A Study on the Sales Forecasting and Retail Impact Analysis of Large Retail Stores in China Using MCI Model

Recent research on GIS analysis, spatial interaction models, and site selection for large retail stores is actively underway in China both domestically and internationally. However, most studies tend to rely on secondary data provided by government agencies, neglecting research based on actual consumer survey data. Therefore, this study aimed to improve methods for analyzing commercial areas of large-scale retail stores in China by proposing the use of consumer data to enhance existing spatial interaction models. Specifically, by conducting surveys among consumers who actually visit large-scale retail stores, basic data such as store visit rates and visitor travel distances were collected to construct the MCI model. Through this approach, the study estimated the visit probability and market share of large-scale retail stores, and analyzed the impact of market environmental changes on commercial areas. Firstly, based on address data from 279 Chinese consumers, the study area was divided into 44 regions. These regions were combined with information on consumer shopping patterns and store details to construct a matrix of interactions between regions and large-scale retail stores. Secondly, important parameters in the MCI model, such as store attractiveness index and distance sensitivity, were estimated through OLS regression analysis. Findings revealed that the store type (regional large-scale retail, urban large-scale retail) did not significantly impact on consumers’ store preferences. Instead, customer visits exhibited an inverse relationship with distance and a direct relationship with store size. These estimated results were consistent with the theoretical perspectives of spatial interaction models. Thirdly, to examine how changes in the retail environment may affect retail businesses within commercial areas, the study focused on changes in sales and market share of surrounding retail businesses when a specific store expanded its area or entered a new region. The results showed that both expanding store area and entering new regions had negative impacts on other existing stores.

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Publication Details

Journal
The Korean Logistics Research Association
Published
2024-08-31
DOI
https://doi.org/10.17825/klr.2024.34.4.75
Primary Topic
Technology and Data Analysis
Type
article
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article

A Study on the Sales Forecasting and Retail Impact Analysis of Large Retail Stores in China Using MCI Model

Byong-Kook Yoo, Zelin Li
The Korean Logistics Research Association
Technology and Data Analysis
article

A Study on the Sales Forecasting and Retail Impact Analysis of Large Retail Stores in China Using MCI Model

Byong-Kook Yoo, Zelin Li
article en

Abstract

Recent research on GIS analysis, spatial interaction models, and site selection for large retail stores is actively underway in China both domestically and internationally. However, most studies tend to rely on secondary data provided by government agencies, neglecting research based on actual consumer survey data. Therefore, this study aimed to improve methods for analyzing commercial areas of large-scale retail stores in China by proposing the use of consumer data to enhance existing spatial interaction models. Specifically, by conducting surveys among consumers who actually visit large-scale retail stores, basic data such as store visit rates and visitor travel distances were collected to construct the MCI model. Through this approach, the study estimated the visit probability and market share of large-scale retail stores, and analyzed the impact of market environmental changes on commercial areas. Firstly, based on address data from 279 Chinese consumers, the study area was divided into 44 regions. These regions were combined with information on consumer shopping patterns and store details to construct a matrix of interactions between regions and large-scale retail stores. Secondly, important parameters in the MCI model, such as store attractiveness index and distance sensitivity, were estimated through OLS regression analysis. Findings revealed that the store type (regional large-scale retail, urban large-scale retail) did not significantly impact on consumers’ store preferences. Instead, customer visits exhibited an inverse relationship with distance and a direct relationship with store size. These estimated results were consistent with the theoretical perspectives of spatial interaction models. Thirdly, to examine how changes in the retail environment may affect retail businesses within commercial areas, the study focused on changes in sales and market share of surrounding retail businesses when a specific store expanded its area or entered a new region. The results showed that both expanding store area and entering new regions had negative impacts on other existing stores.

The Korean Logistics Research AssociationVol. 34(4)
Openalex Percentile: Top 74%
Technology and Data Analysis
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A Study on the Sales Forecasting and Retail Impact Analysis of Large Retail Stores in China Using MCI Model — Byong-Kook Yoo, Zelin Li · The Korean Logistics Research Association (2024) | TGRS Research Map | TGRS