A cellular automata model on residential migration in response to neighborhood social dynamics

Residential migration patterns result from complex processes involving households and their neighborhoods. Simulation models assist in understanding this relationship by contextualizing residential mobility within a theoretical framework. The objective of this study is to model these migration patterns created by the interaction between changes in the social structure of households and the positive or negative social attractors in the neighborhood. Specifically, this study links residential mobility to the dynamic interplay between the micro-environment existing within a household and the meso-environment that structures a neighborhood. The cellular automata model developed in this study incorporates transition rules which govern households in their decision to move. The results represented by a cellular grid demonstrate that residential mobility is significantly influenced by density rates, individual household factors and neighborhood attractors. Three contrasting scenarios are presented in this paper to illustrate the impact of occupancy, density, neighborhood social influence, and the effect of a conglomeration of negative social attractors in a neighborhood. Future iterations of this model will incorporate census and crime data in order to test whether the rules governing this model are an accurate reflection of residential mobility in a mid-sized Canadian city.