PERCEIVED USEFULNESS OF MCDONALD’S FOOD DELIVERY APP AND ITS CUSTOMER SATISFACTION AROUND SAN FRANCISCO DEL MONTE, QUEZON CITY

Abstract

This study explores the correlation between perceived usefulness and customer satisfaction with the McDonald’s Food Delivery App in San Francisco Del Monte, Quezon City, grounded in the Technology Acceptance Model (TAM). Prompted by the rising dependence on online food delivery platforms—especially in the aftermath of the COVID-19 pandemic—the research investigates key user concerns such as interface usability, login difficulties, inaccurate mapping, and delayed deliveries. This study adopted a descriptive-correlational research design and utilized purposive sampling to gather data from 30 individuals aged 18 and above who use the McDonald’s Food Delivery App. The research examined key variables such as perceived usefulness, perceived ease of use, behavioral intention to use, and actual system usage. These were analyzed alongside customer satisfaction indicators, including reliability, responsiveness, assurance, empathy, and tangibles. The data were processed using weighted mean and Pearson’s correlation coefficient to evaluate the relationships among the variables. The findings revealed that users highly rated the app’s perceived usefulness (mean = 3.44) and ease of use (mean = 3.37), with frequent actual usage (mean = 3.36). However, behavioral intention to continue using the app was slightly lower (mean = 3.19), indicating opportunities to strengthen user commitment. Regarding customer satisfaction, responsiveness, assurance, empathy, and tangibles received favorable evaluations (mean range = 3.33–3.35), while reliability scored somewhat lower (mean = 3.29), highlighting areas for potential service enhancement. A strong and statistically significant positive correlation was observed between perceived usefulness and customer satisfaction (r = 0.888, p < 0.05), leading to the rejection of the null hypothesis. The results confirm that greater perceived usefulness of the app leads to higher levels of customer satisfaction. Although the McDonald’s Food Delivery App performs effectively and meets user expectations, enhancements are still needed in areas such as user interface, personalization, delivery precision, and engagement strategies. Based on these insights, the study recommends the following: improving app performance, incorporating gamification and referral programs, utilizing AI-powered chatbots for streamlined customer support, and increasing delivery reliability. The proposed improvement plan aims to refine system usability, enhance customer service, and enable real-time tracking to deliver a more seamless and rewarding user experience. These findings provide actionable insights for McDonald’s and similar food delivery platforms seeking to strengthen customer loyalty and satisfaction in an increasingly digital and competitive food service environment.