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Analysis of a Data Set to Determine the Dependence of Airline Passenger Satisfaction

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Data Analytics in System Engineering (CoMeSySo 2023)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 910))

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Abstract

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.

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Authors and Affiliations

  1. Artificial Intelligence Technology Scientific and Education Center, Bauman Moscow State Technical University, 105005, Moscow, Russia

    V. S. Tynchenko,  Borodulin & V. A. Nelyub

  2. Peter the Great St. Petersburg Polytechnic University, Saint Petersburg, Russia

    V. A. Nelyub

  3. Department of Information Economic System, Institute of Engineering and Economics, Reshetnev Siberian State University of Science and Technology, 660037, Krasnoyarsk, Russia

    I. I. Kleshko

  4. Department of Systems Analysis and Operations Research, Institute of Informatics and Telecommunications, Reshetnev Siberian State University of Science and Technology, 660037, Krasnoyarsk, Russia

    Rukosueva

  5. Information-Control Systems Department, Institute of Computer Science and Telecommunications, Reshetnev Siberian State University of Science and Technology, 660037, Krasnoyarsk, Russia

    V. S. Tynchenko

  6. Department of Technological Machines and Equipment of Oil and Gas Complex, School of Petroleum and Natural Gas Engineering, Siberian Federal University, 660041, Krasnoyarsk, Russia

    V. S. Tynchenko

Authors
  1. V. S. Tynchenko
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  2. Borodulin
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  3. I. I. Kleshko
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  4. V. A. Nelyub
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Correspondence to I. I. Kleshko .

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Editors and Affiliations

  1. Faculty of Applied Informatics, Tomas Bata University in Zlin, Zlin, Czech Republic

    Radek Silhavy

  2. Faculty of Applied Informatics, Tomas Bata University in Zlin, Zlin, Czech Republic

    Petr Silhavy

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Tynchenko, V.S., Borodulin, Kleshko, I.I., Nelyub, V.A., Rukosueva (2024). Analysis of a Data Set to Determine the Dependence of Airline Passenger Satisfaction. In: Silhavy, R., Silhavy, P. (eds) Data Analytics in System Engineering. CoMeSySo 2023. Lecture Notes in Networks and Systems, vol 910. Springer, Cham. https://doi.org/10.1007/978-3-031-53552-9_40

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