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Exploring factors affecting airport selection during the COVID-19 pandemic from air cargo carriers’ perspective through the triangular fuzzy Dombi-Bonferroni BWM methodology

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  • Tanrıverdi, Gökhan
  • Ecer, Fatih
  • Durak, Mehmet Åžahin

Abstract

The COVID-19 pandemic has created unexpected demand for air cargo in terms of rapid mobility of critical basic needs. Air cargo carriers aim to maximize their profits by taking advantage of the current demand and using their limited capacity in the right place. At this point, some of the qualifications of the airports in the places where demand plays a crucial role in this decision of the carriers. Thus, evaluating the factors considered in the airport selection for air cargo carriers during the COVID-19 period is curious. This study proposes a triangular fuzzy Dombi-Bonferroni best-worst method (BWM) framework with vast flexibility to establish the priority preferences of factors considered in selecting airports. The fuzzy BWM model becomes a superior decision support system by combining the Bonferroni mean operator's ability to consider interrelationships between attributes and the flexibility of the Dombi operator. In this sense, we highlight eighteen criteria based on five airport aspects: location, physical features, performance, costs, and reputation. Findings reveal that the foremost aspects are location and costs, whereas the most crucial factors are airport charges and handling charges. The study suggests that airports should follow a low-price policy for airport-related charges without compromising their sustainability to have a share of the increasing number of air cargo flights, especially during the COVID-19 period, when airline passenger flights are decreased. The study is crucial in deciding the strategy and policy of air cargo carriers and airports during the pandemic period.

Suggested Citation

  • Tanrıverdi, Gökhan & Ecer, Fatih & Durak, Mehmet Åžahin, 2022. "Exploring factors affecting airport selection during the COVID-19 pandemic from air cargo carriers’ perspective through the triangular fuzzy Dombi-Bonferroni BWM methodology," Journal of Air Transport Management, Elsevier, vol. 105(C).
  • Handle: RePEc:eee:jaitra:v:105:y:2022:i:c:s0969699722001211
    DOI: 10.1016/j.jairtraman.2022.102302
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    1. Sun, Xiaoqian & Wandelt, Sebastian & Zhang, Anming, 2023. "A data-driven analysis of the aviation recovery from the COVID-19 pandemic," Journal of Air Transport Management, Elsevier, vol. 109(C).
    2. Fatih Ecer & Tolga Murat & Hasan Dinçer & Serhat Yüksel, 2024. "A fuzzy BWM and MARCOS integrated framework with Heronian function for evaluating cryptocurrency exchanges: a case study of Türkiye," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 10(1), pages 1-29, December.
    3. Deveci, Muhammet & Erdogan, Nuh & Pamucar, Dragan & Kucuksari, Sadik & Cali, Umit, 2023. "A rough Dombi Bonferroni based approach for public charging station type selection," Applied Energy, Elsevier, vol. 345(C).

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