Process Mining for resilient airport operations: A case study of Munich Airport’s turnaround process

The aviation industry has faced significant challenges in recent years, including a punctuality crisis in 2018/19 and the ongoing impact of COVID-19 on operations since March 2020. Hence, the industry seeks innovative ways to optimize its operations and become more resilient. Process Mining (PM) has proven valuable in various settings and industries by analyzing event-log data extracted from existing information systems. As airports play a critical role within the aviation network, the authors expand on a case study-based methodology and employ PM techniques to analyze data generated within the airport collaborative decision-making (ACDM) framework for the turnaround process at Munich Airport. They show that applying PM enhances operational transparency, reveals performance differences between ground-handling corporations and airlines, and identifies data quality problems with the implemented ACDM framework. Additionally, the authors develop a conceptual framework demonstrating the positive influence of PM on airport resilience. This study contributes to the aviation literature and resilience theory by showcasing the potential of PM for analyzing and optimizing operational airport processes. Since the ACDM framework is widely used in Europe, researchers and practitioners can apply this approach to improve turnaround processes at other European airports.

• Record URL:
  • https://doi.org/10.1016/j.jairtraman.2023.102451
• Record URL:
  • http://www.sciencedirect.com/science/article/pii/S0969699723000947
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/oclc/31005945
• Supplemental Notes:
  • © 2023 Elsevier Ltd. All rights reserved. Abstract reprinted with permission of Elsevier.
• Authors:
  • Rott, Julian
  • 0000-0002-9882-6737
  • König, Fabian
  • 0000-0002-7879-0239
  • Häfke, Hannes
  • Schmidt, Michael
  • Böhm, Markus
  • 0000-0003-2859-5651
  • Kratsch, Wolfgang
  • Krcmar, Helmut
  • 0000-0002-2754-8493
• Publication Date: 2023-9

Language

• English

Media Info

• Media Type: Web
• Features: References;
• Pagination: 102451
• Serial:
  • Journal of Air Transport Management
  • Volume: 112
  • Issue Number: 0
  • Publisher: Elsevier
  • ISSN: 0969-6997
  • Serial URL: http://www.sciencedirect.com/science/journal/09696997

Subject/Index Terms

• TRT Terms: Airport operations; COVID-19; Data mining; Disaster resilience
• Identifier Terms: Munich Airport International
• Geographic Terms: Munich (Germany)
• Subject Areas: Aviation; Operations and Traffic Management; Terminals and Facilities;

Filing Info

• Accession Number: 01887883
• Record Type: Publication
• Files: TRIS
• Created Date: Jul 18 2023 3:15PM