Yayın Koleksiyonu (Tüm Bölümler)

Permanent URI for this collectionhttps://acikerisim2.beykoz.edu.tr/handle/20.500.12879/74

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The Political Economy of Housing Financialization in Turkey: Links with and Contradictions to the Accumulation Model
(Routledge Journals, Taylor & Francis Ltd, 2020) Erguven, Emre
Financialization influenced the Turkish economy and housing industry mostly through financial liberalization moves and soaring capital inflows. It both increased household liabilities and mortgage loans dramatically and offered various facilities for the housing industry. Relevant legal regulations not only helped the Turkish housing industry prosper but also eased its integration into the national and global financial system. In addition, political implications constituted a strong motivation for governments to attach special importance to the housing industry. I examine housing financialization as an integral part of the accumulation model of the Turkish economy and argue that the housing industry lies at the very heart of the contradictions of this model. The large-scale capital inflows both intensified the dependency on foreign resources and increased the role of the domestic demand. This is the main contradiction of the accumulation model; it manifests itself in the interest rate dilemma and is also critical for housing financialization in Turkey because the characteristics of this model are especially valid for the housing industry. Moreover, not only do the contradictions of the accumulation model disrupt the housing industry, but also the characteristics of the housing industry contribute to the disruption of this model.
Identifying Effective Variables Using Mutual Information and Building Predictive Models of Sulfur Dioxide Concentration with Support Vector Machines
(Foundation Environmental Protection & Research-FEPR, 2010) Sakar, C. Okan; Kursun, Olcay; Ozdemir, Huseyin; Demir, Goksel; Yalcin, Senay
Sulfur dioxide (SO2) is an issue of increasing public concern due to its recognized adverse effects on human health. Therefore, accurate SO2 prediction models are very important tools in developing public warning strategies. The goal of this study is to identify the relevance of meteorological and air pollutant variables using a classical and widely used measure of dependence, Shannon's Mutual Information (MI), and to build an accurate SO, prediction model using the relevant variables as inputs. Specifically, features ranked by MI measure are tested on how much joint predictive power they have of the target using a popular machine learning tool, support vector machines (SVM), and in comparison to multilayer perceptron (MLP), which is the most commonly used machine learning tool in previous studies for the prediction and analysis of air pollutants. It was found that the SVM model gave a higher correlation coefficient (r) and less root mean squared error (RMSE) than MLP for both test and validation sets. The predictive model used 6 input variables for both data sets as the relevant features for maximum SO, concentration prediction at time t+1, which are the average SO,, maximum SO2, outdoor temperature (OT), average nitrogen dioxide (NO2), average ozone (O-3), and average wind speed at time t. The results of this study indicate that MI can be used efficiently in determining the importance of input variables in the prediction of SO2 concentration and SVM is a popular machine learning tool well suited for use in air pollution modeling.
A New Simulation Modelling Approach to Continuous Berth Allocation
(Taylor & Francis Ltd, 2013) Esmer, Soner; Yildiz, Gokalp; Tuna, Okan
Within the international supply chain and logistics system, ports are an important ring of the basic transport activities. Thus, any shortage in or lack of well-planned orders encountered in the port operation processes is most likely to affect the whole logistic system, which eventually will cause undesirable delays in deliveries. This study aims at developing a simulation modelling approach to continuous berth allocation in Port of Izmir Alsancak, which has continuous quayside with two main wharfs perpendicular to each other. The simulation models which serve to evaluate the proposed modelling approach have been developed in ARENA 10.0 Simulation Software. The results of the conducted computational experiments showed that the proposed modelling approach provides more accurate and realistic estimates of performance measures, such as average berth utilisation, average ship waiting time in a queue, and the average number of ships in queuing up to get container terminals.
Using TOPSIS Method with Laplace Criterion to Select Optimum Airline
(Iura Edition Spol Sro, 2010) Eker, Ipek; Turan, Gokhan; Ergin, Ayfer; Alkan, Guler
In this study, for evaluating subjective features that provides preference of airline companies to others the method TOPSIS has been used. Whilst calculating the weights of the criteria Laplace Criterion had been used. The importance of the study is that this is a unique application in air cargo industry.
Criticality Investigations for the Fixed Bed Nuclear Reactor Using Thorium Fuel Mixed with Plutonium or Minor Actinides
(Pergamon-Elsevier Science Ltd, 2009) Sahin, Suemer; Sahin, Haci Mehmet; Acir, Adem; Al-Kusayer, Tawfik Ahmed
Prospective fuels for a new reactor type, the so called fixed bed nuclear reactor (FBNR) are investigated with respect to reactor criticality. These are (1) low enriched uranium (LEU); (2) weapon grade plutonium + ThO2; (3) reactor grade plutonium + ThO2; and (4) minor actinides in the spent fuel of light water reactors (LWRs) + ThO2. Reactor grade plutonium and minor actinides are considered as highly radioactive and radio-toxic nuclear waste products so that one can expect that they will have negative fuel costs. The criticality calculations are conducted with SCALE5.1 using S-8-P-3 approximation in 238 neutron energy groups with 90 groups in thermal energy region. The study has shown that the reactor criticality has lower values with uranium fuel and increases passing to minor actinides, reactor grade plutonium and weapon grade plutonium. Using LEU, an enrichment grade of 9% has resulted with k(eff) = 1.2744. Mixed fuel with weapon grade plutonium made of 20% PuO2 + 80% ThO2 yields k(eff) = 1.2864. Whereas a mixed fuel with reactor grade plutonium made of 35% PuO2 + 65% ThO2 brings it to k(eff) = 1.267. Even the very hazardous nuclear waste of LWRs, namely minor actinides turn out to be high quality nuclear fuel due to the excellent neutron economy of FBNR. A relatively high reactor criticality of k(eff) = 1.2673 is achieved by 50% MAO(2) + 50% ThO2. The hazardous actinide nuclear waste products can be transmuted and utilized as fuel in situ. A further output of the study is the possibility of using thorium as breeding material in combination with these new alternative fuels. (C) 2009 Elsevier Ltd. All rights reserved.
Feature Selection for the Prediction of Tropospheric Ozone Concentration Using a Wrapper Method
(Taylor & Francis Ltd, 2011) Sakar, C. Okan; Demir, Goksel; Kursun, Olcay; Ozdemir, Huseyin; Altay, Gokmen; Yalcin, Senay
High concentrations of ozone (O-3) in the lower troposphere increase global warming, and thus affect climatic conditions and human health. Especially in metropolitan cities like Istanbul, ozone level approximates to security levels that may threaten human health. Therefore, there are many research efforts on building accurate ozone prediction models to develop public warning strategies. The goal of this study is to construct a tropospheric (ground) ozone prediction model and analyze the effectiveness of air pollutant and meteorological variables in ozone prediction using artificial neural networks (ANNs). The air pollutant and meteorological variables used in ANN modeling are taken from monitoring stations located in Istanbul. The effectiveness of each input feature is determined by using backward elimination method which utilizes the constructed ANN model as an evaluation function. The obtained results point out that outdoor temperature (OT) and solar irradiation (Si) are the most important input features of meteorological variables, and total hydrocarbons (THC), nitrogen dioxide (NO2) and nitric oxide (NO) are those of air pollutant variables. The subset of parameters found by backward elimination feature selection method that provides the maximum prediction accuracy is obtained with six input features which are OT, SI, NO2, THC, NO, and sulfur dioxide (SO2) for both validation and test sets.
The Prioritisation of Service Dimensions in Logistics Centres: A Fuzzy Quality Function Deployment Methodology
(Taylor & Francis Ltd, 2016) Vural, Ceren Altuntas; Tuna, Okan
This study takes a customer focus that prioritises the service-offering dimensions of logistics centres (LCs) by considering potential LC customer expectations. Applying a survey and a quality function deployment methodology to logistics service providers, the study explores, categorises and prioritises LC customer expectations and LC service characteristics. The results indicate that customer preferences mainly prioritise infrastructure, and warehouse and intermodal dimensions. However, when the cost dimension is included, higher utility values are delivered through soft service dimensions like value-added or standard services. LC investors or undertakers can use these results to guide their design of market offerings by using the same methodology to assess expectations in their target markets.
Current State and Future of Shipping and Logistics
(Elsevier Science Bv, 2013) Tuna, Okan; Duru, Okan
Consumer Boycotts as a Consequence of Consumerism
(IGI Global, 2014) Yener, D.
Consumerism is not a new concept for marketing, but it has grown in importance in the recent years. Researchers have studied consumerism from within different dimensions. However, its relationship with consumer boycotts has not been dealt with accurately. A consumer boycott is a type of consumer behaviour in which consumers collectively prefer not to use their purchasing power towards a product, brand, or all products of a country. Motivations for participating in boycotts differ in accordance with various factors such as consumers' beliefs, needs, or attitudes. Being boycotted by consumers may cause economic damage and decreased amount of reputation incurred in return. Organizing a boycott and calling for people's participation is much easier today than it used to be in the past. The Internet, especially social media, is an effective tool to inform people about boycotts and free of charge. However, that does not mean all the information circulating in the Internet is always of a reliable nature. In this chapter, the case of Danone in Turkey is thoroughly analyzed. Danone has been the target of Turkey's biggest Internet smear campaign which resulted in 26% shrinkage in its whole category sales. The aim of this chapter is to examine the case of Danone in Turkey as an example of the relationship between consumerism and consumer boycotts. The research for the case of Danone, which has a special importance in Turkey, uses secondary sources such as the daily newspapers, news pages in Internet, and Danone's web page. © 2014, IGI Global. All rights reserved.
Greening Logistics Centers: The Evolution of Industrial Buying Criteria Towards Green
(Elsevier Science Bv, 2013) Altuntas, Ceren; Tuna, Okan
The rapidly globalizing world trade requires longer supply chains with higher attention on the environmental effects of logistics activities. Latest international conventions related with environmental regulations reinforce governments and corporations to adhere to environmental protection precautions. An effort to decrease the negative environmental effects of logistics activity is the geographical concentration of logistics companies which are called logistics centers. This study aims to provide a green industrial service buying approach for the industrial customers of logistics centers. The study combines green purchasing literature with previousely developed environmental performance indicators (EPIs) and develops a green industrial buying model for logistics centers. The model provides a framework for potential residents of a logistics center and supports their industrial buying processes. The model also serves as an input for green industrial service design in a logistics center.

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