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Biyomedikal Sektörü Rekabet Gücü İstatistiksel Analizi: Türkiye Örneği

Thesis Type: Postgraduate

Institution Of The Thesis: Erciyes University, Fen Bilimleri Enstitüsü, Turkey

Approval Date: 2017

Thesis Language: Turkish

Student: Esra KURUM

Supervisor: Hatice Erkekoğlu

Abstract:

The aim of this study is to determine the international competitiveness of the biomedical sector of Turkey. Nowadays, some countries in the field of biomedical sector produce and export their own products while some countries import and use the products of this sector and follow new technologies. The import and export values required to calculate the competitive power of Turkey's biomedical sector were compiled from the data set of the United Nations Statistical Committee "Commodity Trade Statistics Database (COMTRADE)". The data used in the study are limited to the years 1996 and 2014. According to this; Turkey is a net importer in the biomedical sector. Competitiveness of the sector Competitive Advantage Index (RCA), Relative Trade Advantage Index (RTA), Relative Export Advantage Index (RXA), Explained Competitive Advantage Index (RC) etc. indices. With the help of such indexes, the sector has tried to evaluate the competitive power in international trade and achieved the result that the competition power is weak. As an alternative to these indices, training in artificial neural networks was used to estimate the competitive power of the sector. In addition, the factors affecting the competition power of the sector have been tried to be determined by performing regression analysis in SPSS program. The regression model in which the Ln RMA value is a dependent variable in the analyzes made for the Turkish biomedical sector, includes General Health Expenditures, GDP, Number of Scientific Publications; In the regression model where Ln RXA is the dependent variable, the results of the Total Arge Expenditures and Arge Expenditure/GDP parameters are found to be significant

Keywords: Biomedical Sector Competitiveness, Factors affecting competitive power, SPSS, Regression Analysis, RCA, RTA, RXA, RC, Artificial Neural Networks (ANN)