Tanrıverdi Gökhan, Ecer Fatih, Durak Mehmet Şahin
Department of Aviation Management, Ali Cavit Çelebioğlu School of Civil Aviation, Erzincan Binali Yıldırım University, Yalnızbağ Campus, Erzincan, 24000, Turkey.
Department of Business Administrative, Faculty of Economics and Administrative Sciences, Afyon Kocatepe University, ANS Campus, 03030, Afyonkarahisar, Turkey.
J Air Transp Manag. 2022 Oct;105:102302. doi: 10.1016/j.jairtraman.2022.102302. Epub 2022 Sep 16.
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.
新冠疫情在关键基本需求的快速运输方面引发了对航空货运意想不到的需求。航空货运承运人旨在利用当前需求并将其有限运力用在恰当之处,从而实现利润最大化。在这一点上,需求在承运人这一决策中发挥关键作用的地区的机场的一些资质就很重要。因此,研究新冠疫情期间航空货运承运人选择机场时所考虑的因素很有意思。本研究提出了一个具有极大灵活性的三角模糊Dombi - Bonferroni最佳 - 最差方法(BWM)框架,以确定机场选择中所考虑因素的优先偏好。模糊BWM模型通过结合Bonferroni均值算子考虑属性间相互关系的能力以及Dombi算子的灵活性,成为了一个卓越的决策支持系统。从这个意义上说,我们基于机场的五个方面突出了十八个标准:位置、物理特征、性能、成本和声誉。研究结果表明,最重要的方面是位置和成本,而最关键的因素是机场收费和装卸费。该研究表明,机场应在不损害可持续性的前提下,对与机场相关的收费采取低价政策,以在日益增多的航空货运航班中分得一杯羹,特别是在新冠疫情期间,此时航空公司的客运航班减少。该研究对于在疫情期间决定航空货运承运人和机场的战略与政策至关重要。