Bu çalışmada, havayolu yolcu taşımacılığı sektöründe faaliyet göstermekte olan şirketlerin birbirleri arasındaki göreceli lojistik performans düzeylerinin belirlenmesine yönelik bir araştırma gerçekleştirilmiştir. Şirketlerin lojistik performanslarını belirlemek için verimlilik, fiyat, yönetim, maliyet ve hizmet kalitesi boyutları esas alınmış ve bu ana boyutları temsil eden 11 alt boyut çalışmaya dahil edilmiştir. Çalışmaya dahil edilen alt boyutlar; birim operasyon maliyeti, işgücünün verimliliği, uçuş filosunun verimliliği, yolcu doluluk oranı, zamanında kalkış, güvenlik, frekans sayısı, ortalama bilet fiyatı, gelirdeki artış oranı, net kar marjı, pazar payı verileri olarak belirlenmiştir. Çalışmada kullanılan veriler, ilgili şirketlerin yıllık finansal raporlarından, Sky Trax tarafından hazırlanan havacılık istatistiklerinden ve açık kaynaklardan elde edilmiştir. Çalışmada kullanılan kriterlerin ağırlık oranları ise havacılık sektöründe faaliyet gösteren şirketlerde yöneticilik yapan uzman kişiler ile yapılan görüşmelerin yanı sıra Shannon's Entropi yöntemi ve basit ağırlıklandırma ile elde edilmiştir. Kriterler üç farklı ağırlık oranına göre TOPSIS yöntemi kullanılarak analiz edilmiştir. Araştırma sonucunda, sektörde faaliyet gösteren şirketlerin lojistik performansları analiz edildiğinde birinci ve ikinci sırada bulunan şirketlerin çok küçük bir fark ile değiştiği sonucuna ulaşılmıştır. Kriterlerin, uzman görüşü ve entropi yöntemi ile ağılıklandırılması sonucu elde edilen çözümde ise lojistik performans sıralamasının aynı olduğu görülmüştür. Fakat kriterlerin ağırlıkları basit ağırlıklandırma yöntemi ile eşit alındığında sıralamanın değiştiği tespit edilmiştir.

At the end of 2019, COVID-19 first appeared in China and quickly spread throughout the world. Globally, the pandemic has had a negative impact on numerous industries. Similarly, this epidemic has had an impact on financial markets. This study examined the time period between March 11, 2020, when the first case was seen in Turkey, and May 23, 2022, when the pandemic measures were largely lifted. In this research, we examine the relationship between stock returns and liquidity, volatility, and exchange rate returns in Turkish stock markets by using the Markov Switching Method. The study aims to research the relationship between stock exchange return, stock exchange volatility, liquidity, and foreign exchange rate return; and to research the movement characteristics of selected variables in different regimes during the Covid-19 period. By analyzing the results within the scope of the findings, a general evaluation was given in the last section. According to the results, it has been observed that there is a negative correlation between BIST-100 index return with volatility and exchange rate return, while there is a positive correlation between BIST-100 index return and liquidity. Furthermore, it has been determined that the movements of the data in the examined period occurred within the framework of two different regimes. It has been observed that the probability of BIST-100 index return, volatility, and exchange rate returns to remain in the same regime is high, and the probability of switching from one regime to another is relatively low. For market liquidity, it has been determined that both the probability of staying in the same regime and the probability of switching to another regime are close to each other.

The purpose of this study is to establish a reliable model for predicting the financial failures of the Technology Sector enterprises traded in the BIST 1 year in advance. For this purpose, the previous studies on financial failure and predicting financial failure were examined first, then the concept of financial failure and its reasons were discussed. Then the theory of financial ratios and the use of logistic regression analysis techniques in predicting financial failure are explained theoretically. In the last part, the financial ratios of the companies in the Technology Sector traded in the BIST and the financial success and failure categories of the companies were analyzed and evaluated. As a result of the evaluation, it was determined that the financial success situations of the enterprises increased estimation power 1 year ago.

Developing technology and population growth increase energy demand. The limited natural resources and their negative environmental effects increase the interest in alternative energy sources. The decrease in oil resources and the environmental problems caused by these resources have increased the studies for electric vehicles. This study presents descriptive statistics on the charging station locations for electric vehicles and relationships between studies by author, country, citation, and occurrence. This will provide a way for researchers to obtain detailed information about their studies into the locations of electric vehicle charging stations. This study examined 212 studies in the “Web of Science” database from 2011 to 2022. Network analysis was conducted in this research using the Vosviewer and R software. In this context, descriptive statistics are first provided. In the section on descriptive statistics, basic facts about the studies are shown along with the annual scientific output, the most productive countries, the total number of citations per country, country collaboration, the most productive countries and authors, and the total number of citations per country. Since the second half of 2010, there has been an increasing trend in the number of publications on the positioning of electric vehicle charging stations. It is seen that most of the studies on the positioning of electric vehicle charging stations were also carried out in China, India and the USA. The analyses of document co-occurrence, bibliographic coupling, and co-citation are presented in the second section. It has been observed that the most frequently used keywords in studies related to the location of electric vehicle charging stations are optimization, sustainability and distribution systems.