Efficiency analysis of organized industrial zones in Eastern Black Sea Region of Turkey

Abstract Organized Industrial Zones (OIZs) are the production areas of goods and services that are established to provide planned industrialization and planned urbanization by structuring the industry in suitable areas, to prevent environmental problems, and to provide efficient use of resources. The aim of this study is to propose a decision-making model based on data envelopment analysis (DEA) to evaluate the relative efficiencies of OIZs located in the Eastern Black Sea Region of Turkey. First, the efficiency score of each alternative is determined by employing a DEA formulation with interval data. Second, a common weight DEA-based formulation is applied in order to obtain common set of weights and provide ranking results with an improved discriminating power in imprecise nature. In this study, the best performing OIZ alternative, which performs in Eastern Black Sea region of Turkey, is identified based on the approach proposed by Salahi et al. [1]. The DEA-based model developed by Salahi et al. [1] is improved by modifying a constraint. In order to demonstrate the robustness of the application, two numerical illustrations are given. The first example compares the results obtained by the formulation addressed in Salahi et al. [1] and the improved model; while second numerical illustration provides a case study conducted in Eastern Black Sea region of Turkey.

[1]  E. E. Karsak *,et al.  Practical common weight multi-criteria decision-making approach with an improved discriminating power for technology selection , 2005 .

[2]  Jin-Li Hu,et al.  Industrial park efficiency in Taiwan , 2009 .

[3]  Harold O. Fried,et al.  Incorporating the Operating Environment Into a Nonparametric Measure of Technical Efficiency , 1999 .

[4]  Maziar Salahi,et al.  An optimistic robust optimization approach to common set of weights in DEA , 2016 .

[5]  Q. Qiao,et al.  Study on eco-efficiency of industrial parks in China based on data envelopment analysis. , 2017, Journal of environmental management.

[6]  Abraham Charnes,et al.  Measuring the efficiency of decision making units , 1978 .

[7]  Mohammad Izadikhah,et al.  A new data envelopment analysis method for ranking decision making units: an application in industrial parks , 2015, Expert Syst. J. Knowl. Eng..

[8]  Reza Farzipoor Saen,et al.  A new look at measuring sustainability of industrial parks: a two-stage data envelopment analysis approach , 2014, Clean Technologies and Environmental Policy.

[9]  Madjid Tavana,et al.  A hybrid DEA-MOLP model for public school assessment and closure decision in the City of Philadelphia , 2018 .

[10]  Nuray Girginer,et al.  ASSESSING EXPORT PERFORMANCE OF TEXTILE COMPANIES IN ESKISEHIR ORGANIZED INDUSTRIAL ZONE BY USE OF DATA ENVELOPMENT ANALYSIS (DEA) , 2012 .

[11]  Nengcheng Chen,et al.  Environmental efficiency analysis of the Yangtze River Economic Zone using super efficiency data envelopment analysis (SEDEA) and tobit models , 2017 .

[12]  Jin-Li Hu,et al.  Efficiency of Science and Technology Industrial Parks in China , 2010 .