Schriftenreihe der HHL Leipzig Graduate School of Management 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 meanwhile seen as a high potential field for improving business processes and decisions taken by responsible persons in different industry sectors, such as airlines Nevertheless, available advantages of big data have not yet been adequately measured from an economic perspective and have very often not yet been exploited at all or to a reasonable level Additionally, corresponding theoretical concepts and scientific developments focusing on the area of network planning in airlines are currently more or less missing Those challenging deficits make the topic considered by Mr Schosser highly relevant both from a theoretical as well as a practical perspective Thus, the main objective of the thesis consists in closing both the scientific research gap and providing a solution to practitioners focusing on the assessment of big data opportunities in the network planning context of airlines The author provides with the step-by-step, theoretically and empirically based development of the framework, its elements and procedures in the present doctoral thesis an outstanding analytical as well as conceptual personal contribution The framework is from a content-related point of view to be honored as a pioneering achievement and the dissertation contains a lot of new findings that represent a starting point for further work predominantly in the research and practice field of big data evaluation focused on airline network planning that can be transferred to further use cases respectively fields of applications The book, which is based on a dissertation at the HHL Leipzig Graduate School of Management, is aimed equally at readers from science and practice, dealing with (big) data collection, economic evaluation of big data as well as big data analytics Leipzig, May 2019 Prof Dr Iris Hausladen Preface The idea for this PhD thesis was born during a consulting project at a European airline, where different departments were at completely different maturity stages of using Big Data While at some departments network planning was done the old-fashioned way, with legacy IT-systems, data and processes, other departments had already implemented a much more agile way of integrating Big Data The network planning department was frequently approached by data providers with concrete offers, but there was no method to evaluate the impact of the data for airline network planning, and most of the offers were turned down for this reason At the same time, there was no research available to answer this question The main objective of this PhD thesis is hence to alleviate the lack of evaluation methods and provide a concise answer/approach/framework of how Big Data can create value for individual network planning steps The target audience of this thesis comprises airline network planners of all seniority levels and fellow researchers working on Big Data applications for the transportation industry, on network optimization problems or on commercial topics in airlines I tried to find a middle ground between content of pure scientific interest (e.g., chapters and 3), and presenting relevant findings for practitioners (chapters 4, and 6) Finally, I want to thank everyone who contributed to this PhD thesis, in particular my thesis advisor Prof Dr Iris Hausladen, who provided guidance and challenge whenever necessary Further, I want to thank all interview partners of our airline case study group, who need to stay anonymous due to non-disclosure agreements Philipp Behrends, Karin Garcia and Rudolf Schosser made an invaluable contribution by reviewing and commenting on various drafts of this thesis My thanks go also to all staff and students of HHL Leipzig Graduate School of Management who made my time there so enjoyable Finally, I want to thank Maximilian Rothkopf for helping to shape the idea and David Speiser for his support of my PhD project My PhD thesis would not have been possible without the financial support during my educational leave granted by the Zurich Office of McKinsey & Company Berlin, May 2019 Maximilian Schosser Contents Introduction 1.1 Problem and research gap definition 1.1.1 Practical problem 1.1.2 Scientific research gap 1.2 Objective of the study and research questions .3 Methodology 2.1 Development of research design 2.2 Literature review 11 2.2.1 Design of a structured literature review process 11 2.2.2 Identification of keywords, databases, and journals 13 2.2.3 Results of the structured keyword search 15 2.2.4 Description of the research gap 17 2.3 Comparative case study 18 2.3.1 Selection of the case study type 19 2.3.2 Case sampling .20 2.3.3 Data collection and analysis techniques 23 2.3.4 Research quality assurance 27 Theoretical foundation .29 3.1 Development of a theoretical concept 29 3.2 Airlines and their business models 31 3.2.1 The airline industry 32 XII Contents 3.2.2 Development and recent trends in the airline industry 34 3.2.3 Airline business models .35 3.2.4 Major business processes of airlines 43 3.3 Introduction to the network theory .44 3.3.1 Definition of networks 44 3.3.2 Distinction between the network theories 48 3.3.3 Fundamentals of the graph theory .50 3.3.4 Network flows and network optimization .55 3.3.5 Design of flow networks .62 3.4 Airline networks 64 3.4.1 General properties of airline networks 65 3.4.2 Types of airline networks .67 3.4.3 Airline network economics 74 3.4.4 Airline network indicators .78 3.5 Network planning in airlines 84 3.5.1 Components of network planning 84 3.5.2 Long-term planning 87 3.5.3 Spatial optimization 96 3.5.4 Temporal optimization 99 3.5.5 Operational optimization 103 3.5.6 Network planning in cargo airlines .106 3.5.7 Data needs of network planning 110 3.5.8 Definition of strategic network planning .124 448 References Pan, B., Chenguang Wu, D., & Song, H (2012) Forecasting hotel room demand using search engine data Journal 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7.1.1 Airline business models and network planning 320 7.1.2 The network planning process in literature and practice…322 7.1.3 Current data use in literature... airline networks .67 3.4.3 Airline network economics 74 3.4.4 Airline network indicators .78 3.5 Network planning in airlines 84 3.5.1 Components of network planning ... most suited to improve network planning for airlines or replace existing data types [RQ 3]? 343 8.1.4 How can the impact of big data opportunities for airline network planning be quantified