支持商场运维管理的顾客购物行为分析

Analysis of Customer Shopping Behavior to Support Facility Management of Shopping Malls

购物型商场的内部人流量比较大,人与商场的不同店铺、不同商品之间存在大量的交互行为,这些行为产生了大量的数据。通过有效地收集与分析这些数据,将有助于提升商场的运维管理水平。以清华大学C楼的天猫超市为例,利用UWB(Ultra-Wide Band)定位技术进行顾客购物行为的实验研究。结果表明,研究建立的购物行为数据采集方法是可行的,数据综合分析结果可分析出商场内人与商品以及商品与商品之间的关系,以用于货架的调配等运维管理,可为商场运维管理提供支持。

The internal flow of people in shopping malls is relatively large.There are a lot of interactive behaviors between people and different shops and different commodities in shopping malls,which generate a lot of data.Through the effective collection and analysis of this data,it will help to improve the operation and maintenance management of the mall.This research takes the T-mall supermarket in the C building of Tsinghua University as an example and uses UWB positioning technology to carry out on-site experiments of customer shopping behavior.The results show that the shopping behavior data collection method established in this study is feasible,and the results of data comprehensive analysis can be used to analyze the people-goods and goods-goods in the market.The relationship between them then can be used for operation and maintenance management such as shelf deployment,which can provide support for the operation and maintenance management of shopping malls.