TY - GEN
T1 - Predictive analytics in aviation management
AU - Rampersad-Jagmohan, Melissa
AU - Wang, Yi
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.
PY - 2024/2/25
Y1 - 2024/2/25
N2 - 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).
AB - 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).
KW - Aviation
KW - Predictive analytics
KW - Predictive maintenance
KW - Strategic information systems management
KW - Information systems
UR - https://www.scopus.com/pages/publications/85187786487
U2 - 10.1007/978-981-97-0665-5_52
DO - 10.1007/978-981-97-0665-5_52
M3 - Conference contribution
SN - 9789819706648
T3 - Lecture Notes in Electrical Engineering
SP - 401
EP - 406
BT - Advanced Manufacturing and Automation XIII
A2 - Wang, Yi
A2 - Yu, Tao
A2 - Wang, Kesheng
PB - Springer
T2 - Advanced Manufacturing and Automation XIII (IWAMA 2023)
Y2 - 15 October 2023 through 16 October 2023
ER -