论文标题
最有可能的零售集聚模式：空间平衡的潜在最大化和随机稳定性
Most likely retail agglomeration patterns: Potential maximization and stochastic stability of spatial equilibria
论文作者
论文摘要
我们研究了零售集聚的模型，在该模型中，消费者更有可能参观较高商店的区域。这种集聚效果使许多零售商更具吸引力。零售商在平衡中的空间分布是根据购物需求的空间模式来确定的。在这种情况下，可能会出现多个本地稳定的平衡，结果可能取决于商店的初始分布。为了解决这个问题，我们采用了进化游戏理论的方法，选择了最大化代表零售商激励措施的潜在功能的平衡。我们在二维空间环境中演示了该方法。与基于渐进的近视调整的局部稳定性相比，这种全局最大化会导致一个独特，更健壮的预测。如预期的那样，当不动消费者的购物成本下降或较大零售浓度的吸引力增加时，零售集群的数量要么减少。
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.
