Spatial Decision Making in Context to Hospital Location

An opening strategy formulation for the hospitality sector in the COVID-19 environment is a challenging issue. This issue is addressed in this study while introducing two distinct multiple criteria decision-making methods: Grey Relational AnalysisGrey relational analysis (GRA) (GRA) and TOPSISTechnique of Order of Preference by Similarity to Ideal Solution (TOPSIS)-based proposal towards the multiple criteria ranking problem of the hospitality sector of Turkey. The multiple criteria decision-making problem under COVID-19 requires a framework to deal with the underlying uncertaintyUncertainty. Here, a well-known uncertaintyUncertainty dealing framework based on an Atanassov intuitionistic fuzzy setAtanassov intuitionistic fuzzy set is considered. We propose a variant of TOPSISTechnique of Order of Preference by Similarity to Ideal Solution (TOPSIS) and GRAGrey relational analysis (GRA) in the intuitionistic fuzzy environment. Further, a multivalued distance measure known as spatial distance measure has been used to propose spatial-grey relational analysis and spatial TOPSIS methods. The proposed methods are multivalued in nature. During experimentation, spatial-grey relational analysis and spatial TOPSIS detect multiple patterns simultaneously to study the credibility associated with the hospitals of Turkey during COVID-19. Here, a maximum of 3 patterns must be analyzed during hospital selection. The computing costs of the proposed spatialistic methods and TOPSISTechnique of Order of Preference by Similarity to Ideal Solution (TOPSIS)/GRAGrey relational analysis (GRA) are almost the same. The spatial TOPSIS and spatial-grey relational analysis are free of criteria weights and compared with the criteria-weighted intuitionistic TOPSIS and GRAGrey relational analysis (GRA) to discuss the peculiarities associated with the proposed methods.