دانلود رایگان مقاله عوامل تعیین کننده نوسانات روزانه در حجم مسافر هوایی. اثر رویداد و تعطیلات

abstract

Air traffic flows show large seasonal variability, but arrivals and departures may also be significantly influenced by specific events which generate peaks, which generate peaks rising above baseline traffic. While seasonal variations of air flows are well studied in literature, the daily variations and their causes are seldom analysed and quantified. The paper aims at filling this gap by exploring and quantifying the effect of holidays and events (conferences, trade fairs, sport events) in terms of passenger daily fluctuations. We identified the elements affecting these variations and searched for correlations with daily demand fluctuations using an OLS econometric model applied to Milan Malpensa airport. The model allows one to reproduce the observed daily traffic, identifying the baseline component of traffic (depending on the calendar) and the additional effect ascribable to holidays and occasional events. Results show which types of events generate a visible traffic increase. The effect of some of them can be very significant indeed. The largest international design and fashion shows taking place in Milan generate up to more than 20% extra passenger traffic compared to the normal baseline traffic. In addition, the analysis showed that their effect is not limited to the event days, but impacted on the surrounding days as well. Holidays also influence the patterns of demand, creating additional traffic on certain days and more pronounced peaks, which also differ according to seasons.

6. Conclusions and policy indications

Literature on airport traffic determinants focuses mainly on the total traffic and on the capacity to attract passengers according to exogenous characteristics and the attraction power of the local market. In this paper we tried to understand the factors influencing daily traffic variations, using the case of Milan Malpensa airport. A primary factor determining the variations is, unsurprisingly, the calendar, namely the day of the week and the month; both groups of variables proved to be very significant. We also showed that week patterns change during the summer season, when business traffic decreases and working days (Friday in particular) have systematically less traffic, while Saturdays and Sundays increase due to leisure trips.