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The information and communication technologies of the 21st century use digital user data as a technical tool and aim to increase the efficiency and profitability of industrial production through the use of advanced data analysis technologies. Big data technologies carry out continuous surveillance on internet users and can reach accurate inferences through advanced analysis methods by using data generated by users. The ability of big data analysis techniques to collect and process detailed behavioral data about users raises concerns regarding the privacy and confidentiality of user data. This study, which provides a summary of the developmental stages of data technologies and analyses the dangers contained in these technologies in connection with the ongoing and new dynamics of capitalism, includes a survey of 307 people. The survey consists of questions that measure participants' levels of caution and anxiety regarding their personal and behavioral data, internet usage habits, digital skills, and awareness levels of data privacy breaches. The sample included students selected from the Departments of Sociology, Philosophy and Computer Engineering at Hacettepe University and technology company employees at Hacettepe Teknokent to include three different levels of technological expertise. The study found that participants were also more likely to be concerned about their behavioral and sensitive data as their frequency of daily internet use increased. Users' attitudes to behavioral data vary according to their frequency of daily internet use and the level of expertise of the participants. Participants demonstrated a high level of awareness of online profiling, but the habit of keeping data regarding their online behavior private is not widespread. When the findings are evaluated broadly, it is noted that participants with a limited knowledge of the profiling capacity of data technologies are unable to maintain behavioral data confidentiality. This research has limitations in the context of the sample's capacity to represent the research universe. However, it is thought that it will prove useful in drawing the historical background for the development of big data technologies, analysing this technology within the dynamics of capitalism and in drawing attention to the differences between users' approach to personal data and behavioral data. [ABSTRACT FROM AUTHOR]

Nowadays, the activities of companies started to become more complex and diverse as a result of technological developments and increasing human population. This situation requires the efficient use of companies’ resources. It is important for airline companies to carry out their activities effectively with the help of infrastructural improvements and state subsidies for air transportation in our country. This is particularly important both for sectoral and academic development. The data envelopment analysis (DEA), which is the method of this study, is a multi-criteria decision-making method that measures efficiency by evaluating the data set handled by using common inputs and outputs for enterprises or periods covered. This study was conducted in order to measure the efficiency of activities of the airline companies. In addition, this was done in order to measure the shortcomings of the literature and the efficiency of the airline companies. Within the scope of this study, the activity effectiveness of the two companies which are Turkish Airlines and Pegasus Airlines, operating in our country between 2012 to 2015 was measured by using VZA. As a result of the analysis, information about the activity efficiency of the companies in the relevant years is provided by evaluating the obtained results. [ABSTRACT FROM AUTHOR]

In this study, the efficiency of tea processing factories of General Directorate of Tea Enterprises (Çaykur), which is a Public Economic Enterprise, is investigated using data envelopment analysis (DEA) and data set for the period of 2005-2010. First, efficiency analyses are subjected to the every individual year separately. Then using data set in constant prices, factories' efficiency levels of 2005 and 2010 are compared. Findings show that after 2008, efficiency problems are increased in a numbers of factories and efficiency scores decreased in inefficient factories. Homogeneity with respect to productivity is declined in the same period among the factories. Conclusions of the DEA related to comparison of 2005 and 2010 years prove that productivity problems arise in much more factories and effectiveness scores of those factories worsened. These results indicate that productivity levels of Çaykur tied factories are declined in 2010 compared with 2005 [ABSTRACT FROM AUTHOR]