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Mathematical Biosciences and Engineering

2022, Volume 19, Issue 10: 9938-9947. doi: 10.3934/mbe.2022463
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Computational analysis of user experience and customer satisfaction with mobile food delivery services: Evidence from big data approaches

  • Department of Applied Artificial Intelligence, Sungkyunkwan University, Sungkyunkwan-ro 25-2, Jongno-gu, Seoul 03063, Republic of Korea

  • Academic Editor: Jeffrey Yi-Lin Forrest
  • Received: 13 May 2022 Revised: 05 July 2022 Accepted: 05 July 2022 Published: 12 July 2022

  • 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.

    Citation: Eunil Park. Computational analysis of user experience and customer satisfaction with mobile food delivery services: Evidence from big data approaches[J]. Mathematical Biosciences and Engineering, 2022, 19(10): 9938-9947. doi: 10.3934/mbe.2022463

    Related Papers:

  • 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.


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