Spatial sorting and selection within urban agglomerations: a tripartite evolutionary game model approach

作者：Yunsheng Zhang, Shuting Wang, Ruomeng Zhou · 发表于：Humanities and Social Sciences Communications · 年份：2025 · DOI：10.1057/s41599-024-04281-x · 被引用次数：7 · 研究领域：Regional Economics and Spatial Analysis、Land Use and Ecosystem Services、Economic and Environmental Valuation

Urban agglomerations play a pivotal role in regional economic growth by fostering industrial clustering and attracting firms, thereby enhancing urban productivity and efficiency. However, existing research on spatial sorting and selection in urban settings-primarily based on quantitative spatial models-often overlooks the dynamic strategic adaptations of firms with varying skill levels. This gap leads to an incomplete understanding of how firms interact and adjust their spatial positioning over time in response to evolving urban economic conditions. To address this, we develop a tripartite evolutionary game model to investigate the spatial sorting and selection mechanisms among high-, medium-, and low-skill firms in urban settings. The model simulates firms’ strategic choices-whether to enter or avoid central cities-under varying initial conditions, such as participation willingness, skill disparities, and urban costs. Extensive simulations reveal that although these factors influence the process and equilibrium rates, they do not change the ultimate strategic outcome: high-skill firms consistently gravitate toward central cities, whereas low-skill firms tend to remain in peripheral areas, especially when urban costs are high. These findings provide significant insights for urban policy. The concentration of high-skill firms in large cities poses challenges for smaller cities attempting to attract these industries, potentially exacerbating regional disparities. Policymakers a...