航线网络中需求无约束估计的非参数选择模型

A nonparametric discrete choice model for unconstrained demand estimation in airline network

传统的航空客运需求无约束估计方法仅针对平行直达航班中的顾客需求“溢出”和“再现”问题,未能考虑航空网络中直达和中转联程航班之间的网络替代效应.基于顾客偏好排序列表定义了航空网络顾客类型集合,建立了考虑顾客策略行为的网络型非参数离散选择模型.考虑到网络环境下历史预售数据的不完备性,站在线上和线下交易平台的角度,分别建立了非截尾和截尾需求情况下的完备数据对数似然函数.采用E M算法对顾客到达率和概率质量函数进行联合估计,并提出了网络环境下的顾客“初始需求”、“再现需求”和“溢出需求”无约束估计计算方法.通过数值模拟验证了所提方法的可行性和有效性,相较于现有方法能准确反映产品间网络替代效应对顾客选择行为影响,从而更加有效地避免对历史顾客“初始需求”的高估问题.

Traditional unconstrained demand estimation methods in airline industry only address the spillover and recapture problem of customer demand in parallel nonstop flights,and fail to consider the substitution effects in airline networks between direct and connecting flights.Based on the ranking list of customer preferences,customer type set in airline network is defined.Meanwhile,a network nonparametric discrete choice model considering strategic customer behavior is developed.In light of the incompleteness of the historical booking data in network environment,from the perspective of online and offline trading platforms,the complete data log-likelihood functions under the conditions of uncensored and censored demand are established respectively.The EM algorithm is applied to jointly estimating customer arrival rate and the probability mass function.After that,the unconstrained estimation calculation methods of primary demand,recapture demand as well as spillover demand of customers in airline network are proposed.The feasibility and effectiveness of the proposed methods are verified by numerical simulations.Compared with the existing methods,our methods can accurately reflect the impact of substitution effects in networks between products on customer choice behavior,and thereby more effectively avoid overestimating the primary demand of historical customers.