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Öğe Energy-related CO2 emission forecast for Turkey and Europe and Eurasia A discrete grey model approach(Emerald Group Publishing Ltd, 2017) Ayvaz, Berk; Kusakci, Ali Osman; Temur, Gul T.Purpose - The global warming, caused by the anthropogenic greenhouse gases, has been one of the major worldwide issues over the last decades. Among them, carbon dioxide (CO2) is the most important one and is responsible for more than the two-third of the greenhouse effect. Currently, greenhouse gas emissions and CO2 emissions - the root cause of the global warming - in particular are being examined closely in the fields of science and they also have been put on the agenda of the political leaders. The purpose of this paper is to predict the energy-related CO2 emissions through using different discrete grey models (DGMs) in Turkey and total Europe and Eurasia region. Design/methodology/approach - The proposed DGMs will be applied to predict CO2 emissions in Turkey and total Europe and Eurasia region from 2015 to 2030 using data set between 1965 and 2014. In the first stage of the study, DGMs without rolling mechanism (RM) will be used. In the second stage, DGMs with RM are constructed where the length of the rolling horizons of the respected models is optimised. Findings - In the first stage, estimated values show that non-homogeneous DGM is the best method to predict Turkey's energy-related CO2 emissions whereas DGM is the best method to predict the energy-related CO2 emissions for total Europe and Eurasia region. According to the results in the second stage, NDGM with RM (k = 26) is the best method for Turkey while optimised DGM with RM (k = 4) delivers most reliable estimates for total Europe and Eurasia region. Originality/value - This study illustrates the effect of different DGM approaches on the estimation performance for the Turkish energy-related CO2 emission data.Öğe Estimating The Efficiency Of Airports In Turkey: Utilization Of Data Envelopment Analysis And Artifical Neural Network(Ege Univ, Fac Economics & Admin Sciences, 2016) Bolat, Bersam; Temur, Gul T.; Gurler, HaktanEspecially during the last years, both government and private sectors have made investments such as new airports constructions, an expansion of air fleet, and entrance of new firms to aviation sector. These developments in air transport have brought the question whether airports work efficiently. In this study, firstly an efficiency analysis of airports which are located in Turkey is conducted by using Data Envelopment Analysis (DEA). The results of DEA show that 19 airports in 41 airports work efficiently in Turkey. After DEA analysis, we build an Artificial Neural Network model which helps to predict an efficiency of existing and alternative airports by utilizing same data.