Urban Development Through the Lens of Agent-based Modeling
Related publication: Bagheri-Jebelli, N., Crooks, A.T. and Kennedy, W.G., “Capturing the Effects of Gentrification on Property Values: An Agent-Based Modeling Approach”, The Computational Social Science Society of Americas Conference, Santa Fe, NM, USA, 2019.
Goal: Cities are ever changing and growing phenomenon with many underlying complexities. Through its life cycle, a city experiences various forms of dynamics. Models allow for a better understanding of such complexities and dynamics. The model developed in this thesis intends to simulate the dynamics of certain processes such as: an urban market, agent interactions in that market, urban growth, sprawl and shrinkage and gentrification. The purpose of this model is to understand the behavioral pattern of the agents and demonstrate the life cycle of a city based on individual agents’ actions. This model is significant in its integration of various subsystems creating a larger system while observing developers’ behavior. Specifically, the model explores some well-known issues, including the Smith’s rent-gap theory, Burgess’s concentric zones model of urban growth, and Alonso’s bid rent theory. The main results from the model show that the agents move to and reside in properties within their income range, with similar neighbors. This is one of the first models that provides a new lens to explore urban development.
Conclusion: While many models have been developed to explore a single urban process, our model examined multiple processes, namely urban growth, sprawl, shrinkage, and gentrification to portray their effect on the life cycle of a city. The model focused on the agent-agent and agent-environment interactions that play a role in population density and property value. For the purpose of this paper, we narrowed the analysis down to observing the role of gentrification by supply and demand. We observed in the results that the immobilization and displacement of the lower income agents caused by developers revitalizing a neighborhood for profit and also by higher income agents choosing to live near CBD and pay lower rents. The actions of the developers and professionals in the model directly affected the options that non-professionals are left with through the rise of population density and housing price. Our model demonstrates patterns of increased segregation as a result of the preferences, rules, and interactions occurring between agents. Finally, the model supports the previous research revealing the disabling nature of gentrification for the unprivileged population residing in or native to a neighborhood undergoing development.