AI-POWERED PRODUCT RECOMMENDATIONS AND THEIR ROLE IN STIMULATING IMPULSE BUYING AMONG ONLINE SHOPPERS
DOI:
https://doi.org/10.1234/aira.v2i1.41Keywords:
artificial intelligence, behavior, e-commerce, impulse buying, social commerceAbstract
This study investigates the impact of AI-powered product recommendation strategies on consumer impulse buying behavior within e-commerce platforms, focusing on the Generation Z market segment in Indonesia. As online retail continues to expand, platforms increasingly rely on artificial intelligence to personalize shopping experiences. This research addresses a gap in understanding how multiple integrated marketing elements—credibility, surprise, involvement, visual appeal, and personalization—influence unplanned consumer purchases in a rapidly evolving digital context. Using a quantitative correlational approach, data were collected from 100 Generation Z online shoppers through a structured questionnaire employing a 5-point Likert scale. Statistical analysis was conducted using SPSS version 26. The research included item validity testing (r count > 0.195), internal reliability testing (Cronbach's Alpha > 0.70), and classical assumption tests including normality, multicollinearity, and heteroscedasticity. The core analysis employed multiple regression to determine the individual and collective impact of each variable on impulse buying behavior. All five variables were found to significantly influence consumer behavior, with surprise (t = 3.201, p < 0.01) emerging as the strongest predictor, followed by involvement (t = 2.879, p < 0.01), personalization (t = 2.519, p < 0.05), credibility (t = 2.143, p < 0.05), and visual appeal (t = 1.983, p < 0.05). The overall model was statistically significant (F = 9.643 > F-table = 2.31, p < 0.01), confirming the combined effect of these marketing elements on impulse buying. The study contributes to the theoretical development of social commerce by empirically validating the behavioral influence of AI recommendations, offers practical guidance for optimizing personalization strategies in digital marketing, and provides region-specific insights into Indonesian consumer behavior. These findings establish a foundation for future research on ethical and technological advancements in AI-driven consumer engagement.
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