Integrating Decision Support System to Food Choices for Better Digital Customer Experience
(R2024-122514)

AUTHORS

Bahar Tasar, Izmir Bakircay University; Keti Ventura, Ege University; Ural Gokay Cicekli, Ege University

ABSTRACT

Consumers have conflicting demands and search for different personalized tools to help their decisions in the digital world. This study aims to develop a personalized decision support system for food choices. The developed Goal Programming model creates optimal menu alternatives according to consumers' hunger levels, dietary status, allergen restrictions, corresponding to personal needs, and speed and price preferences regarding service performance. These alternatives help consumers find the right foods, reducing wasted time and improving well-being. A pilot customer satisfaction survey evaluates the digital customer experience. The results show that the developed food recommendation system increased online customer satisfaction and experience.