Modeling the Change of the Turkish Air Transport Network (THUA): Dynamic Spatial - Complex Network Approach

Öz

The aviation industry is a capital-intensive industry with high-quality social capital and high technology. For this reason, it is of strategic importance for both national and regional economies. Air transport networks are able to attract domestic and foreign investments to the regions by the settlement of the complementary sectors of the aviation industry, as well as the passengers, cargo, and information they circulate. The Turkish Air Transport Network (THUA) has a history of almost a century started in 1930 and continues to grow today with the world's largest airport and a global flag carrier. In this context, this article models the change of THUA for each year in the 2012-2017 period using spatial-complex network analysis, estimates the effects of socio-economic and network criterion-based dynamics on the probability of a new connection between airports in THUA using machine learning models and reveals important results. Although the THUA is a sparse network, it tends to be concentrated. New ties are not formed randomly between nodes, on the contrary, they are formed between certain airports. Income and population, as well as degree centrality and clustering coefficient, increase the likelihood of a new link between airport pairs.

Anahtar Kelimeler

• Turkey Air Transportation Network
• Spatial Network Analysis
• Complex Network Analysis
• Machine Learning

Türkiye Hava Ulaşım Ağı’nın (THUA) Değişiminin Modellenmesi: Dinamik Mekânsal - Karmaşık Ağ Yaklaşımı

Öz

Havacılık sektörü yüksek ve kaliteli sosyal sermaye ve yüksek teknoloji içeren sermaye yoğun bir sektördür. Bu nedenle hem ülke ekonomileri hem de bölge ekonomileri için stratejik önem arz etmektedir. Hava taşımacılığı ağları dolaşımını sağladıkları yolcu, yük ve bilginin yanı sıra havacılık sektörünün tamamlayıcısı sektörlerin bölgelerde yerleşmesiyle yerli ve yabancı yatırımları da bölgelere çekebilmektedirler. Türk Hava Ulaşım Ağı (THUA), 1930'da başlayan neredeyse bir asırlık bir geçmişe sahiptir ve bugün dünyanın en büyük havalimanı ve küresel bir bayrak taşıyıcısı ile büyümeye devam etmektedir. Bu bağlamda, bu makale THUA’nın 2012-2017 periyodunda her yıl için mekânsal-karmaşık ağ analizlerini kullanarak değişimini modellemekte, makine öğrenmesi modelleri kullanarak THUA’da havalimanları arasında yeni bir bağın oluşum olasılığına sosyo-ekonomik ve ağ ölçütü tabanlı dinamiklerin etkilerini tahmin etmekte ve önemli sonuçlar ortaya koymaktadır. THUA her ne kadar seyrek bir ağsa da yoğunlaşma eğilimindedir. Yeni bağlar düğümler arasında rastlantısal olarak oluşmamakta aksine belirli havalimanları arasında oluşmaktadır. Gelir ve nüfus ve ayrıca derece merkeziliği ve kümelenme katsayısı havalimanı çiftleri arasında yeni bir bağın oluşma olasılığını arttırmaktadır.

Anahtar Kelimeler

• Türkiye Hava Ulaşım Ağı
• Mekânsal Ağ Analizi
• Karmaşık Ağ Analizi
• Makine Öğrenmesi

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