Factors Affect Airline Customers’ Satisfaction: Data Mining

DOI

10.2991/978-94-6463-210-1_43How to use a DOI?

Keywords

airline; customer satisfaction; factor analysis; comparative analysis; logistic regression

Abstract

This study investigated different factors that affect customer satisfaction in the airline industry. These factors include demographic elements (gender and age), and other objective factors like delay time, travel distance, customer class, type of class, and customers’ impressions of different aspects of airline services and facilities. After the exploratory data analysis, statistical approaches were chosen to conduct this research, including comparative analysis and logistics regression. This paper discusses the above-influencing factors and explores the diversity of different categories of customers’ concerns about various aspects of flight services. Finally, a logistic regression model was developed to predict flight satisfaction. The main findings are as follows.

- Males and females have different concerns about needs during travel.

- Customers selecting the business class and those taking business travel are almost the same groups of people, who are generally disloyal. In addition, older customers are more likely to be in better cabins.

- Travelers are more tolerant of departure delays than arrival delays.

- Business travelers are more sensitive to delays. Long-distance flights suffer relatively less delay.

Copyright

© 2023 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Yifei Wang
PY  - 2023
DA  - 2023/07/25
TI  - Factors Affect Airline Customers’ Satisfaction: Data Mining
BT  - 2023 4th International Conference on E-Commerce and Internet Technology (ECIT 2023)
PB  - Atlantis Press
SP  - 344
EP  - 362
SN  - 2589-4943
UR  - https://doi.org/10.2991/978-94-6463-210-1_43
DO  - 10.2991/978-94-6463-210-1_43
ID  - Wang2023
ER  -