Modern large-scale retail stores began in China in the early 1990s and have since experienced rapid growth in the Chinese retail market. However, recent changes in the market environment, such as the rise of online distribution and a culture emphasizi...
Modern large-scale retail stores began in China in the early 1990s and have since experienced rapid growth in the Chinese retail market. However, recent changes in the market environment, such as the rise of online distribution and a culture emphasizing leisure consumption, have led to serious socioeconomic issues in some areas. These include vacancies in large retail stores, management difficulties, closures, and the collapse of small and medium-sized commercial districts. To address these problems, the Chinese government has implemented various policy supports and invested significant funds. However, these measures are often seen as temporary and have shown limited effectiveness, with clear policy outcomes yet to materialize. To enhance the effectiveness of these large retail store policies, it's essential to conduct more objective and empirical analysis before policy implementation. Recently, there has been active research both within and outside of China focusing on retail location selection using GIS analysis, spatial interaction models, and other methods. However, most of these studies rely on secondary data provided by government agencies, often neglecting actual survey data from consumers. In response, this study aims to improve the analysis of retail districts in China by incorporating consumer data into existing spatial interaction models. Specifically, the study involved conducting surveys with consumers who actually visited large retail stores, collecting basic data such as store-specific isitation rates and the distances traveled by visitors. Based on this information, Huff models and MCI models were developed. These models are used to estimate visit probabilities and market share, as well as to analyze the impact of market environment changes on commercial districts.
In this study, four major shopping malls located in the center of Zhifu District, Yantai City - WanDa Plaza, Joy City, ZhenHua Shopping Mall, and ZhenHua Shopping Center - were selected as research subjects. A direct consumer survey method was used to collect information on the shopping patterns of 279 consumers in the study area. Subsequently, the study area was divided into 44 zones based on the starting locations of these 279 consumers. The main research findings, based on this data, can be summarized as follows. First, in the Huff I model, the most critical parameters, store area sensitivity and sensitivity to distance or time, were estimated through regression analysis. The results confirmed the theoretical hypothesis of the Huff model that customer visits are inversely proportional to distance (or time) and proportional to store size. Second, to enhance the Huff model, store attractiveness was not limited to store size but also included store type variables as new store attractiveness variables in estimating the MCI model. The results of the model estimation showed that the type of store (regional large-scale business, city-center large-scale business) did not significantly influence consumer store choice. Further analysis with more varied store attractiveness variables (such as leisure and entertainment functions, product diversity, service level) is needed. Third, to examine the impact on distribution businesses within commercial districts due to changes in the retail environment, scenarios were considered where specific stores expanded their area or new stores entered the area. In both scenarios, a negative impact on the existing stores was observed. However, the degree of this negative impact varied by store, which suggests the need for further information on the specific retail stores and visitors to properly explain these differences.