The Effect of Recommendation Algorithms and Provision of Digital Facilities on Purchasing Patterns and Consumer Loyalty on E-Commerce Platforms in Jakarta

This study investigates the effect of recommendation algorithms and the provision of digital facilities on purchasing patterns and consumer loyalty in e-commerce platforms in Jakarta. Using a quantitative approach, data was collected from 180 respondents through a structured questionnaire utilizing a Likert scale (1-5). The data was analyzed using Structural Equation Modeling with Partial Least Squares (SEM-PLS 3). The results show that recommendation algorithms have a significant positive impact on both consumer loyalty and purchasing patterns, with path coefficients of 0.454 and 0.419, respectively. Additionally, the provision of digital facilities also influences consumer loyalty (0.360) and purchasing patterns (0.405). The study found that enhancing both personalized recommendations and digital infrastructure can significantly improve customer retention and sales, emphasizing the importance of these factors for e-commerce platforms in Jakarta. The model’s R² values suggest that it explains a substantial portion of the variance in consumer loyalty (0.567) and purchasing patterns (0.580), with high predictive relevance. The findings provide practical insights for e-commerce businesses to optimize user experience and strengthen consumer relationships, contributing to improved competitive advantage in the digital market.