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

Author:

Park Eunil

Abstract

<abstract><p>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.</p></abstract>

Publisher

American Institute of Mathematical Sciences (AIMS)

Subject

Applied Mathematics,Computational Mathematics,General Agricultural and Biological Sciences,Modeling and Simulation,General Medicine

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Determining the Correlation among the Users' Satisfaction and Familiarity with Malay Entrepreneurs Food Delivery Mobile Applications in Malaysia;Annals of Data Science;2024-09-13

2. Interaction and Design Barriers for Older Adults in Food Delivery Apps: A Usability Study;International Journal of Human–Computer Interaction;2024-06-13

3. Examining metaverse game platform adoption: Insights from innovation, behavior, and coolness;Technology in Society;2024-06

4. Online Food Delivery by Personal Customization System;2024 International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA);2024-05-23

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