Big Data to Improve Strategic Network Planning in Airlines
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
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Maximilian Schosser
Big Data to Improve Strategic Network Planning in Airlines
LEIPZIG GRADUATE SCHOOL OF MANAGEMENT
Schriftenreihe der HHL Leipzig Graduate School of Management
Reihe herausgegeben von Stephan Stubner, Leipzig, Deutschland
In dieser Schriftenreihe werden aktuelle Forschungsergebnisse aus dem B ereich Unternehmensführung präsentiert. Die einzelnen Beiträge spiegeln die wissen schaftliche Ausrichtung der HHL in Forschung und Lehre wider. Sie zeichnen sich vor allem durch eine ganzheitliche, integrative Perspektive aus und sind durch den Anspruch geprägt, Theorie und Praxis zu verbinden sowie in besonderem Maße internationale Aspekte einzubeziehen.
Weitere Bände in der Reihe http://www.springer.com/series/12648
Maximilian Schosser
Big Data to Improve Strategic Network Planning in Airlines With a foreword by Prof. Dr. Iris Hausladen
Maximilian Schosser HHL Leipzig Graduate School of Management Heinz-Nixdorf Chair of IT-based Logistics Leipzig, Germany Dissertation HHL Leipzig Graduate School of Management, 2019
Schriftenreihe der HHL Leipzig Graduate School of Management ISBN 978-3-658-27581-5 ISBN 978-3-658-27582-2 (eBook) https://doi.org/10.1007/9783658275822 Springer Gabler © Springer Fachmedien Wiesbaden GmbH, part of Springer Nature 2020 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer Gabler imprint is published by the registered company Springer Fachmedien Wiesbaden GmbH part of Springer Nature. The registered company address is: Abraham-Lincoln-Str. 46, 65189 Wiesbaden, Germany
For my wife Karin who filled the days of my PhD studies with pure joy. For my mother Jutta who taught me the most important trait as a researcher – curiosity. For my father Rudolf whose perfectionist mind helped with great suggestions for this thesis.
Foreword Big data not just evolved as a popular buzzword over time but is
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