ÖZGünümüzde turizm sektörünün turistik mal ve hizmetlerin talebine etki eden faktörlere karşı aşırı duyarlı olması bu sektördeki talep tahminlerini ve talebe etki eden faktörlerin analizini oldukça önemli duruma getirmektedir. Bu çalışmada Türkiye'nin Turizm alanındaki pazar payının önemli bir bölümünü oluşturan Avrupa ülkelerinin Türkiye'ye yönelik turizm talebinin modellenmesi amaçlanmıştır. Bu amaçla Görü-nürde İlişkisiz Regresyon Modelleri (GİR) kullanılmış ve bu modeller temel alınarak tahmin edilen parametreler, En Küçük Kareler (EKK) tahminleri ile karşılaştırılmıştır. Ayrıca çalışma kapsamında seçilen Avrupa ülkelerinin Türkiye'ye yönelik turizm talebini etkileyen faktörler incelenmiş ve bu faktörlere göre ülkeler karşılaştırılmıştır. GİR modeli kullanılarak elde edilen parametre tahminlerinin klasik regresyon modeli tahmin tekniklerine kıyasla daha etkin sonuçlar verdiği gözlenmiştir. Bu çalışma, turizm planlamalarının yapılması ve turizm politikalarının belirlenmesinde dünyada yaygın olarak kullanılmayan, Tür-kiye'deki turizm talep tahmin ve modelleme çalışmalarında yer almamış GİR modelinin bir karar yöntemi olarak kullanılmasını önermektedir.
A REWIEV OF TOURISM DEMAND ON TURKEY VIA SEEMINGLY UNRELATED REGRESSION MODELS ABSTRACTSince the tourism sector is highly sensible to the factors affecting touristic product and services, it gives a significant importance to demand forecasting and analyses of the factors that affect the demand. This study aims to model the tourism demand of European countries, which have an important share of the Turkish tourism market. For this study, Seemingly Unrelated Regression (SUR) Model was used and the forecasting parameters were compared with Ordinary Least Square (OLS) outcomes. Addition to that, factors affecting European Countries' tourism demand was analyzed and these countries were compared according to these factors. As a result of this study, parameter estimates of SUR model are more efficient than classical regression model parameter estimates. This study recommends SUR model, which is not widely used around the world and doesn't take part in studies in Turkey to determine the tourism politics and tourism projection works, can be used as a decision method.
The aim of the study is to determine the factors of individuals' skills with regard to internet usage in Turkey by ConfirmatoryFactor Analysis, and to analyze the factor indicators in order to clarify if they vary by gender, age and education level, i.e. if a digital divide is in question, by Multivariate Analysis of Variance (MANOVA) method. For that purpose, the data on "IT Usage -2016" of Turkish Statistical Institute was selected as baseline. All data used in this study is categorical. Though, since Confirmatory Factor Analysis and MANOVA are methods using continuous variables, firstly, the variables were transferred to quantified variables by Optimal Scaling method, and before employing Confirmatory Factor Analysis and MANOVA methods, the validity of both multivariate normality and equality of variance-covariance matrices hypotheses was checked. The results obtained showed that the skill with regard to internet usage consists of four factors: personal intended internet activities, e-learning, e-government services, and software related activities. According to the MANOVA results, these factors significantly vary by gender, age, and education level, and thus, there's a second and a third level digital divide between individuals in Turkey.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.