Turkish Airports Research Articles

Airport Ground Optimizer (AGO): A decision support system initiative for air traffic controllers with optimization and decision-aid algorithms

The growing global air traffic has necessitated more efficient ground management in airports, especially during peak hours. Current approaches mainly consist of radar-based systems and radio communications, which provide limited visual assistance. Hence, Decision Support Systems (DSS) are designed to assist human Air Traffic Controllers (ATCos) by providing reliable recommendations based on current data and situations. The Airport Ground Optimizer (AGO) is a DSS designed for ATCos to manage the complexities of ground traffic in airports. It is based on advanced optimization algorithms and intuitive user interfaces, offering an enhanced operational experience. AGO uses mixed-integer programming (AGO-MIP) and stochastic programming (AGO-STC) to detect conflicts based on expected gate release and taxi times, and then optimizes the entire schedule to minimize hold fuels, resolve conflicts, and reduce fuel consumption, emissions, and delay times. Its key strength lies in translating complex mathematical solutions into user-friendly visual representations. AGO's core functionality includes comprehensive visualizations such as position charts, delay graphs, and potential conflict maps, providing a clear, real-time picture of ground operations for informed decision-making. AGO's queue and gate occupancy analysis calculates and visualizes the maximum queue length and concurrent number of aircraft at gates, enhancing airport capacity, reducing aircraft waiting times, and streamlining ground traffic flow. Simulated in a high-traffic Turkish airport layout, AGO-MIP demonstrated significant improvement in operational efficiency compared to traditional First Come First Served (FCFS) approach. AGO outperformed the traditional FCFS approach, reducing hold fuel by 27.9%, cutting delay time by 21.6%, lowering HC, CO, and NOx emissions by 16.4%, 22.5%, and 29.3% respectively, and decreasing the maximum queue length and its duration by 15.3% and 26.6%, as well as decreasing the number of delayed aircraft by 4.8%. The AGO-STC is also tested using pushback release uncertainties in the case airport, providing robust and feasible sequences, clear feedback for all possible scenarios, and detailed outcomes for each scenario. The study concludes by discussing potential developments and current issues of the tool in detail.

Predictive Modeling of Flight Delays at an Airport Using Machine Learning Methods

Flight delays represent a significant challenge in the global aviation industry, resulting in substantial costs and a decline in passenger satisfaction. This study addresses the critical issue of predicting flight delays exceeding 15 min using machine learning techniques. The arrival delays at a Turkish airport are analyzed utilizing a novel dataset derived from airport operations. This research examines a range of machine learning models, including Logistic Regression, Naïve Bayes, Neural Networks, Random Forest, XGBoost, CatBoost, and LightGBM. To address the issue of imbalanced data, additional experiments are conducted using the Synthetic Minority Over-Sampling Technique (SMOTE), in conjunction with the incorporation of meteorological data. This multi-faceted approach ensures robust forecast performance under varying conditions. The SHAP (SHapley Additive exPlanations) method is employed to interpret the relative importance of features within the models. The study is based on a three-year period of flight data obtained from a Turkish airport. The dataset is sufficiently extensive and robust to provide a reliable foundation for analysis. The results indicate that XGBoost is the most proficient model for the dataset, demonstrating its potential to deliver highly accurate predictions with an accuracy of 80%. The impact of weather factors on the predictions is found to be insignificant in comparison to scenarios without weather data in this dataset.

Airport productivity and network centrality in the pandemic outbreak: Lessons from the Turkish airports

The adverse effects of the Covid-19 outbreak on airport performance have been noted in many studies, but the determinants of airport productivity in this period still need to be adequately discussed. Identifying performance drivers during the pandemic may offer insights into the efficient management of airports. In this study, the factors affecting airport productivity during the pandemic were revealed, and the performance sources were explained with attention to network centrality (indegree, outdegree, clustering coefficient, betweenness, and eigenvector), both in the domestic and international context. To do that, the Fixed Proportion Ratio was applied to measure the performances of Turkish airports from 2017 to 2020. Next, Malmquist Productivity Index was used to calculate the technical and technological changes in productivity. Finally, Gradient Boosting Modeling was employed to test the impacts of network centrality measures and other contextual variables on total factor productivity. Results revealed that international networks lost their importance, while domestic networks were the major drivers of airport productivity during the pandemic outbreak. Accessible airports with robust domestic connections (represented by high clustering coefficient and indegree centrality) were less vulnerable in this period.

Optimizing passenger experience: A technological preference analysis in Turkish Airports

Aviation-oriented companies are continuously seeking innovative approaches to enhance the passenger experience and operational efficiency within the industry. The objective of this study is to evaluate the categorization of passengers' technological preferences in Turkish airports. The objectives of this study are to enhance the understanding of Aviation Companies in Turkey regarding the technology preferences of passengers and their fundamental needs, as well as to analyze the characteristics of passengers that are directly linked to their technological choices. This study employs purposive sampling with a sample size of 455. Various statistical techniques, such as regression, correlation, and descriptive statistics, are employed to analyze the data. The findings indicate that biometric technology, personal device utilization, customisation and customization, as well as streaming and on-demand entertainment, greatly influence the technological preferences of travelers. Nevertheless, contactless solutions, inflight Wi-Fi, and mobile apps and digital services do not influence the technological preferences of travelers.

Ambient air quality assessment at the airports based on a meteorological perspective.

Natural mineral dust episodes elevate particle concentrations and eventually decrease air quality. Air pollutant emissions from aircraft, airport ground operations, and long-range dust transport are producing problems for the aviation sector. Dust transport from the Sahara Desert, one of the primary dust sources globally, significantly affects the eastern Mediterranean basin, including Türkiye. This study investigates the effect of long-range dust transport on particulate matter (PM) concentrations at Turkish airports. Three different approaches were used to analyse dust episodes in the study area. Firstly, routine reports of meteorological conditions at the airports were investigated. For this purpose, airport routine meteorological reports (Metar) and aviation-selected special weather report (Speci) codes, recorded at 11 airports from 2012 to 2021, were used to determine the dust episode days. Secondly, the hourly PM measurement dataset was analyzed from the closest air quality monitoring stations to the airports. Finally, regional atmospheric model results and backward-trajectory analysis were used to validate the dust episodes and determine the dust origin. Results showed that 163 dust episodes occurred during the study period, 17% from North Africa and 12% from the Mediterranean region.

Measurement of Process-Performances of Turkish Airports Using Network Data Envelopment Analysis

The air transportation industry is continuously broadening by adding new airports operating with huge investments. Hence, increasing efficiency and productivity in this industry is becoming critical. At the same time, efficiency calculations are also an important tool used to identify weaknesses and contribute to the improvement of the performance of enterprises. Nevertheless, Classic DEA models are commonly insufficient to determine the efficiency of a system due to ignorance of its internal structure and the treatment of the system as a black box. Therefore, if a production system can be divided into subprocesses by using network DEA model, the results will be more plausible and satisfying. Within this scope, this paper aims to evaluate the efficiencies of 39 out of 56 airports in Türkiye from 2015 to 2019. The results indicate that less-populated airports managed by private entrepreneurs are more efficient than others. Moreover, another characteristic of these efficient airports is that they are both domestically and internationally preferred for leisure trips.

An investigation of the effects of sand and dust storms in the North East Sahara Desert on Turkish airports and PM10 values: 7 and 8 April, 2013 events.

Between April 7 and April 10, 2013, a cyclone with a value of 995hPa that developed in the central Mediterranean transported dust from the Sahara Desert towards Turkey. At 13 airports in Turkey, dust haze and widespread dust were seen during different occasions in this period and caused the observation of so-called "Blowing dust events." This cyclone blew dust towards the Cappadocia airport, and the prevailing visibility decreased to 3800m, making it the lowest value measured during the transition of this cyclone. In this study, Aviation Routine Weather Report (Metar) and Aviation Selected Special Weather Report (Speci) observations of airports in North Africa and Turkey were evaluated for the period between April 3 and April 11, 2013. With this cyclone the prevailing visibility at Benina Airport in Libya decreased to 50m on April 6, 2013. This study aims to evaluate long-distance dust transport's effects on meteorological visibility at airports in Turkey and examine the episodic changes of PM10 values measured by air quality monitoring stations. Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model outputs were used to determine the trajectories of long-distance dust particles. Powder red, green, and blue (RGB) and Moderate Resolution Imaging Spectroradiometer (MODIS) satellite images, Cloud-Aerosol LIDAR Infrared Pathfinder Satellite Observations (CALIPSO) images, the Barcelona Supercomputing Center-Dust Regional Atmosphere Model (BSC-DREAM8b) outputs, and Global Forecast System (GFS) synoptic maps were used for analysis. In addition, PM10 values obtained from air quality monitoring stations were examined. According to the data obtained from the CALIPSO images, the dust concentration on the Eastern Mediterranean reaches up to 5km. The episodic values obtained from certain air quality measurement stations are Adana 701, Gaziantep 629, Karaman 900, Nevşehir 1343, and Yozgat 782µg/m3 on an hourly average.

An Investigation and Benchmarking Model for Developing Sustainable Material Use Among Turkish Airport Operators

Sustainable material use refers to the capacity of a material to be utilized in a way that does not deplete the Earth’s natural resources or harm the ecosystem. This lowering might entail employing renewable or recyclable materials and reducing the overall quantity of material utilized in airport services. Renewable materials, recyclable materials, biodegradable materials, reusable materials, low-impact materials (low-emission materials), natural materials, and non-toxic materials are sustainable materials used in airports. There are 58 civil airports operated in Turkiye. The public information on the airport operators’ websites can assess sustainable material use in these airports. Mentioned 58 airports are operated under ten different airport groups. This study offered a novel scoring system called CACS which stands for Clarity, Accessibility, Continuity, and Suitability, to retrieve sustainable material use from sustainability reports of airport operators. The model proposed in this paper will help the readers benchmark a group of airports not present in the literature. The results show that İGA airport is the highest score among the ten airports, followed by TAV airports at 820.6 and 256.3, respectively. The top five airports encapsulate 97.44% after the Normalization of passenger counts of Turkiye. Airport operators’ sustainable material usage and other sustainability benchmarking on numerous domains based on sustainability reporting systems would draw the public and increase awareness, allowing operator firms and airport authorities to concentrate on creating a more livable future.

Determinants of Market Structure and Demand: A Panel Data Study on Turkish Airports

The aim of this research is to reveal the factors that determine the number of airlines at the airport and the demand for the market. In addition, another objective of the research is to reveal the market structure and the changes in the market structure using concentration measurement tools is another research purpose. The twenty-eight airports in Turkey were examined by panel data analysis between the years 2007-2018. Regarding the market structure in general, decreases have been observed in the concentration values over time. In other words, airports have become more competitive over time. The panel data results show that the number of airlines at airports is strongly influenced by the number of passengers in the relevant market, the city’s GDP, the number of university students, the number of visitors, and the hub airport. On the other hand, it is evident that the number of airline carriers operating in the relevant market, the city’s GDP, its population, the number of university students, the presence of a hub airport, and the number of tourists have a substantial impact on the demand at airports. Results obtained in this research will contribute to the literature by providing new models of market structure and demand. It is thought that the research will guide airline companies and airport managers in terms of predicting demand. Key Words: Airports, Panel Data, Air Travel Demand, Market Structure, Competition. JEL Classification: L11, L93, R41

Impacts of travel bans and travel intention changes on aviation emissions due to Covid-19 pandemic.

The online version contains supplementary material available at 10.1007/s10668-023-02916-8.

Endogenous and exogenous sources of efficiency in the management of Turkish airports

This paper focused on the endogenous and exogenous factors affecting the performance of small and medium-sized Turkish airports. A two-stage approach was adopted. Non-radial DEA methodology was applied in the first step to define the specific endogenous sources in the resource utilization, output production, and revenue generation processes. Shannon's entropy was employed to capture the homogeneity in the endogenous performance drivers. Exogenous sources of efficiency were defined in the second step. Results showed that inefficiency in Turkish airports is mainly driven by endogenous sources, where runway utilization and non-aeronautical revenue generation are the main reasons. Policy implications were derived.

The evaluation of operational efficiencies of Turkish airports: An integrated spherical fuzzy AHP/DEA approach

The demand for air transport services has significantly increased around the globe, which has brought new investments in airports, which, in turn, requires in-depth efficiency analysis of these capital-intensive endeavors. This study examines the operational efficiencies of 46 Turkish civil airports from 2015 to 2018. We employ a novel hybrid methodology that combines Spherical Fuzzy Sets based Analytic Hierarchy Process (SFS-AHP) and Data Envelopment Analysis (DEA), which provides a solid basis for efficiency analysis. To this end, it can handle the hesitancy and uncertainty that the subjective evaluation process of input and output factors possess. Then, we use Self Organizing Maps (SOM), a machine learning method for clustering, to examine the effect of outlier airports on the efficiency scores. Finally, a posthoc analysis is conducted with Tobit regression model to assess the explanatory power of external factors on the efficiency scores, i.e., tourism potential, number of international flights, distance to the city center, population, public/private ownership, and age of airport. The findings show that 67.2% of the Turkish airports operate below the optimal efficiency level, and 93.5% of them should make considerable efforts to refine their operations by implementing managerial and structural changes to reduce input factors. The results also suggest that the airports located in high-density touristic areas achieve higher efficiency levels. Those relatively closer to the city center lead to more airport traffic, generating more revenues. Thus, both factors have a significant impact on efficiency scores. The study provides a novel efficiency analysis framework for airport operators and policy makers that helps them make informed decisions.

Network Centrality and Efficiency in Turkish Airports: A Hybrid Network DEA

Network Centrality and Efficiency in Turkish Airports: A Hybrid Network DEA

Structural and operational management of Turkish airports: a bootstrap data envelopment analysis of efficiency

This paper explores the structural and operational dimensions of the efficiencies of airports. The two-stage procedure is suggested to assess the efficiencies of airports in this study. In the first-stage, Classification and Regression Tree, which is one of the machine-learning approaches used to divide the airports into homogeneous and thus comparable sub-groups. In the second stage, the bootstrap data envelopment analysis approach obtains more precise structural and operational efficiency scores. To illustrate the proposed framework use, we applied it to a real case associated with Turkish airports. The results demonstrate that this framework presents a more comprehensive assessment of airport performance rather than conventional data envelopment analysis models. Moreover, it provides to show the deficiencies of the structural and operational management of airports. The findings can help anywhere airport authorities as well as Turkish airport authorities.

The determinants of air passenger traffic at Turkish airports

Investigating the determinants of air passenger traffic has become commonplace. In contrast with most previous publications, this paper investigates these determinants in an emerging country, Turkey, at the provincial level between 2004 and 2014. We find that GDP/capita, population, distance to alternative airports, tourism, leading cities, and international migrations all support more air traffic. Furthermore, market concentration is associated with less traffic, and the presence of academics with more traffic. Mapping models' residuals suggest catchment areas, surface transport options, domestic migrations and (geo)politics could also matter. Accordingly, it appears the determinants of Turkey's air passenger traffic do not differ from those of developed economies. The results also suggest new airports should be built based on the aforementioned factors.

Public-private partnerships in airports: the Turkish experience

Public-Private Partnerships (PPPs) have become a prevalent method to fund transport infrastructure around the world. PPPs have emerged in airports as an alternative to public airports and complete privatisation of airports. PPPs in airports have a history of 25 years in Turkey. This paper aims to provide an up-to-date review of PPP experiences in Turkish airports. With a case study design, PPPs in Turkish airports are examined in the context of policy, legal grounds, and implementations. PPPs are the main method adopted especially in the funding and operation of new airports and/or terminals in Turkey. Besides the successes, there are also areas to be improved regarding PPP design and implementation. More transparent, comprehensive, and structured contract terms, proper risk assignment, more accurate demand forecasting, and efforts to overcome certain public interest concerns are identified as the main requirements for future policy actions.

Exploration of the adverse effects of shift work in a multicultural environment.

Given that shift work spreads across many different business sectors, studies of its adverse effects are very topical. Much research has been done on the negative impact of shift work, but many researchers have not focused on its impact in a multicultural environment. The aim of this study was to map out how shift work is perceived by workers in two different shift regimes and two national groups. The research was carried out on Czech manufacturing workers and Turkish airport ground personnel using a questionnaire. The impact of shift work was studied from physical, mental, social and health aspects with connection to family status and gender. For statistical evaluation, Pearson's chi-squared test of independence was used. The effect of shift work on workers' performance and scrap rate was analysed only on the sample of the manufacturing workers. Fifty-five Czech male workers, 49 Turkish male workers and 60 Turkish female workers participated in the survey. The dependence between sexes was confirmed for mental aspects and sleeping routines. The main difference between nationalities is in work attitude, social aspects and sleeping routines. According to the family status, the difference was confirmed in all areas except social aspects. The lowest values of productivity and the highest scrap rate were observed on night shifts and the maximum productivity and lowest scrap rates were observed on afternoon shifts. Some of the basic assumptions were confirmed which suggests that a multicultural environment has an influence on the perception of shift work by the nations and gende.

Exploration of the adverse effects of shift work in a multicultural environment.

Given that shift work spreads across many different business sec-tors, studies of its adverse effects are very topical. Much research has been done on the negative impact of shift work, but many researchers have not focused on its impact in a multicultural environment. The aim of this study was to map out how shift work is perceived by workers in two different shift regimes and two national groups. The research was carried out on Czech manufacturing workers and Turkish airport ground personnel using a questionnaire. The impact of shift work was studied from physical, mental, social and health aspects with connection to family status and gender. For statistical evaluation, Pearson's chi-squared test of independence was used. The effect of shift work on workers' performance and scrap rate was analysed only on the sample of the manufacturing workers. Fifty-five Czech male workers, 49 Turkish male workers and 60 Turkish female workers participated in the survey. The dependence between sexes was confirmed for mental aspects and sleeping routines. The main difference between nationalities is in work attitude, social aspects and sleeping routines. According to the family status, the difference was confirmed in all areas except social aspects. The lowest values of productivity and the highest scrap rate were observed on night shifts and the maximum productivity and lowest scrap rates were observed on afternoon shifts. Some of the basic assumptions were confirmed which suggests that a multicultural environment has an influence on the perception of shift work by the nations and gende.

A hybrid AHP/DEA-AR model for measuring and comparing the efficiency of airports

PurposeThe purpose of this paper is to employ an efficiency analysis and compare the efficiency scores of publicly or privately operated airports in Turkey.Design/methodology/approachThis study uses analytic hierarchy process, which is one of the widely known multi-criteria decision-making methods to calculate the relative weights of input and outputs. This study also uses data envelopment analysis and assurance region (AR) method to calculate the efficiency scores of airports at the empirical analysis stage.FindingsThe empirical results reveal that DEA-BCC and DEA-CCR methods produced almost the same efficiency scores, and 14 airports were found as efficient. Also, AR method was employed and under this method, it was only two airports operated by the private sector that were found as efficient. None of the publicly operated airports was found as efficient.Practical implicationsThe main practical implication of this study is that publicly operated airports must improve their efficiency levels in Turkey. This situation indicates that the government policy for the aviation sector must be changed. It is not a coincidence that all publicly operated airports are inefficient. To cope with this situation, it may be a useful policy that establishes a regional airport system or applies the privatization process to all airports.Originality/valueThe most significant contribution of this study to literature is that the AR method, which was never used before in a single country’s airport performance evaluation study, was applied for the first time. Also, this technique was applied first time to Turkish airports for measuring their efficiency levels.

Modeling regional routes with Greek airlines for flight operations to AOE airport

PurposeResearch carried out within the scope of the present new emerging optimum market to Greek regional airlines. This study (based on interconnected flight network) aims to provide an optimal alternative for flights to be carried out by small Greek airlines to Eskisehir Airport in Turkey. The airlines seek to sustainable demand base to improve themselves in a profitable way.Design/methodology/approachIn this study, the analytical network process method was used. In the construction of network models, specific criteria have been considered, and the analysis has been accomplished as multi-criteria decision-making problem because of the relationship and interaction between them. A number of professionals with high knowledge of the Greek and Turkish aviation market were participated in the study.FindingsBoth Greek and Turkish experts think that the scenarios should include more airports (multi leg flights) to benefit from the increased traffic from all these destinations. Although, the model showed that more sustainable and effective routes are the simplest ones (single leg flights). Thus, the experts suggested the following five routes: Athens (ATH)-Antalya (AYT)-Eskisehir (AOE)-ATH; Heraklion (HER)-AOE-ATH; ATH-Istanbul (IST)-AOE-Thessaloniki (SKG); ATH-AOE-Cologne (CGN)-ATH and ATH-AOE-Izmir (ADB)-CGN-ATH. In addition, the experts pointed out the routes Eskisehir (AOE)-Brussel (BRU) and AOE-Cologne (CGN), as the passenger demand for them is high. These are considerable suggestions and should be examined by airlines’ managers, while aviation authorities should take these under consideration.Research limitations/implicationsThere are some factors that limit the potential extension of the small Greek regional airlines to Eskisehir airport. Istanbul’s Atatürk International Airport is the most used airport for international connected flight in Turkey, and the most airlines prefer this as a destination airport, although it has slots limitations and intense traffic. According to a previous project, sustainable flight network may include Istanbul and Izmir. Also, the bilateral agreement between Greece and Turkey according to Memorandum of Understanding between the Aeronautical Authorities of the Republic of Turkey and Hellenic Republic consists the main limitation of the traffic increase.Practical implicationsConnected flight network model suggestions developed in this research may provide contribution to airlines’ research and development activities. Also this kind of studies may contribute to the increase of the passengers’ traffic between the two countries with mutual benefits.Social implicationsBased on the current study, with determined the grid network flights, new flights can be scheduled that are offering significant benefits. Also passengers will have the ability to travel to an attractive destination. In particular, the study may positively contribute to the further development of AOE and to the region around the city. On the other side, the Greek regional airlines can find an important market. Anadolu University’s entrepreneurship ability will be improved and also AOE’s business will be increased. This study will enforce the stronger links between both Greek [Hellenic (Greek) Civil Aviation Authority] and Turkish (General Directorate of Civil Aviation) aviation authorities. In addition, this study may contribute to the improvement of the economic relations between Greece and Turkey with mutual benefits.Originality/valueIt is thought that this research shows Greek and Turkish airports feasibility to cooperate providing benefits to passengers, airlines and the countries’ economies. The study includes current social, economic and cultural dynamics of the countries making significant contribution to academic literature. The capacity and demand analysis is useful for the management of the specific Greek carriers. Expert opinions are consulted over the course of taking strategic decisions. The analysis has been conducted, based on expert opinions and referred to for these pairwise comparisons. Airlines and airport managers based on the suggested methodology may examine potential flights, although more numerical data are necessary.