Homogeneous service with heterogeneous products: Relationships among airline ticket fares and purchase fences

Tsai, Tsung-Yen

doi:10.1016/j.jairtraman.2016.05.008

Cited by 8 publications

(2 citation statements)

References 59 publications

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“…However, reported by recent literatures, passengers show the distinct classified preference associated with their travel purpose [6], experiences or even demographic characteristics such as age, income, and occupation [7]. So, it is reasonable to believe that the air transportation market is actually composed of groups of passengers whose air ticket purchase preferences are in similarity [8].…”

Section: Introductionmentioning

confidence: 99%

“…According to the results, the multinominal logit model (MNL) and the nested logit model (NL) as well as the mixed logit model have the advantages in predicting the probability of purchasing an air ticket with specific price and other characteristics (such as departure and arrival airports, flight time, and on-time performance) [10,11]. However, the discrete choice models are constructed on the assumption that passengers' preferences are homogeneous, thus the modelling results may overestimate some travelers' price endurance or underestimate others' price tolerance, which may cause the loss in flight demand as well as the profit [7]. erefore, the group identification method, also recognized as the market segmentation method, should be linked to the discrete choice model for predicting the segment-specific air ticket purchase behavior.…”

Section: Introductionmentioning

confidence: 99%

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Modelling the Air Ticket Purchase Behavior Incorporating Latent Class Model

Wang

et al. 2020

Mathematical Problems in Engineering

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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.

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Section: Introductionmentioning

confidence: 99%