Author(s)

Jingyu Qian ¹, Guangqiang Li ¹, Shuming Li ¹, Wenchao Ma ², Yunsheng Zhang ¹

Affiliation(s)

¹ Institute of Energy and Mining Engineering, Shandong University of Science and Technology, Qingdao, China
² School of Business Administration, Qingdao City University, Qingdao, China

Corresponding Author

Jingyu Qian

ABSTRACT

There is a wide variety of vegetables and the connections between single product sales are complex. Solving the problems related to vegetable supply and sales is difficult. Therefore, it is necessary to simplify the handling of vegetable supply and sales issues to bring greater economic value. The sales of vegetables between the complexity of the connection due to the wide range of vegetables. To solve the problem of vegetable supply and marketing category, we should simplify the processing of vegetable supply and marketing category problems to bring greater economic value. In this paper, the distribution of six vegetable categories of commodity information and sales flow details of the receipt based on a supermarket in the past three years. In addition, the vegetable supply and sales of class problems are analyzed to simplify the strategy. Firstly, eliminating products with minimal sales over the past three years and utilizing box plots to filter out and remove outliers, then filling missing values using spline interpolation, completing the data preprocessing. Secondly, descriptive statistics are introduced for overall analysis to derive and visualize the distribution patterns of various classes. For the category Spearman correlation coefficient matrix, the sales volume is derived and the correlation coefficient matrix is obtained using MATLAB. For the single product correlation coefficient in the data, the systematic clustering is used to simplify it into 8 categories of daily vegetables and seasonal products, and the sales volume of each period is obtained through data analysis and the Spearman correlation coefficient matrix is derived with MATLAB. This paper combines commodity information and sales details, comprehensively interferes with data screening, statistical analysis, correlation analysis to provide a set of strategies simplifying the problem of vegetable supply and marketing. We lay the foundation for the establishment of vegetable optimization class model.

KEYWORDS

Statistical analysis, Spearman correlation coefficient, Systematic clustering

CITE THIS PAPER

Jingyu Qian, Guangqiang Li, Shuming Li, Wenchao Ma, Yunsheng Zhang, A simplification strategy for vegetable supply and marketing type problems based on correlation analysis. Information Systems and Economics (2024) Vol. 5: 58-64. DOI: http://dx.doi.org/10.23977/infse.2024.050208.

REFERENCES

[1] Santamaria P, Signore A. How has the consistency of the common catalogue of varieties of vegetable species changed in the last ten years [J]. Scientia Horticulturae, 2021, 277: 109805.
[2] Rahman S M E, Mele M A, Lee Y T, et al. Consumer preference, quality, and safety of organic and conventional fresh fruits, vegetables, and cereals[J]. Foods, 2021, 10(1): 105.
[3] Asgari S D, Mohammadi E, Makui A, et al. Data-Driven Robust Optimization Based on Position-Regulated Support Vector Clustering[J]. Journal of Computational Science, 2024: 102210.
[4] Shen Q, Qiu Y. A Novel Text Ensemble Clustering Based on Weighted Entropy Filtering Model[C]//Journal of Physics: Conference Series. IOP Publishing, 2021, 2024(1): 012045.
[5] Rodriguez-Pretelin A, Nowak W, Morales-Casique E. Optimization-based clustering of random fields for computationally efficient and goal-oriented uncertainty quantification: Concept and demonstration for delineation of wellhead protection areas in transient aquifers[J]. Advances in Water Resources, 2022, 162: 104146. 
[6] Zhou J, Lai Z, Miao D, et al. Multigranulation rough-fuzzy clustering based on shadowed sets [J]. Information Sciences, 2020, 507: 553-573.

Sponsors, Associates, and Links

---

• Accounting, Auditing and Finance
  
  
• Industrial Engineering and Innovation Management
  
  
• Tourism Management and Technology Economy
  
  
• Journal of Computational and Financial Econometrics
  
  
• Financial Engineering and Risk Management
  
  
• Accounting and Corporate Management
  
  
• Social Security and Administration Management
  
  
• Population, Resources & Environmental Economics
  
  
• Statistics & Quantitative Economics
  
  
• Agricultural & Forestry Economics and Management
  
  
• Social Medicine and Health Management
  
  
• Land Resource Management
  
  
• Information, Library and Archival Science
  
  
• Journal of Human Resource Development
  
  
• Manufacturing and Service Operations Management
  
  
• Operational Research and Cybernetics