Satisfaction Analysis of Airline Passenger Experience

Yiran Zhang

2024

Abstract

With the rapid development of the aviation industry, airlines are increasingly focusing on passenger satisfaction with their flight experience. Not only does this enhance brand loyalty, it may also enable travelers to become effective evangelists for the brand. In order to deeply explore what affects air passenger satisfaction and the key factors behind it, this article studied a data set from Kaggle containing more than 120,000 airline passenger satisfaction scores. Through comparative analysis and verification, this paper selected the XGBoost model and SHAP model from many models. These two models have shown significant effects and accuracy in identifying and predicting factors related to overall satisfaction. At the same time, this article also uses a variety of data visualization methods to show the differences in satisfaction among different types of passengers and different routes. After detailed analysis of the visualization results and combined with market conditions, this article puts forward a series of targeted improvement suggestions, aiming to help airlines optimize services and improve satisfaction.

Paper Citation

in Harvard Style

Zhang Y. (2024). Satisfaction Analysis of Airline Passenger Experience. In Proceedings of the 1st International Conference on Engineering Management, Information Technology and Intelligence - Volume 1: EMITI; ISBN 978-989-758-713-9, SciTePress, pages 141-152. DOI: 10.5220/0012911400004508

in Bibtex Style

@conference{emiti24,
author={Yiran Zhang},
title={Satisfaction Analysis of Airline Passenger Experience},
booktitle={Proceedings of the 1st International Conference on Engineering Management, Information Technology and Intelligence - Volume 1: EMITI},
year={2024},
pages={141-152},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012911400004508},
isbn={978-989-758-713-9},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Engineering Management, Information Technology and Intelligence - Volume 1: EMITI
TI - Satisfaction Analysis of Airline Passenger Experience
SN - 978-989-758-713-9
AU - Zhang Y.
PY - 2024
SP - 141
EP - 152
DO - 10.5220/0012911400004508
PB - SciTePress