The main objective of this project is to set up a knowledge-based ecosystem for young cryptocurrency traders. The project also aims to monitor the current market behavior of leading cryptocurrencies based on cost and benefit criteria to examine the relative importance of the technical and economic determinants before crafting and executing an effective trading strategy. 

Research team aims at using real-life data to provide a solution for the load and balance problem of Turkish Airlines in their cargo department. The solution will be based on optimization with the use of a mathematical framework of mixed-integer linear programming formulation of the aircraft container loading. This model is preferred to the currently used manual or semi-manual methods as it will provide an optimal solution to the problem and shall ensure faster loadings with more safety in terms of airplane balancing, optimum utilization of airplane cargo space, and less consumption of fuel. This shall ensure an increase in revenue, reduction in cost, and survival of the cargo unit of Turkish Airlines as a profitable cargo company for the future. The project is conceptualized as an initial step of a more advanced project that comprises developing a software tool for Turkish Cargo that will be used for solving load and balance problem by cargo professionals.

dThis project examined the operational efficiencies of 46 Turkish civil airports from 2015 to 2018. Researchers employed 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, PR team 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 has been 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 showed 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 provided a novel efficiency analysis framework for airport operators and policy makers that helps them make informed decisions.

Crafting and executing the best cryptocurrency mining strategy is vital to succeeding in cryptocurrency market investments. This study aims to identify the best cryptocurrency mining strategy based on service providers’ performance for cryptocurrency mining using a hybrid analytics approach, which integrates the Analytic Hierarchy Process (AHP) and Fuzzy-TOPSIS techniques, along with sensitivity analysis. The results show that hosted mining is the overall best cryptocurrency mining strategy, followed by home mining and cloud mining, based on both total cost of operations and cryptocurrency payout criteria. The empirical findings also suggest that the critical features of the highest performing service providers (i.e., hosted mining strategies and cloud mining) were their flexibility of contracts and the superior efficiency in terms of the daily payout. Finally, of the three location alternatives for home mining, Turkey ranks first compared to the U.S. and Europe.