This study investigates the perception of passengers of airport service attributes, using data from the Skytrax Airport Review websites. Overall, a total of 7358 reviews were collected from the website, together with other related passenger data, namely review headers, passenger types, rating scores of airport attributes and the overall rating. This study focused on investigating each group of passenger types to identify underlying differences amongst airport's passenger segmentation, particularly on the leisure travellers. The study performed different techniques of data analysis including sentiment analysis, lemmatization and partial least square – structural equation modelling (PLS-SEM) to reveal key patterns derived from the available data, which the normal survey data or the interview data may not have revealed. The research contributes to airport passenger segmentation by highlighting the differences found in the travellers segmented by Skytrax. The study also provides practical implications to airport managers.

本研究使用来自 Skytrax 机场评论网站的数据调查乘客对机场服务属性的看法。总体而言，该网站共收集了 7358 条评论，以及其他相关乘客数据，即评论标题、乘客类型、机场属性评分和总体评分。这项研究的重点是调查每一组旅客类型，以确定机场旅客细分之间的潜在差异，尤其是休闲旅客。该研究执行了不同的数据分析技术，包括情感分析、词形还原和偏最小二乘 - 结构方程模型 (PLS-SEM)，以揭示从可用数据中得出的关键模式，而正常调查数据或访谈数据可能没有揭示这些模式。该研究通过突出 Skytrax 细分的旅客中发现的差异，为机场旅客细分做出了贡献。该研究还为机场管理人员提供了实际意义。