The prioritisation of provinces for public grants allocation by a decision-making methodology based on type-2 fuzzy sets

Regional development agencies (RDA) are the units established for accelerating regional development and increasing local capacity. They aim at activating the regional dynamics and to reduce the intra-regional and inter-regional development gap. In a region, each province may have a different development level. This would pose a problem for socio-economic development. In order to reduce the disparities among the provinces, financial support mechanisms of development agencies would be a beneficial influence only if supports are used with to correct strategies. In order to play a vital role to reduce intra-regional disparities, it is necessary to consider many criteria to categorise settlements in terms of socio-economic development. Some of these criteria are generally subjective and extremely difficult to express in numbers. However, fuzzy sets are a great help to decision makers in a prioritisation of provinces for public grants allocation process with linguistic variables and measurement challenges. In this study, a new city-ranking model has been proposed for development agencies operating in Turkey. To address ambiguities and relativities in real-world scenarios more conveniently, type-2 fuzzy sets and crisp sets have been simultaneously used in multicriteria decision making (MCDM) process of grants allocation. To illustrate the proposed model better, an application with real case data has been performed in the Middle Black Sea Development Agency in Turkey.