Application of Data Science in Online Food Delivering App :A Data-Driven Approach Using the UTAUT2 Model in Zomato

The fast growth of online food ordering websites has revolutionized consumer behavior, fueled by technological and data science advancements.This research examines the determinants of sustained intention to use online food ordering websites, with a focus on Zomato.The study model includes habit, performance expectancy, information quality, and price value as independent variables, examining their impact on sustained intention as the dependent variable.Data were gathered using a structured questionnaire, with 104 participants, and analyzed to support the proposed hypotheses.The results shed light on how user habits, perceived effectiveness, service information quality, and price perception affect sustained use of online food ordering websites.The research contributes to consumer retention mechanisms and service feature optimization through data-driven decision-making in the food ordering sector.