标题： 最可能的零售集聚模式：空间均衡的潜力最大化与随机稳定性 显示英文标题

标题： Most likely retail agglomeration patterns: Potential maximization and stochastic stability of spatial equilibria

摘要： 我们研究了一个零售集聚模型，其中消费者更可能前往商店集中度较高的区域。这种集聚效应使拥有众多零售商的区域更具吸引力。在均衡状态下，零售商的空间分布是内生地根据购物需求的空间模式确定的。在这种情况下，可能会出现多个局部稳定的均衡，结果可能取决于店铺的初始分布。为了解决这个问题，我们应用了进化博弈论的一种方法，选择最大化代表零售商激励潜力函数的均衡。我们在二维空间设置中演示了该方法。与基于渐进、短视调整的局部稳定性相比，这种全局最大化导致了一个唯一且更稳健的预测。正如预期的那样，当不动消费者购物成本下降或更大零售集中区的吸引力增加时，零售集群的数量都会减少。 显示英文摘要

摘要： We study a model of retail agglomeration where consumers are more likely to visit zones with a higher concentration of shops. This agglomerative effect makes zones with many retailers more attractive. The spatial distribution of retailers in equilibrium is endogenously determined in response to the spatial pattern of shopping demand. In such a setting, multiple locally stable equilibria may arise, and the outcome can depend on the initial distribution of shops. To address this issue, we apply an approach from evolutionary game theory, selecting the equilibrium that maximizes a potential function representing the incentives of retailers. We demonstrate the method in a two-dimensional spatial setting. Compared to local stability based on gradual, myopic adjustments, this global maximization leads to a unique and more robust prediction. As expected, the number of retail clusters decreases either when shopping costs for immobile consumers fall or when the attractiveness of larger retail concentrations increases.