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

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  • Dursun, Mehtap
  • Goker, Nazli
  • Tulek, Burcu Deniz

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.

Suggested Citation

  • Dursun, Mehtap & Goker, Nazli & Tulek, Burcu Deniz, 2019. "Efficiency analysis of organized industrial zones in Eastern Black Sea Region of Turkey," Socio-Economic Planning Sciences, Elsevier, vol. 68(C).
  • Handle: RePEc:eee:soceps:v:68:y:2019:i:c:s0038012118301423
    DOI: 10.1016/j.seps.2018.10.010
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    References listed on IDEAS

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    1. Harold Fried & Shelton Schmidt & Suthathip Yaisawarng, 1999. "Incorporating the Operating Environment Into a Nonparametric Measure of Technical Efficiency," Journal of Productivity Analysis, Springer, vol. 12(3), pages 249-267, November.
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    3. Tavana, Madjid & Ebrahimnejad, Ali & Santos-Arteaga, Francisco J. & Mansourzadeh, Seyed Mehdi & Matin, Reza Kazemi, 2018. "A hybrid DEA-MOLP model for public school assessment and closure decision in the City of Philadelphia," Socio-Economic Planning Sciences, Elsevier, vol. 61(C), pages 70-89.
    4. Chen, Nengcheng & Xu, Lei & Chen, Zeqiang, 2017. "Environmental efficiency analysis of the Yangtze River Economic Zone using super efficiency data envelopment analysis (SEDEA) and tobit models," Energy, Elsevier, vol. 134(C), pages 659-671.
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    2. Özuyar, Pınar, 2021. "Circular Economy Practices In Turkey And Their Potential Interaction With Climate Change Mitigation And Adaptation," Academic Review of Humanities and Social Sciences, Bursa Teknik Üniversitesi, vol. 4(1), pages 18-32.
    3. Zhang, Han & Zheng, Jinhui & Hunjra, Ahmed Imran & Zhao, Shikuan & Bouri, Elie, 2024. "How does urban land use efficiency improve resource and environment carrying capacity?," Socio-Economic Planning Sciences, Elsevier, vol. 91(C).
    4. Soniya Falahatdoost & Xingping Wang, 2022. "Industrial Park Role as a Catalyst for Regional Development: Zooming on Middle East Countries," Land, MDPI, vol. 11(8), pages 1-18, August.

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