Driving factors analysis model of social e-commerce platform users' shopping intention based on regression analysis method
by Jiangdai Li; Changyi Jin; Jing Zeng
International Journal of Networking and Virtual Organisations (IJNVO), Vol. 29, No. 3/4, 2023

Abstract: In order to analyse the driving factors of shopping intention of social e-commerce platform users and improve the effectiveness of user shopping intention analysis, this article proposes a regression analysis-based model for analysing the driving factors of shopping intention of social e-commerce platform users. Firstly, the improved synthetic minority oversampling technique (BSMOTE) algorithm is used to sample process the user shopping intention data. Secondly, singular value decomposition (SVD) is used to analyse the data set and shopping intention topics. Then, regression analysis is used to quantitatively describe the driving factors and user shopping intentions, eliminate interfering factors, and construct a model for analysing the driving factors of user shopping intention. The sum of squares decomposition formula is used to modify the model and complete the model construction. Experimental results show that the proposed method can effectively analyse the factors, with an accuracy rate of 95.16% and a recall rate of over 95%.

Online publication date: Wed, 10-Jan-2024

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Networking and Virtual Organisations (IJNVO):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com