Objective: To analyze the purchasing behavior of millennials on the e-commerce platforms, identifying the key factors that influence their repurchase intention. Materials and methods: A non-experimental quantitative approach of cross-sectional design was used, in which data were collected using a structured questionnaire applied to 400 participants. Data analysis included both descriptive and inferential statistics, using Pearson correlation analysis to assess the relationship between trust, satisfaction, and repurchase intention. Results: The results reveal that trust (0.78) and satisfaction (0.83) have a significant positive correlation with repurchase intention. Furthermore, 50% of participants use e-commerce platforms on a weekly basis, highlighting the relevance of user experience in customer retention. Conclusions: Trust and satisfaction are the most important factors determinants ...

Objective: This study analyzes how predictive models and AI algorithms influence fashion electronic trade optimization, assessing their impact on personalizing the user experience and increasing sales. Materials and methods: A quantitative approach with a non-experimental, cross-sectional, and correlational design was used, applying surveys to 50 fashion retail companies with an online presence, and to 500 consumers active on electronic trade platforms. Data were collected through surveys and databases, analyzing factors such as the implementation of artificial intelligence, the conversion rate, and the customer loyalty. For the analysis, descriptive and inferential statistics tests, including correlation and regression analysis, were used for the analysis. Results: The results evidence that AI has a significant impact on sales and customer loyalty, with a positive correlation (r = 0.87;...