Библиографическое описание:Analysis of a Data Set to Determine the Dependence of Airline Passenger Satisfaction : доклад, тезисы доклада / V. S. Tynchenko [et al.]. - [S. l. : s. n.], 2024. - Текст : непосредственный // Data Analytics in System Engineering : Proceedings of 7th Computational Methods in Systems and Software 2023 / Computational Methods in Systems and Software 2023 (CoMeSySo2023) (2023 ; 12.04 - 13.04 ; Zlín, Czech Republic). - Springer Nature Switzerland, 2024. - 910-3. - P. 434-458.
Аннотация:This paper presents an analysis of a data set to determine the factors influencing airline passenger satisfaction. The study examines various criteria such as gender, customer type, age, travel type, class, and range to assess their impact on passenger satisfaction. The dataset consists of 25 columns, including attributes like Wi-Fi availability, convenience of online booking, seat comfort, in-flight entertainment, baggage handling, and overall satisfaction. The sample is relatively balanced, with equal representation of men and women, predominantly repeat customers, and a majority flying for business purposes. Key findings include a strong correlation between departure and arrival delays, higher satisfaction among passengers in business class, and positive ratings for Wi-Fi service correlating with overall satisfaction. Correlation analysis reveals interdependencies between different attributes, such as the influence of cleanliness on seat comfort and food and beverage ratings. In addition, a neural network forecasting model is used to estimate the average ratings of passengers, although with low accuracy, which was later excluded. Finally, a decision tree algorithm is utilized to identify the most significant attributes affecting passenger satisfaction words.
Мероприятие:Computational Methods in Systems and Software 2023 (CoMeSySo2023) (Zlín, Czech Republic, 2023 ; 12.04 - 13.04)
Номера страниц:434-458
Держатель оригинала документа:Bauman Moscow State Technical University, Peter the Great St. Petersburg Polytechnic University, Reshetnev Siberian State University of Science and Technology, Siberian Federal University
Количество экземпляров:
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