基于K-均值聚类分析的航班不正常时旅客行为分类

航班不正常是旅客投诉的主要原因之一,也是容易与地面服务人员产生冲突的主要原因之一。帮助地面服务工作人员能快速识别旅客需求、快速响应并满足旅客在航班不正常时的服务抱怨、提高航班不正常时旅客服务质量具有重要意义。为此,构建航班不正常时旅客行为评价指标,通过问卷调查得到旅客行为数据,采用K-均值聚类分析法将航班不正常时旅客分为4类,并筛选出不同类旅客的行为表现指标。

Passenger Behavior Classification of Abnormal Flights Based on K-means Clustering Method

Abnormal flights are one of the main reasons for passenger complaints, and they are also one of the main reasons for conflicts between passengers and ground service. It is important to help ground service staff to quickly identify passenger needs, quickly respond to and meet passengers'' service complaints when flights are abnormal, and improve passenger service quality. Based on this, the passenger behavior evaluation index when the flight is abnormal is firstly constructed, the passenger behavior data is obtained through the questionnaire survey, and K-means clustering analysis method is used to divide the passengers when the flight is abnormal into four categories, and the behavioral performance indexes of different types of passengers are screened out .