IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2503.05754.html
   My bibliography  Save this paper

Examining the Dynamics of Local and Transfer Passenger Share Patterns in Air Transportation

Author

Listed:
  • Xufang Zheng
  • Qilei Zhang
  • Victoria Cobb
  • Max Z. Li

Abstract

The air transportation local share, defined as the proportion of local passengers relative to total passengers, serves as a critical metric reflecting how economic growth, carrier strategies, and market forces jointly influence demand composition. This metric is particularly useful for examining industry structure changes and large-scale disruptive events such as the COVID-19 pandemic. This research offers an in-depth analysis of local share patterns on more than 3900 Origin and Destination (O&D) pairs across the U.S. air transportation system, revealing how economic expansion, the emergence of low-cost carriers (LCCs), and strategic shifts by legacy carriers have collectively elevated local share. To efficiently identify the local share characteristics of thousands of O&Ds and to categorize the O&Ds that have the same behavior, a range of time series clustering methods were used. Evaluation using visualization, performance metrics, and case-based examination highlighted distinct patterns and trends, from magnitude-based stratification to trend-based groupings. The analysis also identified pattern commonalities within O&D pairs, suggesting that macro-level forces (e.g., economic cycles, changing demographics, or disruptions such as COVID-19) can synchronize changes between disparate markets. These insights set the stage for predictive modeling of local share, guiding airline network planning and infrastructure investments. This study combines quantitative analysis with flexible clustering to help stakeholders anticipate market shifts, optimize resource allocation strategies, and strengthen the air transportation system's resilience and competitiveness.

Suggested Citation

  • Xufang Zheng & Qilei Zhang & Victoria Cobb & Max Z. Li, 2025. "Examining the Dynamics of Local and Transfer Passenger Share Patterns in Air Transportation," Papers 2503.05754, arXiv.org.
    • Handle: RePEc:arx:papers:2503.05754
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/2503.05754
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Gunter, Ulrich & Zekan, Bozana, 2021. "Forecasting air passenger numbers with a GVAR model," Annals of Tourism Research, Elsevier, vol. 89(C).
    2. Marques Teixeira, Filipe & Derudder, Ben, 2020. "Revealing route bias in air transport data: The case of the Bureau of Transport Statistics (BTS), Origin-Destination Survey (DB1B)," Journal of Air Transport Management, Elsevier, vol. 82(C).
    3. de Barros, Alexandre G. & Somasundaraswaran, A.K. & Wirasinghe, S.C., 2007. "Evaluation of level of service for transfer passengers at airports," Journal of Air Transport Management, Elsevier, vol. 13(5), pages 293-298.
    4. Cattaneo, Mattia & Malighetti, Paolo & Paleari, Stefano & Redondi, Renato, 2017. "Evolution of the European network and implications for self-connection," Journal of Air Transport Management, Elsevier, vol. 65(C), pages 18-28.
    5. Wei, Wenbin & Hansen, Mark, 2006. "An aggregate demand model for air passenger traffic in the hub-and-spoke network," Transportation Research Part A: Policy and Practice, Elsevier, vol. 40(10), pages 841-851, December.
    6. Birolini, Sebastian & Besana, Emanuele & Cattaneo, Mattia & Redondi, Renato & Sallan, Jose Maria, 2022. "An integrated connection planning and passenger allocation model for low-cost carriers," Journal of Air Transport Management, Elsevier, vol. 99(C).
    7. Redondi, Renato & Malighetti, Paolo & Paleari, Stefano, 2012. "De-hubbing of airports and their recovery patterns," Journal of Air Transport Management, Elsevier, vol. 18(1), pages 1-4.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Fageda, Xavier, 2014. "What hurts the dominant airlines at hub airports?," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 70(C), pages 177-189.
    2. Sismanidou, Athina & Tarradellas, Joan & Bel, Germà & Fageda, Xavier, 2013. "Estimating potential long-haul air passenger traffic in national networks containing two or more dominant cities," Journal of Transport Geography, Elsevier, vol. 26(C), pages 108-116.
    3. Birolini, Sebastian & Besana, Emanuele & Cattaneo, Mattia & Redondi, Renato & Sallan, Jose Maria, 2022. "An integrated connection planning and passenger allocation model for low-cost carriers," Journal of Air Transport Management, Elsevier, vol. 99(C).
    4. Pternea, Moschoula & Haghani, Ali, 2019. "An aircraft-to-gate reassignment framework for dealing with schedule disruptions," Journal of Air Transport Management, Elsevier, vol. 78(C), pages 116-132.
    5. Bezerra, George Christian Linhares & Gomes, Carlos F., 2016. "Measuring airport service quality: A multidimensional approach," Journal of Air Transport Management, Elsevier, vol. 53(C), pages 85-93.
    6. Xu, Yifan & Adler, Nicole & Wandelt, Sebastian & Sun, Xiaoqian, 2024. "Competitive integrated airline schedule design and fleet assignment," European Journal of Operational Research, Elsevier, vol. 314(1), pages 32-50.
    7. Nokhaiz Tariq Khan & Javed Aslam & Ateeq Abdul Rauf & Yun Bae Kim, 2022. "The Case of South Korean Airlines-Within-Airlines Model: Helping Full-Service Carriers Challenge Low-Cost Carriers," Sustainability, MDPI, vol. 14(6), pages 1-19, March.
    8. Sibdari, Soheil & Mohammadian, Iman & Pyke, David F., 2018. "On the impact of jet fuel cost on airlines’ capacity choice: Evidence from the U.S. domestic markets," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 111(C), pages 1-17.
    9. Chandra Mahapatra, Subas & Bellamkonda, Raja Shekhar, 2023. "Higher expectations of passengers do really sense: Development and validation a multiple scale-FliQual for air transport service quality," Journal of Retailing and Consumer Services, Elsevier, vol. 70(C).
    10. Moro, Sérgio & Lopes, Rui J. & Esmerado, Joaquim & Botelho, Miguel, 2020. "Service quality in airport hotel chains through the lens of online reviewers," Journal of Retailing and Consumer Services, Elsevier, vol. 56(C).
    11. Pels, Eric, 2021. "Product differentiation and network optimality," Transport Policy, Elsevier, vol. 110(C), pages 415-429.
    12. Wei, Wenbin, 2008. "A new approach to quantify the benefit to air travelers resulting from airport capacity expansion," Journal of Air Transport Management, Elsevier, vol. 14(1), pages 47-49.
    13. Givoni, Moshe & Rietveld, Piet, 2009. "Airline's choice of aircraft size - Explanations and implications," Transportation Research Part A: Policy and Practice, Elsevier, vol. 43(5), pages 500-510, June.
    14. Pels, Eric, 2021. "Optimality of the hub-spoke system: A review of the literature, and directions for future research," Transport Policy, Elsevier, vol. 104(C), pages 1-10.
    15. Rodríguez-Déniz, Héctor & Suau-Sanchez, Pere & Voltes-Dorta, Augusto, 2013. "Classifying airports according to their hub dimensions: an application to the US domestic network," Journal of Transport Geography, Elsevier, vol. 33(C), pages 188-195.
    16. Zhou, Xuemei & Huang, Huang & Jia, Xinchang & Jiang, Nan, 2014. "Integrated passenger terminal capacity analysis under the capacity constraints of surrounding road network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 414(C), pages 194-203.
    17. A. O. Tomaev & A. S. Kaukin, 2018. "Modeling of the Market of Internal Russian Passenger Air Transportation," Administrative Consulting, Russian Presidential Academy of National Economy and Public Administration. North-West Institute of Management., issue 4.
    18. Mohammadian, Iman & Abareshi, Ahmad & Abbasi, Babak & Goh, Mark, 2019. "Airline capacity decisions under supply-demand equilibrium of Australia’s domestic aviation market," Transportation Research Part A: Policy and Practice, Elsevier, vol. 119(C), pages 108-121.
    19. Birolini, Sebastian & Avogadro, Nicolò & Malighetti, Paolo & Paleari, Stefano, 2024. "Con-Accessibility: Logit-based catchment area modeling for strategic airport system planning," Transportation Research Part A: Policy and Practice, Elsevier, vol. 190(C).
    20. Fageda, Xavier & Flores-Fillol, Ricardo, 2016. "How do airlines react to airport congestion? The role of networks," Regional Science and Urban Economics, Elsevier, vol. 56(C), pages 73-81.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:arx:papers:2503.05754. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.