The adverse effects of the Covid-19 outbreak on airport performance have been noted in many studies, but the determinants of airport productivity in this period still need to be adequately discussed. Identifying performance drivers during the pandemic may offer insights into the efficient management of airports. In this study, the factors affecting airport productivity during the pandemic were revealed, and the performance sources were explained with attention to network centrality (indegree, outdegree, clustering coefficient, betweenness, and eigenvector), both in the domestic and international context. To do that, the Fixed Proportion Ratio was applied to measure the performances of Turkish airports from 2017 to 2020. Next, Malmquist Productivity Index was used to calculate the technical and technological changes in productivity. Finally, Gradient Boosting Modeling was employed to test the impacts of network centrality measures and other contextual variables on total factor productivity. Results revealed that international networks lost their importance, while domestic networks were the major drivers of airport productivity during the pandemic outbreak. Accessible airports with robust domestic connections (represented by high clustering coefficient and indegree centrality) were less vulnerable in this period.

中文翻译：

---

大流行病爆发中的机场生产力和网络中心地位：土耳其机场的经验教训

许多研究都指出了 Covid-19 疫情对机场绩效的不利影响，但这一时期机场生产力的决定因素仍需要充分讨论。识别大流行期间的绩效驱动因素可能有助于深入了解机场的高效管理。在这项研究中，揭示了大流行期间影响机场生产力的因素，并解释了绩效来源，同时关注国内和国际背景下的网络中心性（入度、出度、聚类系数、介数和特征向量）。为此，采用固定比例比率来衡量土耳其机场 2017 年至 2020 年的绩效。接下来，使用马姆奎斯特生产力指数来计算生产力的技术和技术变化。最后，采用梯度提升模型来测试网络中心性度量和其他上下文变量对全要素生产率的影响。结果显示，在疫情爆发期间，国际网络失去了重要性，而国内网络是机场生产力的主要驱动力。在此期间，具有强大国内联系（以高聚类系数和内度中心性为代表）的无障碍机场的脆弱性较小。