Education, Science, Technology, Innovation and Life
Open Access
Sign In

Statistical Analysis of Fresh Produce Retail Data in Convenience Stores and Optimization of Pricing Strategies

Download as PDF

DOI: 10.23977/infse.2023.041015 | Downloads: 15 | Views: 271

Author(s)

Hanzhi Xu 1

Affiliation(s)

1 School of Mathematics Science, Shanxi University, Taiyuan, Shanxi, 237016, China

Corresponding Author

Hanzhi Xu

ABSTRACT

The sales volume of various supermarket categories is influenced by market and seasonal factors. In the short term, demand for different categories of vegetables fluctuates. Unreasonable purchasing and pricing strategies can inevitably lead to losses. To maximize supermarket profits, a comprehensive analysis of automatic replenishment and pricing strategies for vegetable products is of great significance for fresh food supermarkets. We utilize multiple linear regression to model the sales volume of each vegetable category, coupled with ARIMA-derived wholesale prices for each category in the next 7 days for planning. Finally, we employ simulated annealing to determine the optimal replenishment and pricing strategies, aiming to maximize revenue in the future 7 days.

KEYWORDS

Multiple Linear Regression, ARIMA, Simulated Annealing Algorithms

CITE THIS PAPER

Hanzhi Xu, Statistical Analysis of Fresh Produce Retail Data in Convenience Stores and Optimization of Pricing Strategies. Information Systems and Economics (2023) Vol. 4: 109-115. DOI: http://dx.doi.org/10.23977/infse.2023.041015.

REFERENCES

[1] Han Xianjun, Liu Yanli, Yang Hongyu. Multiple linear regression-guided stereo matching algorithm [J]. Journal of Computer-Aided Design & Computer Graphics, 2019, 31 (1): 84-93.
[2] Cui Yibin, Liu A, Ding A, Chao A, Zheng A. Analysis of pollution sources in Chang tan Reservoir, Zhejiang Province based on absolute principal component-multiple linear regression (APCS-MLR) model[J]. Journal of Ecology and Rural Environment, 2023, 39 (4).
[3] Zhang M. Forecasting of runoff in the lower Yellow River based on the CEEMDAN-ARIMA model [J]. WATER SUPPLY, 2023, 23 (3).
[4] Yu Z. ARIMA Modelling and Forecasting of Water Level in the Middle Reach of the Yangtze River [M]. 4th International Conference on Transportation Information and Safety (ICTIS), 2017.
[5] Phillips C, Hoenigman R, Higbee B. Food Redistribution as Optimization [J].  2011. DOI:10.1371/journal.pone.007553.
[6] Zhou Junjie. Annealing inversion of geomagnetic simulation considering prior information [J]. Geological Review, 2023, 69 (S01).
[7] Yang Haoxu. Correlation analysis of vegetable price and sales volume——Taking oil wheat as an example [J]. Food Safety Guide, 2018 (21). 

Downloads: 7479
Visits: 147642

All published work is licensed under a Creative Commons Attribution 4.0 International License.

Copyright © 2016 - 2031 Clausius Scientific Press Inc. All Rights Reserved.