针对现有易感染者-已感染者-已恢复者(susceptible-infected-recovered,SIR)模型未考虑机场网络的拓扑结构对航班延误传播影响的问题,基于复杂网络理论计算机场网络的拓扑特征指标,利用熵权优劣解距离(technique for order preference b...
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针对现有易感染者-已感染者-已恢复者(susceptible-infected-recovered,SIR)模型未考虑机场网络的拓扑结构对航班延误传播影响的问题,基于复杂网络理论计算机场网络的拓扑特征指标,利用熵权优劣解距离(technique for order preference by similarity to ideal solution,TOPSIS)方法评估各个机场的综合重要度,将全部机场分为若干个类,据此建立不同类别机场航班延误传播的改进SIR模型,并求解模型的传播阈值;以2023年中国机场网络为例,将全部机场划分为5类,并用改进的SIR模型仿真不同初始条件下机场的航班延误传播。结果表明:改进的SIR模型在仿真延误传播时更具适用性;机场的综合重要度越高,延误传播范围越广、速度越快、恢复周期越长;当多个机场的航班发生延误时,E类机场的延误传播能力明显提升;机场网络拓扑结构对延误传播具有抑制性,延误难以波及全部机场。改进的SIR模型展现了机场重要度对延误传播的差异化影响,为航班延误管理策略的制定提供了参考。
文章以新疆机场集团为研究对象,选取2013~2023年间的16个机场作为效率分析的目标,运用数据包络分析(DEA)方法,结合BCC模型以及Malmquist指数,从静态和动态两个维度对机场集团的运营效率进行了全面评估。研究结果表明:(1) 乌鲁木齐地窝堡国际机场(URC)和库尔勒机场(KRL)作为核心枢纽,其综合效率、技术效率和规模效率均表现优异。(2) 塔什库尔干机场(HQL)和奇台机场(JBK)等支线机场的效率值较低,表明其在资源配置、技术水平和规模匹配方面存在较大提升空间。(3) 技术进步(TC)是效率提升的主要驱动力,尤其是在博乐机场(BPL)和阿勒泰机场(AAT)中表现显著,而乌鲁木齐地窝堡国际机场(URC)和喀什机场(KHG)的效率下降则可能与规模过大、资源配置不合理或区域经济波动有关。This paper takes Xinjiang Airport Group as the research object, selects 16 airports from 2013 to 2023 as the efficiency analysis targets, uses data enveloping analysis (DEA) method, combines BCC model and Malmquist index, and comprehensively evaluates the operational efficiency of the airport group from both static and dynamic dimensions. The results show that: (1) Urumqi Diwopu International Airport (URC) and Korla Airport (KRL), as the core hubs, have excellent performance in comprehensive efficiency, technical efficiency and scale efficiency. (2) The efficiency values of regional airports such as Tashkourgan Airport (HQL) and Qitai Airport (JBK) are low, indicating that there is a large room for improvement in terms of resource allocation, technical level and scale matching. (3) Technological progress (TC) is the main driving force of efficiency improvement, especially in BPL and Altai Airports (AAT), while the efficiency decline of Urumqi Diwopu International Airport (URC) and Kashgar Airport (KHG) may be related to excessive scale, unreasonable resource allocation or regional economic fluctuations.
本研究以新疆机场集团为研究对象,采用基于松弛的DEA (SBM-DEA)模型,结合非期望产出(如碳排放和旅客投诉量)和财务数据,全面评估了新疆17个机场2013年至2023年的运营效率。研究结果表明:1) 2013年至2019年期间,大部分机场的运营效率较高,尤其是在2016年、2018年和2019年,部分机场的效率值接近或达到1,表明资源配置和运营管理较为合理。2) 受新冠疫情影响,几乎所有机场在2020年和2021年的效率值均显著下降,尤其是2020年,效率值普遍低于0.5。3) 随着疫情逐渐得到控制,部分机场在2022年和2023年的效率值有所回升,尤其是乌鲁木齐地窝堡国际机场和喀什机场的效率值迅速恢复至1,显示出较强的恢复能力和较高的运营管理水平。Taking Xinjiang Airport Group as the research object, this study comprehensively evaluated the operational efficiency of 17 airports in Xinjiang from 2013 to 2023 by using a slightly-based DEA (SBM-DEA) model, combined with unexpected outputs (such as carbon emissions and passenger complaints) and financial data. The results show that: 1) During 2013 to 2019, the operation efficiency of most airports is relatively high, especially in 2016, 2018 and 2019, the efficiency value of some airports is close to or reaches 1, indicating that resource allocation and operation management are reasonable. 2) Due to the impact of the COVID-19 epidemic, almost all airports have significantly decreased their efficiency values in 2020 and 2021, especially in 2020, the efficiency value is generally lower than 0.5. 3) With the epidemic gradually under control, the efficiency values of some airports rebounded in 2022 and 2023, especially the efficiency values of Urumqi Diwopu International Airport and Kashgar Airport quickly recovered to 1, indicating strong resilience and high level of operation and management.
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