Open AccessInvestigation and Study on Students’ Online Shopping Consumption under the Background of Big Data
Author(s) -
Chun-rui Tao,
Siwei Wang
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1616/1/012009
Subject(s) - consumption (sociology) , logistic regression , the internet , government (linguistics) , big data , order (exchange) , computer science , statistical software , regression analysis , software , advertising , psychology , world wide web , data science , business , sociology , data mining , social science , linguistics , philosophy , finance , machine learning , programming language
With the rapid development of social and economic growth of the Internet, online shopping has become an indispensable part of people’s lives, college students has become a main force in online shopping. Although online shopping has gradually matured, there are still many problems, and the problems are worth discussing. Based on the social background of big data, based on the questionnaire survey on the online shopping consumption of students of the International College of Zhengzhou University, this article uses the basic statistical analysis methods, correspondence analysis, and SPSS software and EXCEL software. Use Logistic regression method to analyze students’ online shopping consumption. Combined with the status of students’ online shopping, find out the differences of students’ online shopping behaviors, analyze the psychological characteristics of online shopping consumption, in order to correctly guide students’ consumption concepts. Then logistic regression analysis was used to find out the key factors that influence students’ online shopping frequency. Finally, based on the previous analysis conclusions, the school, e-commerce, and the government propose corresponding countermeasures.