Abstract
The Chinese retail industry is expected to grow dramatically over the next few years, owing to the rapid increase in purchasing power of Chinese consumers. Retail managers should analyze the market demands and avoid dull sales to promote the sustainable development of the retail industry. Economic sustainability in the retail industry, which refers to a suitable return of investment, requires the implementation of precise product allocation strategies in different regions. This study proposed a hybrid model to evaluate economic sustainability in the preparation of goods of retail shops on the basis of market demand evaluation. Through a grid-based convolutional neural network, a regression model was first established to model the relationship between consumer distribution and the potential market demand. Then, another model was proposed to evaluate the sustainability among regions based on their supply-demand analysis. An experiment was conducted based on the actual sales data of retail shops in Guiyang, China. Results showed an immense diversity of sustainability in the entire city and three classes of regions were distinguished, namely, high, moderate, and limited. Our model was proven to be effective in the sustainability evaluation of supply and demand in the retail industry after validation showed that its accuracy reached 92.8%.
Highlights
The concept of sustainable development requires the identification of the demands of society and the implementation of an appropriate resource allocation strategy to satisfy requirements and to avoid expenditures
Owing to complicated consumer activities, estimation of market demand is recognized as an important concern and a main challenge for the sustainable development of the retail market [2]
To solve the limitations in current studies, to fill the gap in microscopic market potential estimation issues, and to provide many sustainable business strategies for retail shops, the current study proposed a new method to evaluate the economic sustainability of geographic units based on the estimation on the market demand of retailers through social media and actual sales data
Summary
The concept of sustainable development requires the identification of the demands of society and the implementation of an appropriate resource allocation strategy to satisfy requirements and to avoid expenditures. The estimation of consumer demand has constantly focused on a macroscopic scale and it has not provided practical business strategies for retail shops due to the lack of appropriate auxiliary social economic data with large quantity. Social media data provide a new approach to solve the problem with the development of crowd-sourcing data Such data are easy to obtain and their volume is larger than that of traditional survey questionnaires. To solve the limitations in current studies, to fill the gap in microscopic market potential estimation issues, and to provide many sustainable business strategies for retail shops, the current study proposed a new method to evaluate the economic sustainability of geographic units based on the estimation on the market demand of retailers through social media and actual sales data.
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