Indoor Mobility Interaction Model: Insights into the Customer Flow in Shopping Malls
Indoor Mobility Interaction Model: Insights into the Customer Flow in Shopping Malls
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DOI：
10.1109/access.2019.2942428
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发表时间：
2019-09
期刊：
影响因子：
3.9
通讯作者：
Yaxi Liu;T. Pei;Ci Song;Hua Shu;Sihui Guo;Xi Wang
中科院分区：
文献类型：
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作者：
Yaxi Liu;T. Pei;Ci Song;Hua Shu;Sihui Guo;Xi Wang
大型户外空间的相互作用因其对于理解人地关系的重要性而被广泛研究。重力等模型已被证明能够量化两个地方之间的相互作用。然而，尽管人类70%以上的时间都在室内度过，但室内空间的互动仍不清楚。很少有研究尝试构建室内交互模型。在本研究中，我们通过客流分析购物中心内商店之间的交互，以确定室内移动交互是否遵循重力定律及其影响因素。基于室内定位数据，定义两个客流度量（连接流，表示商店之间的直接连接，关联流，表示商店之间的关联关系）和两个距离度量（路径距离，表示最小出行成本，商店距离，表示平均出行成本），以适应传统和扩展重力模型（考虑商店楼层和类型）。我们发现：1）商店之间的交互遵循幂律分布，表明只有一小部分商店对密切相关； 2）客户移动性受引力定律支配，其中连接流的距离衰减指数为1-2，关联流的距离衰减指数为0-1； 3）店铺楼层和类型是影响店铺之间互动的两个重要因素。这些发现为室内互动建模提供了见解，并可以支持室内环境优化布局、估计客流量和促进销售。
Interaction in large-scale outdoor space has been extensively studied due to its importance in understanding the human-land relationship. Models such as the gravity have been proven to be able to quantify the interaction between two places. However, interaction in indoor space still remains unclear even though humans spend over 70% of their time indoors. Few studies attempt to construct an indoor interaction model. In this study, we analyze the interaction between stores in shopping malls via customer flow to determine whether indoor mobility interaction follows the gravity law and what are its influencing factors. Based on indoor positioning data, two customer flow measures (connectivity flow, indicating the direct connection between stores, and association flow, indicating the association relationship between stores) and two distance measures (path distance, indicating the minimum travel cost, and store distance, indicating the mean travel cost) are defined to fit the traditional and extended gravity models (considering store floor and type). We find that 1) interaction between stores follows a power law distribution, indicating that only a small fraction of store pairs is closely related; 2) customer mobility is governed by the gravity law, where the distance decay exponent is 1–2 for the connectivity flow and 0–1 for the association flow; and 3) store floor and type are two important factors that affect the interaction between stores. These findings provide insights for modeling indoor interactions and can support indoor settings to optimize their layout, estimate the customer flow and promote sales.