Economic growth is a phenomenon that increases the welfare level of both individuals and societies. In the historical process, some of the economies of different sizes have grown faster, while others have grown more slowly. The most obvious reason for the difference can be shown as the faster progress of some countries in terms of industrialization and technological progress. In this study, it is aimed to estimate the economic growth rates of OECD countries with different economic sizes by using fuzzy and multiple regression analysis. In this direction, the Gross Domestic Product (GDP) growth rate of the countries for 2020 is considered as the dependent variable, and the Covid-19 mortality rates, interest rates, tax rates and savings rates as independent variables. R program was used for analysis. In the study, economic growth rates were estimated with fuzzy and multiple linear regression methods. Considering the literature, the h value was taken as 0.01, 0.5, 0.9, respectively, and the fuzzy regression method estimates 106 were obtained. MSE, RMSE and MAE values, which are the performance criteria of the models, were used to determine the appropriate model. When the performance values of the models were compared, it was found that the values were quite close to each other. However, it was observed that the performance criterion values of the multiple linear regression model were slightly smaller.
Her geçen gün gelişen ve değişen bir kavram olan e-ticaret, Covid-19 salgını ile birlikte tüm dünyanın ortak paydası haline gelmiştir. Covid-19 pandemi döneminde, internet ve mobil teknolojilerin kullanımının yaygınlaşması tüketicilerin hayatlarının pek çok noktasında olduğu gibi alışveriş deneyimlerinde de değişiklik yaratmış ve e-ticaret uygulamaları hızla benimsenmiştir. Değişen tüketim ve yaşam biçimleri giderek daha fazla sayıda tüketiciyi sanal ortama dahil etmiştir. Bu çalışmanın amacı Covid- 19 salgını sürecinde kullanımı artan e-ticaret sitelerinin tercih edilme nedenlerini belirlemektir. E-ticaret sitelerinde çok çeşitli ve farklı kategorilerde ürün bulunduğu için tüketicilerin e-ticaret sitesi tercih nedenlerinin değişiklik gösterebileceği göz önüne alındığında elektronik ve giyim alışverişi olmak üzere iki farklı kategoride Türkiye’de yaşayan 18 yaş ve üzeri 415 kişiye çevrimiçi (online) anket uygulanmıştır. Anketlerden elde edilen veriler derlenerek katılımcıların e-ticaret sitelerini tercih etme nedenleri Saklı Markov modeli kullanılarak belirlenmiştir. Çalışmadan elde edilen sonuçlara göre tüketicilerin bir sonraki elektronik ve giyim alışverişlerinde yani iki farklı kategoride de en yüksek olasılıkla tercih edecekleri e-ticaret sitesi Trendyol’dur. İki kategoride de Trendyol e-ticaret sitesinin ‘Daha güvenli alışveriş imkanı (D_1)’ nedeniyle tüketiciler tarafından tercih edileceği belirlenmiştir.
Poverty, a problem that has existed throughout the history of humanity and sought a solution, is a phenomenon that is struggled under the joint responsibility of world states, national and international organizations. As a result of the positive and economic developments after the World War II, with the implementation of social spending programs, a transition to a systematic structure has been achieved in the struggle against poverty. In this study, a panel data set covering the period 2004-2018 for 23 countries was constructed to examine the impact of international aid on per capita income. The study results show a positive relationship between the international aid, population, and human development index and per capita gross domestic product at the 5% significance level, a negative relationship between the unemployment rate and the Gini coefficient and per capita income at the 5% significance level. If the international aid increases by 1%, the per capita income increases by 0.08%, if the population increases by 1%, the per capita income increases by 1.45%, if the value of human development increases by 1%, the per capita income increases by 1.60%. If the unemployment rate increases by 1%, per capita income decreases by 0.15%; if the Gini coefficient increases by 1%, the per capita income decreases by 0.63%.
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