The intensity of small-business owners and the environmental difficulties they encountered were investigated as predictors of growth intentions in Turkey. Data were collected from 526 small businesses in 14 major cities using the Entrepreneurial Profile Questionnaire. Factor analysis showed environmental difficulties and growth intentions to be multifactor constructs, while intensity emerged as a single factor. A canonical correlation analysis found owner intensity to be significantly related to the three growth plan factors of technology improvement, resource aggregation, and market expansion. Among the difficulty factors, only lack of know-how and financing problems showed a significant relation to growth plans. Financing difficulties hindered technological improvement and resource aggregation, while know-how negatively affected market expansion. Other difficulty factors such as entry barriers, family-business role conflict, and ethnic prejudice were not among the predictors of growth plans. The article draws out the implications of these findings for government policy and for future research.
Purpose The purpose of this paper is to investigate empirically the main factors that affect the house prices in Izmir, Turkey using the quantile regression and ordinary least square approaches. Design/methodology/approach Sample data about the housing market for Izmir collected from the web pages of various real estate agencies during June 2018. Following this, the quantile regression method is used to estimate all possible effects of variables on each interested quantile to determine the factors that affect house prices to guide the potential consumers, house developers, city planners and the policymakers in Izmir, Turkey. Findings Results show that the age of the house, central heating and parking have no significant effect on prices. The size of the house, the existence of an elevator, fire and security have a positive and significant effect on prices. The number of rooms has lower values for high-priced houses, while the floor, the number of balconies, air conditioning, proximity to schools have a higher value for high-priced houses. The number of toilets, the number of bathrooms and the distance to the hospital have a lower value on the high-priced housing. The value of the distance from the city center and the shopping center is almost uniform in all quantiles and lowers the value of the higher-priced houses. With the exception of the value of the houses in the 10th percentile in Balcova district, the value of the houses in Konak, Balcova and Narlidere is lower prices in Karsiyaka. Originality/value This is the first comprehensive research to determine the major factors that affect house prices in Izmir. The second contribution of this paper is that it includes all possible variables and accordingly derives adequate policy implications, which could be used both by the public housing authority and private housing constructing companies in designing and implementing effective housing policies.
The main objective of this paper is to evaluate empirically the existence of a budgetary trade-off between military, education and health expenditures in Turkey for the time period 1925-1998. Development economists, peace and defense economists and political economists have extensively investigated the existence of a trade-off between military, education and health spending since the 1970s. However, the literature review reveals that it is hard to establish a general theory of budgetary trade-off between military, education and health spending and make this applicable for all cases. This is mostly due to economic, social, political, and historical differences among the countries Moreover, it is likely that different research techniques, different time periods analyzed may produce different results. As a result of this, researchers have found a variety of outcomes regarding the trade-off between defense-education and health expenditures. This study presents a brief literature review within the framework of trade-offs between defense-education and health expenditures and also concentrates on theoretical model development. The discussion will center on developing a multi-variable single equation regression model and presenting estimable forms of equations.Turkey, Defense Expenditure, Health Expenditure, Educational Expenditure,
PurposeThe purpose of this paper is to analyze empirically major factors that affect housing prices in Istanbul, Turkey using the classification and regression tree (CART) approach.Design/methodology/approachThe data set was collected from various internet pages of real estate agencies during June 2007. The CART approach was then applied to derive main results and to make implications with regard to the housing market in Istanbul, Turkey.FindingsThe CART results indicate that sizes, elavators, existance of security, existance of central heating units and existance of view are the most important variables crucially affecting housing prices in Istanbul. The average price of houses in Istanbul was found to be 373,372.36 New Turkish Liras. The average size of a house was 138.37 m2. The average age of houses is 15.07 years old with the average number of rooms being 3.11. The average number of baths is 1.43 and average number of toilets is 1.22. Only 5 percent of homes have storage space, 45 percent of homes have parking space, 64 percent of homes are heated with furnace, whereas only 29 percent of homes are used central heating system. Among the 31 variables employed in this study, it was concluded size, elavator, security, central heating unit and view are the most important factors that have impact on housing prices in housing market in Istanbul.Practical implicationsFuture research and analysis of housing market in Istanbul and in Turkey can benefit from the method used in this study and findings derived from this research to come up with more general model(s) to include more houses in a wide range of regions in Turkey to analyze the determinants of housing prices in Turkey in general.Originality/valueExamining housing prices using the CART model is relatively new in the field of housing economics. Additionally, this study is the first to use the CART model to analyze housing market in Istanbul and in Turkey and derive valuable housing policies to be used by the authorities.
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