Food Delivery Applications with Data Mining Methods: Evaluating End-Users’ Experience

Abstract

Online food delivery applications (OFD apps) have existed in Malaysia for more than a decade. It has received a wide range of customer acceptance among the young and adults in Malaysia. However, the paradigm of customer satisfaction in the OFD apps has shifted since the COVID-19 pandemic struck the world. There were several recent research conducted to identify the factors that affected Malaysian tertiary students’ satisfaction towards OFD apps. However, past research did not study the aspect of OFD apps’ content and user interface (UI) design from a mobile application’s usability study perspective. Moreover, past research also did not classify or cluster the customers to understand them from a deeper perspective. This research attempted to explore the factors affecting Malaysia tertiary students' satisfaction with OFD apps with two data mining methods namely the multiple regression analysis (MRA) and K-means clustering analysis, by using questionnaire data collected from 156 Malaysia tertiary students. The output of the analysis will help the OFD service providers to understand their customers better and be able to plan the right resources to manage the app's quality and services.