Modeling the Determinants of Customer Mindset Towards Online Food Ordering

Online food ordering has become an essential part of the modern dining experience, offering convenience and time savings for consumers. It allows customers to browse menus, place orders, and make payments through mobile apps or websites. This growing trend not only enhances customer satisfaction but also drives business growth for restaurants. So, understanding the factors that shape customer mindset and preferences can help businesses enhance their services, increase customer satisfaction, and foster brand loyalty. Additionally, as the digital food delivery market expands, insights from such research can guide the development of more user-friendly apps and marketing strategies, ultimately boosting both customer engagement and business success. The present study aimed to model the factors affecting customers’ mindset towards online food ordering. Employing a mixed-methods approach, the study utilized structured interviews with 16 users of mobile food ordering applications to gather the necessary data for thematic analysis. MAXQDA software was employed for data analysis, resulting in 71 sub-themes being extracted and categorized into 14 main themes through axial coding. Subsequently, using interpretive structural modeling (ISM), the 14 main themes were analyzed based on their feedback relationships. The results indicate that food quality, food price, and living conditions significantly influence advertisement and ordering experience components.