Bayesian network (BN) is an efficient graphical method that uses directed acyclic graphs (DAG) to provide information about a set of data. BNs consist of nodes and arcs (or edges) where nodes represent variables and arcs represent relations and influences between nodes. Interest in organic food has been increasing in the world during the last decade. The same trend is also valid in Turkey. Although there are numerous studies that deal with customer perception of organic food and customer characteristics, none of them used BNs. Thus, this study, which shows a new application area of BNs, aims to reveal the perception and characteristics of organic food buyers. In this work, a survey is designed and applied in seven different organic bazaars in Turkey. Afterwards, BNs are constructed with the data gathered from 611 organic food consumers. The findings match with the previous studies as factors such as health, environmental factors, food availability, product price, consumers' income and trust to organization are found to influence consumers effectively.

This study aims to reveal the structure of the European Airport Network (EAN) using concepts from complex network theory by utilising 2019 passenger data collected from Eurostat. Initially, the EAN was explored by computing connectivity and centrality measures and their correlations. The community structure of the EAN was also examined by modularity maximisation using the relatively new Leiden algorithm. When the network was compared with simulated models, it was observed that the EAN had small-world and scale-free properties. To measure the hub performance of the airports, their binary betweenness centrality was compared with a weighted betweenness measure employing the ratio of geographical distance to passenger traffic between the nodes. A significant difference was observed between the two centrality measures.

We present two innovative functional partial quantile regression algorithms designed to accurately and efficiently estimate the regression coefficient function within the function-on-function linear quantile regression model. Our algorithms utilize functional partial quantile regression decomposition to effectively project the infinite-dimensional response and predictor variables onto a finite-dimensional space. Within this framework, the partial quantile regression components are approximated using a basis expansion approach. Consequently, we approximate the infinite-dimensional function-on-function linear quantile regression model using a multivariate quantile regression model constructed from these partial quantile regression components. To evaluate the efficacy of our proposed techniques, we conduct a series of Monte Carlo experiments and analyze an empirical dataset, demonstrating superior performance compared to existing methods in finite-sample scenarios. Our techniques have been implemented in the ffpqr package in .

Violence against women is a significant sociological problem that negatively affects society. Although violence against women is widespread worldwide, the help-seeking behavior of women exposed to violence remains underdeveloped. In this study conducted in Turkey, the formal help-seeking behavior of women exposed to violence was studied according to sociodemographic factors. Data were obtained from surveys on domestic violence against women from the Turkish Statistical Institute (TURKSTAT), which was held in 2008 and 2014. Chi-square and binary logistic regression analyses are used in this study. The dependent variable is determined as whether women who had experienced violence sought help from formal institutions. In order to explain the dependent variable, education, age group, region, and sociodemographic variables are used. According to the results, as the education level of women exposed to violence increases, help-seeking behavior through official means also increases. In addition, women with a personal income are more likely to seek formal help than those without, and the development of the sociocultural region inhabited affects the formal help-seeking behavior of women exposed to violence. Between 2008 and 2014, legal regulations on women’s rights in Turkey were seen to positively affect formal help-seeking behavior. Although the formal help-seeking behavior of women subjected to violence in 2014 increased significantly compared to 2008, this improvement is not sufficient.

Purpose: This study aims to investigate the determinants of Foreign Direct Investment (FDI) for the 55 countries from 4 different continents and 3 different development levels. Method: A panel dataset is constructed over the period of 1995-2019 with 17 candidate independent variables and Bayesian Model Averaging (BMA) is employed for each continent and for each development level to reveal the determinants of FDI. Results: Results showed that globalization is the primary factor to attract FDI regardless of the development level and continent. But there are also other factors that affect FDI which differ based on the development level and geographic location of the country. FDI in transition economies benefits from qualified labor force which negatively affects developed countries and has no effect on developing countries. Corruption is only effective in developing countries. Secondary education is effective at European and Asian countries, tertiary education is effective on American countries. This study contributes the literature by using a BMA method in a panel data context. BMA uses weighted average of all the possible models which gives more balanced results than a single model. Applying BMA to the countries in different continents and development levels separately allows to make inferences based on region and wealth. Originality: This study used a fairly large dataset on terms of selected time period, number of countries and selected variables which most of the studies lack of. Also, the advantage of applying BMA to a panel dataset, is obvious as both controls the cross section variation and also considers a weighted average of all possible linear regression results rather than giving only a single linear regression model result. Thus applying BMA on a panel dataset give a better insight as to which variables should be considered as determinants of FDI.

Turkish businessmen, politicians and most academicians tend to see foreign direct investment (FDI) as a remedy for the chronic lack of capital accumulation in Turkey. The meagre FDI inflows which followed the Customs Union Agreement with the European Union, in 1995, created a deep disappointment among these people. Efforts to attract foreign capital have intensified since 2005 and inflows have soared. However, the greater part of the increase is the result of the Turkish government's privatization programme of publicly owned companies, and the acquisition of private firms by large multinational companies, rather than greenfield investments. This research investigates FDI inflows to Turkey and tries to estimate the transfer of profits.