Air transport has emerged as the foremost choice for travel, both domestically and internationally, in recent times. Enhancements in air transport not only foster the expansion of a country’s industry and international trade but also facilitate convenient, swift and comfortable travel for individuals. Türkiye has notably risen as a pivotal hub for air transport, serving as a strategic crossroads connecting Asia, Africa, America and Europe. It stands as a highly developed nation in both domestic and international passenger and cargo transportation. The significance of an airport is directly proportional to the number of destinations it serves and the frequency of flights it offers. Second airports, particularly those facilitating transfers outside of central airports (hubs), hold significant importance in this regard. These airports are often regarded as transfer hubs, serving as vital conduits for the movement of people and cargo between various locations. Hence, the selection of an airport as a hub holds paramount importance.
In this study, the initial step involved reviewing prior research on the selection of hubs. In their 2002 study, Janic and Reggiani tackled the issue of selecting hub airports for a European Union airline. They employed three distinct methods to address the problem. Seven alternative airport terminals underwent evaluation across nine criteria utilizing Simple Additive Weighting (SAW), Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and Analytic Hierarchy Process (AHP) methods [
1]. In 2013, Jantachalobon and Vanichkobchinda conducted a study aimed at determining the optimal alternative for selecting a regional air transport hub in Southeast Asia, as well as identifying the factors influencing this selection. In their study, the primary objectives were to minimize total transportation costs and reduce travel times [
2]. In 2014, I Casas et al. devised a simulation model to design a new terminal for Barcelona International Airport. Agent-based simulation techniques were also integrated into the simulation methodology. This endeavor has resulted in the system evolving into a decision-making tool for terminal management and dynamic optimization of operations [
3]. In 2015, Çiftçi and Şevkli put forward a mathematical model for the selection of a new hub airport. The model, encompassing over 90 cities in Europe and the Middle East, was applied to three prominent cities in Türkiye: Ankara, Antalya and İzmir. The model considers various factors such as unit passenger revenues, operating costs, distances, occupancy factors and flight times. As a result, Antalya has been identified as a viable airport for the establishment of the new hub [
4]. In the 2018 study by Korani et al., significant factors and criteria were initially identified to evaluate all alternatives for hub airport selection. The criteria were weighted using the AHP method, after which the alternatives were evaluated through Data Envelopment Analysis. This hybrid method has been implemented for Iranian airports [
5]. In Dozic’s 2019 study, 166 articles in the field of aviation published between 2000 and 2018 were analyzed. In this research, studies addressing topics related to airlines, airports, air traffic, etc., and resolved through multi-criteria decision-making methods were categorized. The analysis of the articles revealed that Taiwan leads in studies conducted within the aviation sector, with the AHP method being predominantly utilized among multi-criteria decision-making methods [
6]. In the study conducted by Görçün in the same year, transportation alternatives between Silivri Airport and Sabiha Gökçen Airport were evaluated using the AHP and TOPSIS methods. As a result of the study, four transit transportation alternatives were selected, with speed identified as the most crucial evaluation criterion in this selection process [
7]. In another study by Soylu and Katip in the same year, they focused on the capacity-free multiple P-hub median problem for the location allocation of new hub airports. They put forth exact and heuristic algorithms aimed at determining Pareto bounds for new investment strategies and for minimizing transportation costs within airline networks. Their study revealed that opting for routes with fewer stops is not always cost-effective, as it may lead to an increase in the overall costs within the airport network [
8]. In another study in 2019, Sugianto et al. employed the AHP method to identify parameters for the establishment of a new hub airport. They conducted their study for four international airports in Indonesia. Five criteria were evaluated, and the order of importance was determined for the selection of an airport that could serve as a hub airport. As a result, they found that airport charges and airport costs are the most significant criteria [
9]. In 2020, Aydın and Şeker conducted a study in which they evaluated five airports for the selection of a new hub airport aimed at ensuring low costs. In their study, they employed the Interval-valued Intuitionistic Fuzzy (IVIF) method, the Weighted Aggregated Sum Product (WASPAS) method and the Multi-Objective Optimization (MULTIMOORA) method. Based on twelve evaluation criteria, Antalya Airport was determined to be the most suitable alternative [
10]. In 2022, Zargini’s study also tackled the vector-optimization problem, considering variable dominant and non-dominant solution structures for the selection of a new hub airport. He utilized his proposed approach to evaluate seven airports across seven criteria. As a result of the study, Brussels Airport was identified as the most suitable airport [
11]. In 2023, Badi et al. sought to determine the hub airport and evaluated five airports in North African countries, considering five criteria. A hybrid gray-CODAS (Combined Distance-Based Assessment) method was employed in the assessment. As a result of the evaluation, Morocco International Airport Mohammed V, was identified as the best alternative [
12]. In another study conducted by Taçoğlu et al. in the same year, they undertook an evaluation considering six criteria for the selection of a hub airport. The evaluation encompassed twelve airports in Türkiye, utilizing the Fuzzy AHP method. Following the study, İzmir Airport emerged as the most suitable choice for a hub airport [
13].
In summary, numerous studies have been conducted, employing a variety of methods in the literature for the selection of airport transfer centers. However, there has not been a study that combines the AHP method with MOORA and ELECTRE techniques for airport hub selection, particularly focusing on international airports in Türkiye. MCDM methods offer very effective solutions because they represent a collective mind rather than a single person and are comparable between methods. Using methods together or in a hybrid way plays a major role in increasing the accuracy of the decision. This study can be characterized as novel, as it explores a unique combination of methodologies and considers diverse criteria for airport hub selection. Other parts of the study can be summarized as follows:
Section 2 delves into the methodologies employed and the data utilized, while
Section 3 evaluates the findings, presents a sensitivity analysis and underscores the study’s contributions. Finally,
Section 4 discusses the outcomes of the evaluation and provides recommendations for future research directions.