm variable does not have a significant effect on the impulse buying behavior of fashion consumers on TikTok Shop, with a significance value of 0.102 (>0.05). In contrast, the live streaming variable has a positive and significant effect on impulse buying, with a regression coefficient of 0.559 and a significance value of <0.001 (<0.05). Simultaneously, algorithms and live streaming have a significant effect on impulse buying, as evidenced by an F-statistic of 46.753 and a significance value of <0.001. The coefficient of determination (R Square) of 0.491 indicates that the two independent variables explain 49.1% of the variation in impulse buying, while the remaining 50.9% is influenced by other factors outside the research model. These findings suggest that live streaming is a more dominant factor than algorithms in encouraging consumers to make impulsive purchases on TikTok Shop.
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