Analysis of Merchandise sales by factor, principal component and cluster models
DOI: 10.23977/infse.2024.050119 | Downloads: 9 | Views: 163
Author(s)
Jiayi Wang 1, Chunhua Ji 1
Affiliation(s)
1 Zhonghua Vocational College of Ynufe, Yunnan University of Finance and Economics, Anning, 650399, China
Corresponding Author
Jiayi WangABSTRACT
The correlation between different categories was determined by analyzing the six categories through factor analysis model, in which the correlation between cauliflower and leafy vegetables was the strongest, and the correlation between cauliflower and eggplant was the weakest. The method used in this paper can correlate the correlation between vegetables, and provide qualitative and quantitative analysis for the sales behavior between different vegetable dealers, and provide reference ideas and suggestions for their reasonable and effective operation. By considering the correlation between goods, their placement can be improved to result in a chain reaction of dish sales and improve overall sales. This can be achieved by placing complementary dishes together, allowing customers to directly purchase items that complement their meal. The goal is to achieve breakthroughs from a single product to the category.
KEYWORDS
Factor analysis, PCA, K-means clusteringCITE THIS PAPER
Jiayi Wang, Chunhua Ji, Analysis of Merchandise sales by factor, principal component and cluster models. Information Systems and Economics (2024) Vol. 5: 141-147. DOI: http://dx.doi.org/10.23977/infse.2024.050119.
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