Data Analytics for Air Travel Data: A Survey and New Perspectives

Haiman Tian, Maria Presa-Reyes, Yudong Tao, Tianyi Wang, Samira Pouyanfar, Alonso Miguel, Steven Luis, Mei Ling Shyu, Shu Ching Chen, Sundaraja Sitharama Iyengar

Research output: Contribution to journalReview articlepeer-review

Abstract

From the start, the airline industry has remarkably connected countries all over the world through rapid long-distance transportation, helping people overcome geographic barriers. Consequently, this has ushered in substantial economic growth, both nationally and internationally. The airline industry produces vast amounts of data, capturing a diverse set of information about their operations, including data related to passengers, freight, flights, and much more. Analyzing air travel data can advance the understanding of airline market dynamics, allowing companies to provide customized, efficient, and safe transportation services. Due to big data challenges in such a complex environment, the benefits of drawing insights from the air travel data in the airline industry have not yet been fully explored. This article aims to survey various components and corresponding proposed data analysis methodologies that have been identified as essential to the inner workings of the airline industry. We introduce existing data sources commonly used in the papers surveyed and summarize their availability. Finally, we discuss several potential research directions to better harness airline data in the future. We anticipate this study to be used as a comprehensive reference for both members of the airline industry and academic scholars with an interest in airline research.

Original languageEnglish (US)
Article number167
JournalACM Computing Surveys
Volume54
Issue number8
DOIs
StatePublished - Nov 2022

Keywords

  • Airline
  • big data
  • revenue management

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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