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Predictive analytics in aviation management

  • Melissa Rampersad-Jagmohan
  • , Yi Wang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Citations (Scopus)

Abstract

The aviation industry has undergone significant changes driven by technological advancements and changing consumer demands (Joseph 2023). One area that has seen notable growth is Predictive Analytics (PA), which involves using historical information to determine trends and forecast future occurrences (IBM 2022). Predictive analytics has become increasingly important in the aviation industry and is driven by the need to improve safety, make better decisions and improve passenger satisfaction and experience (RTS Labs 2023). As data plays an increasingly integral role in the industry, predictive analytics will become even more prevalent. The Aviation industry faces several issues, including flight delays and cancellations, unscheduled maintenance and repair, inefficient fuel consumption and passenger dissatisfaction (Awasthi 2018). This paper aims to select a digital technology to enhance the operations of the aviation industry and improve the passenger experience. The chosen digital technology is Predictive Analytics (PA). Following this, the identification of Strategic Information Systems (SIS) opportunities and their impacts will be discussed, considering competitive edge feasibility, risks, and challenges to implementing the chosen technology. Following the analysis, a recommendation will be proposed to implement the PA technology or maintain current operations (Laudon and Laudon 2018).
Original languageEnglish
Title of host publicationAdvanced Manufacturing and Automation XIII
EditorsYi Wang, Tao Yu, Kesheng Wang
PublisherSpringer
Pages401-406
Number of pages6
ISBN (Print)9789819706648
DOIs
Publication statusPublished - 25 Feb 2024
EventAdvanced Manufacturing and Automation XIII (IWAMA 2023) - Shanghai
Duration: 15 Oct 202316 Oct 2023

Publication series

NameLecture Notes in Electrical Engineering
Volume1154 LNEE
ISSN (Print)1876-1100
ISSN (Electronic)1876-1119

Conference

ConferenceAdvanced Manufacturing and Automation XIII (IWAMA 2023)
CityShanghai
Period15/10/2316/10/23
OtherAdvanced Manufacturing and Automation XIII (IWAMA 2023) (15/10/2023-16/10/2023, Shanghai )

Keywords

  • Aviation
  • Predictive analytics
  • Predictive maintenance
  • Strategic information systems management
  • Information systems

ASJC Scopus subject areas

  • Industrial and Manufacturing Engineering

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