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Patronage of urban commercial clusters: A network-based extension of the Huff model for balancing location and size

机译:城市商业集群的赞助:Huff模型的基于网络的扩展,用于平衡位置和规模

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摘要

We introduce a version of the Huff retail expenditure model, where retail demand depends on households’ access to retail centers. Household-level survey data suggest that total retail visits in a system of retail centers depends on the relative location pattern of stores and customers. This dependence opens up an important question—could overall visits to retail centers be increased with a more efficient spatial configuration of centers in planned new towns? To answer this question, we implement the model as an Urban Network Analysis tool in Rhinoceros 3D, where facility patronage can be analyzed along spatial networks and apply it in the context of the Punggol New Town in Singapore. Using fixed household locations, we first test how estimated store visits are affected by the assumption of whether shoppers come from homes or visit shops en route to local public transit stations. We then explore how adjusting both the locations and sizes of commercial centers can maximize overall visits, using automated simulations to test a large number of scenarios. The results show that location and size adjustments to already planned retail centers in a town can yield a 10% increase in estimated store visits. The methodology and tools developed for this analysis can be extended to other context for planning and right-sizing retail developments and other public facilities so as to maximize both user access and facilities usage.
机译:我们介绍了霍夫零售支出模型的一种版本,该模型的零售需求取决于家庭对零售中心的访问权限。家庭层面的调查数据表明,零售中心系统中的总零售访问量取决于商店和客户的相对位置模式。这种依赖性提出了一个重要的问题:在计划中的新城镇中,通过更有效的中心空间配置,是否可以增加对零售中心的总体访问量?为了回答这个问题,我们将该模型作为Rhinoceros 3D中的城市网络分析工具来实现,该模型可以沿空间网络分析设施的使用量并将其应用于新加坡榜鹅新城的环境中。使用固定的家庭位置,我们首先测试假设购物者是在家中还是在去本地公共交通站点的途中逛商店的假设,如何影响估计的逛店。然后,我们将探讨如何使用自动模拟来测试大量场景,同时调整商业中心的位置和规模,以最大程度地提高整体访问量。结果表明,对一个城镇中已经计划好的零售中心进行位置和规模调整可以使估计的商店访问量增加10%。可以将为该分析开发的方法和工具扩展到其他环境,以规划零售开发和其他公共设施并对其进行适当大小调整,以使用户访问和设施使用最大化。

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