Check-in is the process that passengers wait for the most before their flight. Waiting times of passengers will vary depending on the number of counters at the airport, the number of self-service facilities, and whether passengers benefit from online/mobile check-in technologies. As a result of the measures taken at airports with the Covid-19 pandemic, check-in processing times have been prolonged. In this study, Esenboğa airport domestic departure check-in operations are simulated with the ARENA-TRIAL simulation program. The developed scenarios were simulated at peak hours. Initially, it was determined that the number of employees and facilities should be increased to keep the service level at standards during the Covid-19 pandemic thanks to the optimum number of facilities obtained. Secondly, it was determined that the time spent by passengers for check-in processes increased significantly during the Covid-19 pandemic. In addition, it has been observed that the placement of the optimum number of self-bag drop facilities at the airport reduced the average waiting time required for the check-in processes of passengers in the period before and during Covid 19. Finally, during the Covid-19 pandemic, the airport queue density has increased dramatically.

Businesses provide various marketing strategies in order to gain a competitive advantage and achieve sustainable profitability in today's globally competitive environment. While some of these strategies are realized through traditional marketing methods, some of them are implemented through digital marketing applications. The continuous and rapid change in information and communication technologies has made it obligatory for businesses to reconsider their marketing strategies and activities. In the literature, there are various studies conducted with multi-criteria decision-making methods in order to measure the marketing performance of businesses. However, there is no study conducted with these criteria specific to airline companies' marketing performance. The criteria determined as a result of the literature review were analyzed using the fuzzy-AHP and Fuzzy-BWM methods for weight determination, and the TOPSIS method for alternative selection which are among the multicriteria decision-making techniques. As a result of the study, net profitability, load rate, and total passenger number criteria came to the fore among other criteria, evaluations were made for the 6 airline companies examined, and the best and the worst alternative airline companies were determined, and evaluations were made in terms of marketing strategies. As a result, an exemplary application was introduced to airline companies in order to improve their marketing strategies and performances, and inferences that could contribute to future studies were made in the literature.

Purpose: This study aims to reduce the fuel costs, which constitute the largest share of total cost that airline companies have, with extra fuel transportation. Methodology: A nonlinear programming model has been developed for tankering application that takes advantage of the different fuel prices at the airports. General Reduced Gradient Method (GRG) is used to solve the generated nonlinear programming problem. MS EXCEL solver add-in is used to solve the problem. Findings: In the application part of study, two application has been studied on and one of them is parametrical and other assumes Istanbul as an hub airport in order to analyze the effect of flight distance, load rate, fuel price difference between the airports and altitude of cruise flight on tankering and cost. It has been observed that the fuel cost can be saved when tankering is applied to flight distances of 1300nm and less. Although the load rate is high and the fuel price difference is low, flights have been conducted between the centers which have short flight distances, the model allowed to tanker. It was observed that when the amount of fuel recommended by the problem result was taken for the designed scenarios, the fuel consumption increased by 2.5-3% compared to the trips without tankering. Despite the increase in fuel consumption, it has been found that a total fuel cost can be saved of 1% to 47% for round trips. Originality: The efficiency of the original optimization model created with non-linear modeling was developed and tested for various scenarios.