Measuring development levels of NUTS-2 regions in Turkey based on capabilities approach and multi-criteria decision-making

Ozdemir Y., Gul M.

COMPUTERS & INDUSTRIAL ENGINEERING, vol.128, pp.150-169, 2019 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 128
  • Publication Date: 2019
  • Doi Number: 10.1016/j.cie.2018.12.035
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.150-169
  • Keywords: Regional development, NUTS-2 regions, Well-being index, Capabilities approach, Multi-criteria decision-making, Pythagorean fuzzy sets, TODIM, ANALYTIC HIERARCHY PROCESS, RISK-ASSESSMENT, DEVELOPMENT AGENCIES, OCCUPATIONAL-HEALTH, EXTENDED TODIM, FUZZY, SELECTION, SAFETY, MODEL
  • Istanbul University Affiliated: No


Regional development seeks to better understand the issues and problems facing the regions because of the contemporary economic and social changes, including the formulation of territorial policies accordingly. In Turkey, in order to coordinate regional development, 26 regional development agencies were founded relating to the nomenclature of territorial units for statistics-2 (NUTS-2) regions. Since these regions have different development levels, it is useful for stakeholders to determine performance measures related to the regional development and propose a ranking model among these regions to provide a balance in delivering financial support mechanisms. Therefore, in this study, an iterative multi-criteria decision-making (MCDM) model is proposed. Firstly, Pythagorean Fuzzy Analytic Hierarchy Process (PFAHP) is used to assign weights to indicators of well-being index for provinces (WiP) in Turkey. Then, a TODIM (an acronym in Portuguese of interactive and multiple attribute decision making) based ranking model for 26 regions was applied. Also, this model takes capabilities and well-being approach into account differently from traditional utilitarian development models which take only some macro-economic and financial parameters. In order to do this, the model uses data from WiP. On conclusion, a comparative ranking projection with two other MCDM methods and WiP is provided and an effective and broader point of view was gained by the regional development performance measuring model.