機場直接連結的驅動因素

Factors behind Airport Direct Connections

過去十年亞太地區的航空網絡發展迅速，機場連結性顯著成長，對於機場營運者或航空公司而言，了解影響機場航空網路發展背後的驅動力極為重要，可作為日後經營管理策略的參考。本研究旨在探索影響機場直接連結的因素，透過Innovata 2016年航班資料及影響因素變數資料蒐集，彙整建立羅吉斯迴歸（Logistic regression）模式，結果如預期顯示影響機場直接連結的主要正向因素為機場所在國家的競爭力、機場交通量等；相比之下，負面影響因素包括航線距離、航線上潛在中轉樞紐數量等。總體而言，該模式解釋88%航線樣本，代表已能充分解釋機場直接連結與相關因素之間的因果關係，因此該模式可用於評估和開發潛在航線市場，並作為機場管理單位或航空業者決定開發潛在航線之參考。 Over the past decade, air transport networks in the Asia-Pacific region have developed rapidly, and airport connectivity has expanded remarkably; for airport operators and airlines, it might be important to understand the driving force behind this expansion. Thus, this study intends to explore the factors that affect airport network, specifically, the relationship between airports' direct connections and associated factors such as distance between airports, airport traffic, effect of hubs, national carriers' fleet sizes, etc. Using Innovata 2016 flight data and collected factor data, logistic regression models were developed, and as expected, the results showed that the major positive influences on airport direct connections are the competitiveness of the countries and cities where airports are located, airport traffic volume, the primary airports in multi-airport metropolitan areas, and the fleet sizes of home-base carriers. In contrast, the factors with negative effects include route distance, the number of hub airports available along the route, and the secondary airports in multi-airport areas. Overall, the model explained approximately 88% of the route samples, and the findings suggested that the model adequately interpreted the causal relationships between airport direct connections and the associated factors; the model could be applied to develop and evaluate potential airport markets and to promote these potential route markets to candidate airlines.

Over the past decade, air transport networks in the Asia-Pacific region have developed rapidly, and airport connectivity has expanded remarkably; for airport operators and airlines, it might be important to understand the driving force behind this expansion. Thus, this study intends to explore the factors that affect airport network, specifically, the relationship between airports' direct connections and associated factors such as distance between airports, airport traffic, effect of hubs, national carriers' fleet sizes, etc. Using Innovata 2016 flight data and collected factor data, logistic regression models were developed, and as expected, the results showed that the major positive influences on airport direct connections are the competitiveness of the countries and cities where airports are located, airport traffic volume, the primary airports in multi-airport metropolitan areas, and the fleet sizes of home-base carriers. In contrast, the factors with negative effects include route distance, the number of hub airports available along the route, and the secondary airports in multi-airport areas. Overall, the model explained approximately 88% of the route samples, and the findings suggested that the model adequately interpreted the causal relationships between airport direct connections and the associated factors; the model could be applied to develop and evaluate potential airport markets and to promote these potential route markets to candidate airlines.