This research explores the physical infrastructure and flight consolidation efficiency drivers of Eurasian airports regarding their infrastructure and movement productivity levels. A novel Fuzzy Double-Frontier Network DEA (FDFNDEA) model is proposed to investigate the relationship between desirable (freight and passenger turnovers) and undesirable (pollutant emission levels due to aircraft movements) outputs against the respective infrastructure usage, fuel consumed, and movements performed at each of the 23 Eurasian airports from 2000 to 2018. This balance between desirable and undesirable outputs emerges spatially and temporally due to the evolution of the airport system's productive resources at each one of the Eurasian countries over the period observed. Shannon's entropy is used as the cornerstone to quantify the input and output vagueness of this evolution in Triangular Fuzzy Numbers (TFN), thus allowing the accurate building of alternative optimistic and pessimistic double-frontier efficiency. Differently from previous research, Shannon's entropy is the key for measuring input and output vagueness levels in light of the maximal entropy principle. This principle states that the distribution that best represents the current state of knowledge is the one with largest entropy. Maximal entropy yields bias-free decision-making in the sense that the input/output distributional profiles for Eurasian airports contain the maximal possible heterogeneity, working as a robust or best/worst-case scenario against eventual unconsidered assumptions. Hence, optimistic and pessimistic Malmquist Productivity Indexes (MPI) for overall and each stage productivity results are subsequently regressed against contextual variables related to airport characteristics and regional socio-demographic and economic indicators of each Eurasian country using bootstrapped Cauchy regressions. The findings revealed the spatial heterogeneity of productivity factors and airport performance across Eurasia. Results also demonstrated the negative impact of income inequality and the positive impact of private participation on technological progression in the Eurasian airport industry.

这项研究探讨了欧亚机场的物理基础设施和飞行整合效率驱动因素，涉及其基础设施和移动生产力水平。提出了一种新颖的模糊双边界网络DEA（FDFNDEA）模型来研究理想的（货运和旅客周转率）和不理想的（由于飞机移动而造成的污染物排放水平）输出与相应基础设施使用，燃料消耗和执行的移动之间的关系。在2000年至2018年期间，有23个欧亚机场中的每个机场。由于观察期内每个欧亚国家的机场系统生产资源的演变，使得期望和不期望的产出之间的平衡在空间和时间上出现了。香农 s的熵被用作量化此模糊三角数（TFN）中这种演化的输入和输出模糊性的基石，从而可以准确地建立替代的乐观和悲观的双重边界效率。与以前的研究不同，香农的熵是根据最大熵原理测量输入和输出模糊度的关键。该原理指出，最能代表当前知识状态的分布是熵最大的分布。从欧亚机场的输入/输出分布配置文件包含最大可能的异质性的意义上讲，最大熵产生无偏见的决策，可以作为针对最终未考虑假设的健壮或最佳/最坏的情况。因此，随后，使用自举式柯西回归，针对总体和每个阶段的生产率结果的乐观和悲观的马尔姆奎斯特生产率指数（MPI），根据与每个欧亚国家的机场特性以及区域社会人口统计学和经济指标相关的背景变量进行回归。研究结果揭示了整个欧亚大陆生产力因素和机场绩效的空间异质性。结果还证明了收入不平等的负面影响以及私人参与对欧亚机场行业技术进步的积极影响。