SELECTING E-HAILING DELIVERY SERVICES AMONG UNDERGRADUATE STUDENTS: A FUZZY TOPSIS APPROACH - Muhamad, Siti Nor Nadrah; Zarawi, Nik Nur Syazwanie Mohamad; Pazil, Nur Syuhada Muhammat (INTERNATIONAL JOURNAL OF ENTREPRENEURSHIP AND MANAGEMENT PRACTISES (IJEMP), 2026)
This research evaluates students’ preferences regarding e-hailing food delivery services at Universiti Teknologi Mara (UiTM) Perlis. Despite the growing reliance on online food delivery, there is a lack of studies addressing student preferences in smaller campuses like Perlis, as well as a limited use of Multi-Criteria Decision-Making (MCDM) methods to provide structured rankings rather than simple descriptive statistics. Using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method, the research aims to rank the criteria that influence students’ choices. Factors such as delivery time, price, food delivery services, customer experience, and rider professionalism are examined to understand their impact on decision-making. This research employs quantitative methods, including surveys with 83 students, to gather data and provide insights into improving e-hailing food delivery services. The study is important as it will improve their operational effectiveness and support the continuing development of food e-hailing services. It was revealed that GrabFood was the most frequently used delivery service, followed by Foodpanda, Restaurant Delivery, and Shopee. In future research, this study may employ Multi-Criteria Decision-Making (MCDM) MCDM techniques such as Decision-Making Trial and Evaluation Laboratory (DEMATEL), Multi-Attribute Utility Theory (MAUT), Fuzzy Analytical Hierarchy Process (Fuzzy AHP), and Preferences Ranking Method for Enrichment of Evaluations (Fuzzy PROMETHEE). To improve the review process, additional criteria and a wider range of alternatives might be considered.