An Analysis of Community Group Buying Behavior of Urban Residents Based on Big Data | Zendy

Nanxin Huang | Zendy; Kexin Yu | Zendy; Chen Cheng | Zendy

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An Analysis of Community Group Buying Behavior of Urban Residents Based on Big Data

Author(s) -

Nanxin Huang,

Kexin Yu,

Chen Cheng

Publication year - 2021

Publication title -

mathematical problems in engineering

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.262

H-Index - 62

eISSN - 1026-7077

pISSN - 1024-123X

DOI - 10.1155/2021/1819323

Subject(s) - cluster analysis , logistic regression , scale (ratio) , big data , marketing , group (periodic table) , psychology , computer science , advertising , business , data mining , geography , artificial intelligence , machine learning , cartography , chemistry , organic chemistry

By using keywords crawled by big data as a survey reference, this research applied latent category clustering method and binary logistic regression model analysis method to analyze the differences in community group buying behaviors of residents from different city scale and summarize the shopping behavior and features of different types of residents, for the purpose of offering advice on different marketing methods for different types of urban residents, so as to realize the precise marketing of community e-commerce and promote the further development of the industry.

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