Big Data to Improve Strategic Network Planning in Airlines

1. Auflage 2020
ISBN: 978-3-658-27581-5
Verlag: Springer

Buch, Englisch, 462 Seiten, Book, Format (B × H): 148 mm x 210 mm, Gewicht: 630 g

Reihe: Research

Big data has become an important success driver in airline network planning. Maximilian Schosser explores the status quo of network planning across a case study group consisting of nine airlines representing different business models. The author describes 23 big data opportunities for airline network planning and evaluates them based on their specific value contribution for airline network planning. Subsequently, he develops a financial evaluation methodology for big data opportunities based on key performance indicators for airline network planning departments.

Zielgruppe

Research

Autoren/Hrsg.

Schosser, Maximilian

Fachgebiete

• Mathematik | Informatik EDV | Informatik Angewandte Informatik Wirtschaftsinformatik
• Wirtschaftswissenschaften Betriebswirtschaft Wirtschaftsinformatik, SAP, IT-Management
• Wirtschaftswissenschaften Wirtschaftssektoren & Branchen Fertigungsindustrie Luftfahrtindustrie
• Wirtschaftswissenschaften Betriebswirtschaft Bereichsspezifisches Management Einkauf, Logistik, Supply-Chain-Management
• Wirtschaftswissenschaften Wirtschaftssektoren & Branchen Transport- und Verkehrswirtschaft

Inhaltsverzeichnis

Introduction, Methodology, and Theoretical Foundations of Strategic Network Planning in Airlines.- Status Quo of Strategic Network Planning in Airlines.- Big Data Opportunities for Airline Network Planning.- Financial Impact of Big Data for Airline Network Planning.

Über Autor(innen)

Maximilian Schosser completed his doctoral dissertation under the supervision of Prof. Dr. Iris Hausladen at the Heinz-Nixdorf Chair for IT-based Logistics at HHL Leipzig Graduate School of Management, Germany. He works as a management consultant and focuses on digitization and analytical topics in the transportation and logistics sector. His core field of expertise is the deployment of big data analytics in commercial and operational processes.