2021
DOI: 10.1108/dta-11-2020-0286
|View full text |Cite
|
Sign up to set email alerts
|

M-GAN-XGBOOST model for sales prediction and precision marketing strategy making of each product in online stores

Abstract: PurposeThe rapid development of e-commerce has brought not only great convenience to people but a great challenge to online stores. Phenomenon such as out of stock and slow sales has been common in recent years. These issues can be managed only when the occurrence of the sales volume is predicted in advance, and sufficient warnings can be executed in time. Thus, keeping in mind the importance of the sales prediction system, the purpose of this paper is to propose an effective sales prediction model and make di… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1
1

Citation Types

0
8
0

Year Published

2022
2022
2025
2025

Publication Types

Select...
10

Relationship

0
10

Authors

Journals

citations
Cited by 23 publications
(8 citation statements)
references
References 51 publications
0
8
0
Order By: Relevance
“…Many papers shared a methodology and structure similar to this research, such as those referenced in Refs. [ 34 , [35] , [36] , [37] ].…”
Section: Methodsmentioning
confidence: 99%
“…Many papers shared a methodology and structure similar to this research, such as those referenced in Refs. [ 34 , [35] , [36] , [37] ].…”
Section: Methodsmentioning
confidence: 99%
“…Precision refers to the percentage of genuinely useful information in all reviews, predicted as useful information by the information entropy model, and is defined as:Recall refers to the percentage of useful information correctly identified by the information entropy prediction model and is defined as: F 1 refers to the harmonic average of precision and recall and is defined as:ACC refers to the proportion of paired samples in all samples. The formula is as follows:where TP is the number of useful reviews correctly identified; FP is the number of useless reviews incorrectly classified as useful; TN is the number of useless reviews correctly classified as useless; FN is the number of useful reviews incorrectly classified as useless (Wang and Yang, 2021).…”
Section: Methodsmentioning
confidence: 99%
“…Taobao dramatically increases Alibaba's income by matching users with items they are likely interested in purchasing using AI algorithms. Alibaba projected an astonishing $72 billion in sales for the fiscal year 2020, demonstrating the extraordinary impact of AI on revenue growth (Wang & Yang, 2021).…”
Section: Revenue Growthmentioning
confidence: 99%