Computational analysis of user experience and customer satisfaction with mobile food delivery services: Evidence from big data approaches

Abstract

Because of the COVID-19 global pandemic, mobile food delivery services have gained new prominence in our society. With this trend, the understanding of user experience in improving mobile food delivery services has gained increasing importance. To this end, we explore how user experience factors extracted by two natural language processing methods from comments of user reviews of mobile food delivery services significantly improve user satisfaction with the services. The results of two multiple regression analyses show that sentiment dimension factors, as well as usability, usefulness, and affection, have notable effects on satisfaction with the applications. Based on several findings of this study, we examine the significant implications and present the limitations of the study.