Nowadays, the aviation technology has become much reliable than ever, and air transportation is by far the best choice for long distance transportation. Airports serve as the flight nodes for air transportation, and the construction and development of airports are often considered as the most important development plans of the entire country or the local government. The huge amount of cost for constructing an airport and the long (usually more than fifty years) life cycle demand a comprehensive plan in the initial stage of an airport construction. Underestimating the transportation demand of the airport may make it difficult to extend the airport in the future and affect its subsequent operations. On the other hand, overestimating the transportation demand of the airport may result in over-investment and poor operation performance. Around the world, airports are often considered as enterprises. The governments and airport administrators have begun to pay attention to the operation performance of airports and adopt every indicator of the conduct in order to carry on the performance assessment. By doing so, they hope to reduce the operating cost, increase profit, and enlarge their competition advantages. Of the indicators of the operation performance, yearly enplanement has widely been considered as a key indicator. This research collected the data pertaining to commercial airports in the mainland of the United States whose yearly enplanements are over 2,500 passengers. It employs statistical method and decision tree to analyse the relationship between the population change of the metropolitan (population, density of population, population change, etc.) and the yearly enplanement change of airports. Also, we discuss the relationship among the number of airports in a metropolitan, the distance from an airport to the closest business center, the distance from the airport to another nearest airport, and the yearly enplanement change of the airport.

Post deregulation, many U.S. airlines created hubs with banked schedules, however, in the past decade these same airlines began to experiment with depeaking their schedules to reduce costs and improve operational performance. To date there has been little research that has investigated revenue and operational shifts associated with depeaked schedules; yet understanding the trade-offs among revenue, costs, and operational performance at a network level is critical before airlines will consider future depeaking and related congestion-management strategies. This study develops data cleaning and analysis methodologies based on publicly available data that are used to quantify airport-level and network-level revenue and operational changes associated with schedule depeaking. These methodologies are applied to six case studies of airline depeaking over the past decade. Results show that depeaking is associated with revenue per available seat mile (RASM) increasing slower than the rest of the network and the industry as a whole. Depeaking is associated with improved operations for both the depeaking airlines and competitors. Airports benefit from increases in non-aeronautical sales associated with connecting passengers spending more time in the terminal. The underlying reasons driving airlines' scheduling decisions during depeaking vary greatly by case. Results from the study provide insights for airlines that are considering depeaking and the airports which are affected. The results suggest that losses in RASM and no improvement in operations could potentially lead an airline to repeak, and that RASM is prone to fall when a strong competitive threat exists.