دانلود رایگان مقاله اثر ورود حامل کم هزینه بر مدل تقاضای Airport pairs با رویکرد تمرکز بازار

abstract

The trend of open sky policies and growth of low-cost airlines, the topic of airport-pairs demand is gradually being addressed in the golden aviation circle of Northeast Asia. The variety of flight services among the four major metropolises with dual-airport systems leads to a competition-cooperation relationship existing between various airports and airlines. Therefore, this study investigates the causal relationship between the route-level passenger demand and influential factors using aggregate data collected through website observations. The empirical study focuses on direct flights of airport-pair routes among Taipei, Shanghai, Seoul, and Tokyo. Results of the passenger regression model indicate that frequency, code-share, and morning flights have positive impacts on increasing passenger numbers for airlines. Further, the market concentration degree of Herfindahl-Hirschman Index and entry effect of low-cost carriers are important for the route-level passenger demand. In addition, routes with departures and arrivals in hub airports have a considerable attraction relative to other airport-pair routes. Finally, the proposed passenger model performs well in predicting market share, especially for routes with high demand.

5. Conclusion

This study adopted a regression analysis method to construct the monthly demand model of airlines passengers for airport-pairs routes. As there no complete database for the aviation market, this study collects passenger demand and the influential variables via CAA statistics and the website-observation method. The main purpose is not only investigating the impacts of these variables, such as airfare, frequency, and airport capacity, but also examining the effects of market power and LCC entry. Furthermore, this study also validates the performance of model prediction by calibrating and validating samples. Several important results and insights are summarized below. First, this study successfully constructed a passenger regression model within the constraint of scarce dataset in aviation demand and influential variables. Using the website-observation method, the results of regression model indicated that flight factor signifi- cantly affects the demand of airlines passengers through flight frequency, code-share flight, and the ratio of morning flight. Airfare and punctuality are another two influential flight factors, where the latter is only significant for non-hub departure airports. Another important insight is the significance of H2H variable. It implies that flights with departures and arrivals in hub airport have a strong positive impact on all airport-pair routes. It is observed that flights’ frequency of origin and destination airports is still more effective than the factor of airport access. In addition, third-party LCCs receive more passenger demand than the LCCs of destination city owing to its reputation.