An understanding of how Social Overhead Capital (SOC) is associated with the land value of the local community is important for effective urban planning. However, even within a district, there are multiple sections used for different purposes; the term for this is spatial heterogeneity. The spatial heterogeneity issue has to be considered when attempting to comprehend land prices. If there is spatial heterogeneity within a district, land prices can be managed by adopting the spatial clustering method. In this study, spatial attributes including SOC, socio-demographic features, and spatial information in a specific district are analyzed with Finite Mixture Modeling (FMM) in order to find (a) the optimal number of clusters and (b) the association among SOCs, socio-demographic features, and land prices. FMM is a tool used to find clusters and the attributes' coefficients simultaneously. Using the FMM method, the results show that four clusters exist in one district and the four clusters have different associations among SOCs, demographic features, and land prices. Policymakers and managerial administration need to look for information to make policy about land prices. The current study finds the consideration of closeness to SOC to be a significant factor on land prices and suggests the potential policy direction related to SOC.
翻译:了解社会超额资本如何与当地社区的土地价值相联系,对于有效的城市规划十分重要,但是,即使在一个地区,也有多个部门用于不同目的;这一术语是空间异质性;空间差异问题在试图理解土地价格时必须加以考虑;如果一个地区存在空间差异,可以采用空间集群法管理土地价格;在这项研究中,对特定地区的空间属性,包括社会超额资本、社会人口特征和空间信息进行了分析,包括社会超额资本、特定地区的空间属性,包括社会人口特征和空间信息等,并用金融混合模型(FMM)来分析,以便找到(a) 最佳组数,以及(b) 空间多类集、社会人口特征和土地价格之间的联系;空间多变性问题是一个用于同时寻找集群和属性系数的工具;使用FMM方法,结果显示,一个地区存在四个集群,而四个集群在社会经济、人口特征和土地价格之间有着不同的联系;决策者和管理管理部门需要寻找关于土地价格的政策信息,以便(a) 找出(a) 最佳组群集数;(b) 社会-人口特征和土地价格之间的关联;目前研究发现与SOC相关的政策因素是一个重要的方向。