Grey System Theory in Research into Preferences Regarding the Location of Place of Residence within a City

Abstract

Analyses of the correlations between social and economic phenomena are rarely limited to simple evaluations of the relationships that exist between two features. Information about the structure and behaviour of complex phenomena and processes in the natural environment and social systems is usually incomplete and uncertain. Grey relational analysis (GRA) poses an alternative to statistical methods (e.g., correlation analysis, variance analysis, regression analysis and direct comparisons) to evaluate complex phenomena. In GRA, the number of assumptions relating to the size and distribution of samples is far smaller than in statistical methods. The required number of observations in the GRA is n ≥ 4. Therefore, the grey system theory (GST) provides useful tools for analysing limited and imperfect data. GST can be used to predict a system’s future behaviour and to evaluate the relationships between observation vectors. The study aimed to determine the strength of the relationships between the analysed features with the use of GST and to analyse the model’s behaviour for a different number of variables. The main assumptions and definitions relating to GST were presented. The residential preferences of a selected social group were analysed. The proposed approach supports the development of effective decision-making procedures in urban planning.