Ali Kemal Çelik

A multinomial logit analysis of risk factors influencing road traffic injury severities in the Erzurum and Kars Provinces of Turkey

A retrospective cross-sectional study is conducted analysing 11,771 traffic accidents reported by the police between January 2008 and December 2013 which are classified into three injury severity categories: fatal, injury, and no injury. Based on this classification, a multinomial logit analysis is performed to determine the risk factors affecting the severity of traffic injuries. The estimation results reveal that the following factors increase the probability of fatal injuries: drivers over the age of 65; primary-educated drivers; single-vehicle accidents; accidents occurring on state routes, highways or provincial roads; and the presence of pedestrian crosswalks. The results also indicate that accidents involving cars or private vehicles or those occurring during the evening peak, under clear weather conditions, on local city streets or in the presence of traffic lights decrease the probability of fatal injuries. This study comprises the most comprehensive database ever created for a Turkish sample. This study is also the first attempt to use an unordered response model to determine risk factors influencing the severity of traffic injuries in Turkey.

Determinants of housing demand in the Erzurum province, Turkey

Purpose - – The main aim of this study is to determine the factors that influence the housing demand of households in Erzurum, northeastern Turkey. Housing demand is generally affected by several factors including housing prices, individuals’ income, expectations and choices and so on, as a means of its demographic and socio-psychological contexts. Design/methodology/approach - – A questionnaire-based cross-sectional survey was carried out, in which the outcome variable had binary responses such as whether to invest in housing or not. A binary logistic regression analysis was performed to estimate the underlying data. Findings - – The questionnaire was conducted in 2,927 households living in Erzurum city center, and 47 per cent of the respondents claimed that they would consider investing in housing in the future. The estimation results reveal that demographic or socio-economic factors that may possibly influence housing demand of the respondents are as follows: household head’s and spouse’s occupation, monthly income, the number of individuals in the family and car ownership. Originality/value - – This paper involves the most comprehensive survey addressing the housing demand in the East Anatolian Region, Turkey. Additionally, this paper aims to contribute to the existing housing literature through establishing the statistical analysis of housing demand in an unstudied territory of the world.

A Comparison of Alternative Ordered Response Models for Analysing User Satisfaction with Transport Services in Turkey

Abstract The main objective of this paper is to analyse user satisfaction with road, maritime, air, and rail transport services in Turkey using four distinctive ordered response models. The estimation results reveal that partial constrained generalized ordered logit model has the best model fit for road and maritime transport services. In addition, ordered logit and generalized ordered logit are the convenient models for air and rail transport services, respectively. Results also indicate that current residence (urban), gender (male), occupational sector (private), and education level (low educated) were the statistically significant variables that are more likely to increase user satisfaction. This paper is probably the first attempt to analyse user satisfaction with all transport services using comparative ordered response models. As a social indicator, the results of this study may provide a valuable evidence for future sustainable transport policies in Turkey.

Effects of the tourism industry on the balance of payments deficit

The balance of payments is an accounting record that indicates the economic and financial situations of a country as compared with other countries. International tourism directly affects the balance of payments as an invisible export entry. The significant contribution of international tourism appears on the balance of payments account under the entry of international services. In order to discuss the favourable effect of tourism on the balance of payments, the amount of foreign currency revenues for a country must exceed the amount of foreign currency expenditures. Most developing countries, including Turkey, are exposed to crucial balance of payments and foreign trade deficits. At this point, tourism has a favourable effect in closing the gap in foreign trade and the balance of payments. This paper examines the primary effect of numerical tourism revenues on the balance of payments between 1984 and 2012 in Turkey. The empirical findings suggest that the increase in tourism revenues over this period has resulted in a decrease in the balance of payments deficit of 14%.

Analysing workplace violence towards health care staff in public hospitals using alternative ordered response models: the case of north-eastern Turkey

The main objective of this article is to determine key factors that may have a significant effect on the verbal abuse, emotional abuse and physical assault of health care workers in north-eastern Turkey. A self-administered survey was completed by 450 health care workers in three well-established hospitals in Erzurum, Turkey. Because of the discrete and ordered nature of the dependent variable of the survey, the data were analysed using four distinctive ordered response models. Results revealed that several key variables were found to be a significant determinant of workplace violence, such as the type of health institution, occupational position, weekly working hours, weekly shift hours, number of daily patient contacts, age group of the respondents, experience in the health sector, training against workplace violence and current policies of the hospitals and the Turkish Ministry of Health.

Predictors of college students’ willingness to use social network services: The case of two Turkish universities

Purpose – The purpose of this paper is to determine predictors of social network services use among college students at two Turkish universities, with particular emphasis on Facebook, Twitter, Foursquare, and Instagram. Design/methodology/approach – A written questionnaire was administered to 822 college students from various faculties. The data obtained from the corresponding questionnaire were analyzed using ordered logit analysis and four different models were independently estimated with respect to social network services. Findings – Ordered logit estimation results revealed that frequency of log in to social network sites, time spent on social network sites, and following event alerts were three predictors that had significant impact on the frequency of all four social network sites’ use. Particularly; event participation, information sharing, following on top ranked topics, and purchasing a product through social media were the other additional predictors of college students’ willingness to use the ...

Application of Panel Quantile Regression and Gravity Models in Exploring the Determinants of Turkish Automotive Export Industry

This paper purposes to determine potential factors influencing the amount of Turkish automotive industry exports. For this purpose, the available data of 68 major trading partners of Turkey in terms of automotive industry exports were utilized for the sample period 2007–2015. Both panel quantile regression and the gravity model of trade approaches were considered to analyze the relevant data. The empirical findings of this paper revealed that the population and the distance variables were found as statistically significant for all quantiles, while the former has positive and the latter has negative signs as expected. Results also indicated that there was a statistically significant positive correlation between GDP per capita and the amount of Turkish automotive industry exports at 10 and 50% quantiles; however, it was not statistically significant at 90% quantile despite its positive sign. Among Turkey’s exporter countries, being a EU member country dummy variable was found to have a statistically significant positive impact on the amount of automotive industry exports. Real exchange rate was not found as a significant determinant of the amount of automotive industry exports. In the lights of empirical evidence obtained from this study, several recommendations were made for Turkey’s future international trade policies.

An investigation of export–import ratios in Turkey using spline regression models

Abstract This paper examines the use of spline functions in linear, squared, and cubic spline regression models and exhibits the estimation of spline parameters from data by ordinary least squares. Determination of the number and the location of knots is central to spline regression. In this paper, we initially propose a method based on the coefficient of determination R2 related to the estimation of knots in spline regression. This proposed method as applied to export–import ratio distributions in Turkey for the years 1923–2010 determines the knots, and linear, quadratic, and cubic spline regression models are established accordingly. Results reveal that spline regression models offer better results than polynomial regression models, and that the quadratic spline regression model is the best explanatory model for export–import ratio distributions in the smoothest spline regression models.