No abstract

As passengers are proved to be preference heterogeneous in air travel, this paper tries to model the air ticket purchase behavior incorporating market segmentation. In the research, a latent-NL model, established on the latent class structure and the nested logit model, integrates the personal features as well as the purchase preferences into the forecast of segment-specific purchase probability. In order to calibrate the model, a stated preference survey is designed with the choice profiles using real service information, and the survey is conducted in four cities in China for data collection. The results show that the proposed model provides an effective approach for predicting the air travel demand in particular for air ticket pricing, and the estimation results outperforms the traditional-nested logit model with higher goodness-of-fit. Besides, the model is then adopted to test the efficiency of different pricing strategies, showing its advantages in improving the flight revenues.

No abstract

Benefiting from the Belt and Road initiative, China experiences the flourishing cross-border trading and tourism. Meanwhile, explosive air transport demand arises in Chinese Bay Area as its strategic position on the Belt and Road. As an important infrastructure in Chinese Bay Area, Hong Kong-Zhuhai-Macao Bridge has connected Zhuhai airport and Hong Kong airport. As a result, we firstly propose a new international transfer mode called “air-bus-air”. In order to identify the target market of “air-bus-air”, a path choice model is established integrating multinomial logit model and latent class model and validated by path choice data. Test results indicate that a latent class model with three segments performs best and this method is effective in improving the accuracy of market segmentation.

No abstract