Statistical models to predict commercial- and parking-space occupancy
Statistical models to predict commercial- and parking-space occupancy
复制标题
预测商业和停车位占用率的统计模型
DOI：
--
复制
发表时间：
1991
期刊：
影响因子：
--
通讯作者：
S. McNeil
中科院分区：
文献类型：
--
作者：
E. Mcguiness;S. McNeil
本文探讨了使用简单的分析模型来定量估计对特定地点的商业和停车空间的需求。根据宾夕法尼亚州匹兹堡中央商务区的数据，通过入住率的回归方程，捕捉和量化了位置和其他场地特征对需求的影响。除了场地和位置考虑外，模型还包括建筑物的使用和条件以及租户的类型。然后使用预测的入住率来分析需求。这些模型分别从价格影响、经济影响和竞争市场影响的角度进行了讨论。将这些模型应用于匹兹堡现有灰狗巴士总站的选址开发。确定开发方案并估算成本，然后将其与基于市场价格和预测入住率的收入进行比较。使用净现值分析。本文还讨论了模型的局限性和其他应用。
This paper examines the use of simple analytical models to estimate quantitatively the demand for site‐specific commercial and parking space. The influence of locational and other site characteristics on demand is captured and quantified through regression equations for occupancy, based on data from the Pittsburgh, Pennsylvania, central business district. In addition to site and locational considerations, the use and condition of the building and type of tenant are included in the models. The predicted occupancy is then used to analyze demand. The models are discussed in terms of price impacts, economic influences, and the effects of competing markets. These models are applied to the development of the site of the existing Greyhound bus terminal in Pittsburgh. Development options are identified and costs estimated, which are then compared with revenues based on market rates and predicted occupancy. A net present value analysis is used. Limitations and other applications of the models are also discussed.