Correlation Analysis of Retail Space and Shopping Behavior in a Commercial Street Based on Space Syntax: A Case of Shijiazhuang, China

Abstract

The visibility and spatial characteristics of commercial space are the key factors that affect the space vitality. However, the coupling visibility graphical analysis of commercial spaces and spatial characteristics to quantitatively analyse consumer behaviour in commercial street spaces and assess the vitality of retail spaces has not been adequately studied. In this paper, the aim is to conduct a visibility graph analysis of Zhuangli Street in Letai Center, Shijiazhuang, using space syntax theory, assessing the spatial vitality of the retail space by investigating the shop visits. First, a methodology for obtaining data on spatial characteristics and consumer behaviour of shopping streets was developed. Secondly, this article constructs a process for a visibility graph analysis of Zhuangli Street based on space syntax theory. Third, two combination variables of the space coefficient and depth coefficient of shop windows in retail spaces of a commercial street are proposed. Finally, the effect of combination variables and business types on spatial vitality was analyzed using correlation and multiple regression methods, and a space vitality prediction model was proposed. The results showed that the shop with the highest shop visits of retail spaces in the shopping street is 13.55 times higher than the smallest shop. The space coefficient of the shop window, depth coefficient of the shop window, and space connectivity of retail spaces in commercial streets have positive effects on space vitality. The workflow proposed in this paper can provide technical support for retail space design in commercial streets as well as evaluating and optimizing commercial street space design solutions.