Relational network data development efficiency analysis of Turkey and european railway

In this study, Relational Network Data Envelopment Analysis (DEA) implemented that analyze the efficiency of the 14 Europe and Turkey railways data of the years 2000 to 2017 which chosen from UIC (International Union of Railways) railisa database. Initially, the system, production and consumption process efficiency of 14 railways were estimated with with linear programming models using Lingo 17.0 Program. Later efficiency ranking of 14 railways was made for each year and production and consumption process efficiency were interpreted with performance matrices. After that Tobit Regression Analysis was used to identify the factors affecting production, consumption and system activities by using the efficiency scores database obtained from the efficiency analysis. By this means. As a result of the study, the efficiency rankings of 14 railways for 18 years and the significant variables affecting the rankings were identified. The most important variables affecting the efficiency of the system were found to be passenger and freight train occupancy, national income per capita and population density. Key Worlds: Railway Effficiency, Relational Network Data Envelopment Analysis, Tobit Regression Analysis.