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Modeling human migration driven by changing mindset, agglomeration, social ties, and the environment

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  • Gonzalo Suarez
  • Rachata Muneepeerakul

Abstract

Migration is an adaptation strategy to unfavorable conditions and is governed by a complex set of socio-economic and environmental drivers. Here we identified important drivers relatively underrepresented in many migration models—CHanging mindset, Agglomeration, Social ties, and the Environment (CHASE)—and asked: How does the interplay between these drivers influence transient dynamics and long-term outcomes of migration? We addressed this question by developing and analyzing a parsimonious Markov chain model. Our findings suggest that these drivers interact in nonlinear and complex ways. The system exhibits legacy effects, highlighting the importance of including migrants’ changing priorities. The increased characteristic population size of the system counter-intuitively leads to fewer surviving cities, and this effect is mediated by how fast migrants change their mindsets and how strong the social ties are. Strong social ties result in less diverse populations across cities, but this effect is influenced by how many cities remain. To our knowledge, this is the first time that these drivers are incorporated in one coherent, mechanistic, parsimonious model and the effects of their interplay on migration systematically studied. The complex interplay underscores the need to incorporate these drivers into mechanistic migration models and implement such models for real-world cases.

Suggested Citation

  • Gonzalo Suarez & Rachata Muneepeerakul, 2022. "Modeling human migration driven by changing mindset, agglomeration, social ties, and the environment," PLOS ONE, Public Library of Science, vol. 17(2), pages 1-11, February.
  • Handle: RePEc:plo:pone00:0264223
    DOI: 10.1371/journal.pone.0264223
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    1. Ryuichi Kitamura & Cynthia Chen & Ram Pendyala & Ravi Narayanan, 2000. "Micro-simulation of daily activity-travel patterns for travel demand forecasting," Transportation, Springer, vol. 27(1), pages 25-51, February.
    2. Siaw Akwawua & James A. Pooler, 2001. "The development of an intervening opportunities model with spatial dominance effects," Journal of Geographical Systems, Springer, vol. 3(1), pages 69-86, May.
    3. Diana Suleimenova & Derek Groen, 2020. "How Policy Decisions Affect Refugee Journeys in South Sudan: A Study Using Automated Ensemble Simulations," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 23(1), pages 1-2.
    4. Marta C. González & César A. Hidalgo & Albert-László Barabási, 2009. "Understanding individual human mobility patterns," Nature, Nature, vol. 458(7235), pages 238-238, March.
    5. Hassani-Mahmooei, Behrooz & Parris, Brett W., 2012. "Climate change and internal migration patterns in Bangladesh: an agent-based model," Environment and Development Economics, Cambridge University Press, vol. 17(6), pages 763-780, December.
    6. Govert E. Bijwaard, 2008. "Modeling Migration Dynamics of Immigrants," Tinbergen Institute Discussion Papers 08-070/4, Tinbergen Institute.
    7. Filippo Simini & Marta C. González & Amos Maritan & Albert-László Barabási, 2012. "A universal model for mobility and migration patterns," Nature, Nature, vol. 484(7392), pages 96-100, April.
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