Does Islamic Banking Contribute to Economic Growth and Industrial Development in Turkey?

This paper aims to identify the effects of Islamic banking on economic growth and industrial development in Turkey. For this purpose, quarterly data for the periods between 2005 and 2016 were taken into the consideration. Additionally, VAR Granger causality analysis was used in this study. It was concluded that Islamic banks\u27 loans do not have a significant effect on the improvement of economy and industry in Turkey. The main reason for this result is that Islamic banking has a very low percentage in Turkish banking sector. Thus, it can be said that Islamic banking in Turkey should be so developed that it can contribute to GDP growth and industrial development

Causality Relationship Between Interest Rate of Deposit Banks and Profit Share Rate of Islamic Banks in Turkey

The popularity of Islamic banking is increasing day by day. On the other hand, some people also criticized this system in some aspect. One of the criticism is that profit sharing rates of Islamic banks are similar to interest rate of deposit banks. While considering this issue, this study aims to identify the causality relationship between profit sharing rate and interest rate in Turkey. Within this scope, monthly, quarterly, 6-months and yearly data for the period between 2000 and 2016 was analyzed separately. In addition to this situation, Toda Yamamoto causality analysis was used in this study so as to achieve this objective. According to the results of the analysis, it was determined that there is a significant causality relationship between these rates. In other words, it was concluded that interest rate of the deposit banks is the main indicator of the profit share rate of Islamic banks in Turkey. The main reason behind this situation is that indicators in the market affect both deposit banks and Islamic banks. Therefore, it is inevitable that deposit rates and profit share rates will be similar when deposit banks and Islamic banks perform in the same market

Assessing the electricity production capacities of emerging markets for the sustainable investments

It is essential to supply the necessary electricity for both the increase in the quality of life of the citizens and the stable growth of the country’s economy. For countries to have energy independence, they need to increase their electricity generation capacity. However, all alternatives required to increase electrical capacity have both advantages and disadvantages. Within this scope, it is not easy for countries to make the right investment decisions. Therefore, a comprehensive analysis is needed to determine the right investment policy. The purpose of this study is to evaluate the electricity production capacities of emerging markets. A new fuzzy decision-making model has been constructed to find a solution for this situation. The groups for the electricity production capacities are examined by the extension of DEMATEL with Quantum Spherical fuzzy sets and golden ratio. In the following stage, emerging seven economies are ranked by using QSF TOPSIS technique. This situation helps to understand which of these countries are more successful in generating electricity capacity effectively. The main novelty is to define the most significant electricity generation alternatives by a novel model that integrates DEMATEL and TOPSIS with QSFSs and golden ratio. The results demonstrate that solar photovoltaic is the most optimal way to increase electricity capacity of the countries. Additionally, China is the most successful emerging country to generate electricity in an efficient way. Countries should take some actions to increase their solar energy investments. First, it would be appropriate to provide tax exemptions to solar energy investors so that the costs of these projects can be decreased. Additionally, investments in solar energy technologies need to be further increased

Non-classical approach to identifying groups of countries based on open innovation indicators

This article aims to highlight various methods and approaches to grouping countries, ac-cording to the behavior of their open innovation indicators. GDP, inflation and unemployment are the most important indicators of the economic and social policies of states, allowing them to be evaluated and models built. To find the relationships between open innovation indicators the paper uses marginal analysis and feature reduction, as well as machine learning methods (shift to the mean, agglomerative clustering and random forest methods). The results showed that, after isolat-ing all groups, the importance of the signs was established and the patterns of behavior of indicators for each group were compared and open innovation dynamics was analyzed. The conclusions showed that it is obvious that increasing the number of variables in the model and using more ex-tensive indicators can greatly increase the accuracy, in contrast to the generally accepted simple classifications. This approach makes it possible to more accurately find the connections between sectors of the economy or between state economies in general. An accompanying result of the study was the clarification of the equality of open innovation indicators for the analysis of their interrela-tionships between countries

Introduction of biofuels as a way of solving ecological problems

Since environmental issues have become a priority for everyone on the planet, and the fact that growing demand for fossil fuels will soon lead to a reduction in world reserves, except for climate change due to their use and greenhouse gas emissions. The aim of this work was to assess the potential for the introduction of biofuels and find the optimal conditions for the enzymatic hydrolysis of Japonica Rice husk. In addition, evaluate the positive and negative consequences because of the use and implementation of this technology. The methodology used variables: substrate FPU, pH, time, temperature and concentration surfactants using the screening construct obtained statistically, all variables are significant. Then an optimization plan was applied for the variables: pH, FPU and time, dropping those with a lower level of significance. Finally, the best conditions found in previous projects were (pH 5.0, 13 h, and 30 FPU/g of substrate); later, these conditions were applied in experiments to assess the effect of an increase in hydrolyzed cellulose. They use 6%; 8% and 10% of pulp is available with a recycling yield of 74%, 42% and 16%. The community has its own interests in the use of biofuels; therefore, this study provides an opportunity for biofuel producers to reduce environmental, economic, and social costs