Online Food Ordering Activity

This dataset investigates online food ordering (OFO) behavior, focusing on young adults (ages 16–30) to explore the relationship between OFO usage, order frequency, and obesity. The study hypothesizes that frequent OFO usage may correlate with higher BMI levels due to food choices and ordering convenience and that factors like impulsive decision-making, tech-savviness, promotional offers, and convenience are key drivers of OFO frequency. Additionally, it proposes that frequent and infrequent users exhibit distinct behaviors, with frequent users more aware of nutritional quality and infrequent users citing cost concerns as a barrier. The dataset contains 343 records with columns covering demographics, health, economic factors, and behavioral motivations for OFO, as well as preferred platforms. Key findings show a weak positive association between OFO frequency and obesity (p-value = 2.43e-7, coefficient = 0.28), and classification models such as Random Forest achieve 81% accuracy in predicting frequent users, identifying convenience, variety, and promotional discounts as top motivators. The dataset provides a basis for modeling OFO behavior and assessing health implications, with potential applications in consumer segmentation and public health, revealing cultural and economic factors shaping OFO practices. The data was collected by via a survey, which had questions split into two sections: demographics and OFO-related factors. Comprising 25 questions, the survey included text-based items, multiple-choice questions, checkboxes, and Likert scale items. Administered anonymously via Google Forms, it prioritized respondent privacy and ease of completion. After gathering initial feedback from peers, adjustments were made to refine the final version.