## Qualitative and Quantitative Analysis of the Puerile Strategy on Big Data

Author(s)

Haijun Yuan

Corresponding Author:
Haijun Yuan
Affiliation(s)

Basic Course Teaching Department, Shandong Institute of Commerce and Technology, Jinan, Shandong, China

### Abstract

With the advent of the era of big data, the economic market has been in a dynamic change. In order to adapt to this change, many companies have implemented a widely used strategy of expanding sales at low prices and low interests - “puerile”. Thus, we analyze the “puerile” strategy from three aspects: turnover, profit margin, and discount strength of the mall. Through mathematical modeling, charts are created by collecting the sales data of a shopping mall in 2017 and 2018. By separating and filtering the collected data, the data with missing cost prices is separated and filtered out. The abnormal data is excluded, and the required data is finally obtained. By finding minimum and maximum profit margins, the average daily profit margin and turnover of the mall based on small profits and high sales are calculated. By setting the four indicators to measure the discount strength of the anti-discount sum, sales volume ratio, turnover ratio, and cost ratio, a linear weighting mathematics model of the discount force is established. Finally, the daily discount strength is classified, and the size of the discount force is analyzed.

### Keywords

the puerile strategy, the big data, discount strength, linear weighting function

### Cite This Paper

Haijun Yuan. Qualitative and Quantitative Analysis of the Puerile Strategy on Big Data. Academic Journal of Business & Management (2023) Vol. 5, Issue 4: 70-76. https://doi.org/10.25236/AJBM.2023.050412.

### References

[1] He Shengming. Dictionary of Finance and Economics [M]. China Finance and Economic Press, 1990.

[2] Yi yang, Profit points for small profits and high sales. Brilliance [J]; 2018, (12):34-35.

[3] National University Mathematical Modeling Organizing Committee. 2019 National College Students Mathematical Modeling Competition Questions;http://www.mcm.edu.cn/html_cn/node/ b0ae8510b9ec 0cc0deb2266d2de19ecb.html

[4] Jiang Qiyuan, Xie Jinxing. Anthology of Mathematical Modeling Cases [M].Beijing: Higher Education Press, 2006.

[5] Zhuo Jinwu. MATLAB Mathematical Modeling Methods and Practices [M]. Beijing: Beihang University Press. 2018.

[6] Yu Xin, Xu Shiming. Applied Mathematics of Economics [M]. Beijing: Higher Education Press, 2009.

[7] Yang Mingsheng, Lin Jianhua. MAthematica Basics and Mathematical Software [M].Dalian: Dalian University of Technology Press, 2003.

[8] Zheng Li, Chen Yu, Li Liang. A segmented study of the problem of "small profits but high sales". Mathematical Modeling and Its Applications [J]; 2020, 12(4):101-109.

[9] Deng Minghua, Xue Yi. Statistical modeling and analysis of "small profits, high sales". Mathematical Modeling and Its Applications [J]; 2020, 9(1):67-71.

[10] Tong Qiang. Correlation analysis between "promotional activities" and revenue based on big data analysis of shopping mall sales; Computer Knowledge and Technology[J].2022.18(5):34-37.

[11] Fu Feier, Analysis of the Factors Influencing the Sales of Museum Cultural and Creative Products under the Background of "Internet +". Industrial Innovation Research [J], 2022, 4(8):25-28.