Examining the Effect of AI-Driven Recommendation Ease and Consumer Privacy Perception on TikTok Shop Repurchase Intentions in Tegal
DOI:
https://doi.org/10.24905/icobis.v2i1.39Keywords:
Artificial Intelligence Recommendations, Consumer Privacy Perception, Repurchase Intention, Social Commerce, TikTok ShopAbstract
This study aims to analyze the influence of Artificial Intelligence (AI)-driven recommendation ease and consumer privacy perception on repurchase intentions within the TikTok Shop application in Tegal City and Tegal Regency. Employing a quantitative approach, the research utilized a survey method with purposive sampling, involving 100 TikTok Shop users who had previously made purchases through the platform. Data were collected via questionnaires and analyzed using SPSS version 22, encompassing validity and reliability tests, classical assumption tests, multiple linear regression, t-tests, F-tests, and the coefficient of determination. The findings reveal that AI recommendation ease does not exert a significant effect on repurchase intention, showing a significance value of 0.069 (>0.05) and a regression coefficient of 0.175. Conversely, consumer privacy perception demonstrates a positive and significant effect on repurchase intention, with a significance value of 0.000 (<0.05) and a coefficient of 0.503. Simultaneously, both independent variables significantly influence repurchase intention, supported by an F-value of 26.448 and a significance value of 0.000. Furthermore, the coefficient of determination (R2) of 0.353 indicates that 35.3% of the variance in repurchase intention is explained by these two variables, while the remaining 64.7% is attributed to external factors outside the model. These findings highlight the critical importance of robust privacy protection, data transparency, and the continuous enhancement of AI recommendation systems in the social commerce sector.
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