Development of an Inventory Management Strategy Model (Two-Products) Based on Demand Predicting in Digital Supply Chain Networks by Combining Data Analysis Methods | ||
| Advances in Industrial Engineering | ||
| دوره 60، شماره 1، شهریور 2026، صفحه 165-184 اصل مقاله (1.15 M) | ||
| نوع مقاله: Research Paper | ||
| شناسه دیجیتال (DOI): 10.22059/aie.2026.406483.1962 | ||
| نویسندگان | ||
| Ehsan Mardan* 1؛ Ali Qorbani2 | ||
| 1Assistant Professor, Department of Industrial Engineering, Semnan University, Semnan, Iran. | ||
| 2M.Sc., Department of Industrial Engineering, Semnan University, Semnan, Iran. | ||
| چکیده | ||
| Recording and classifying commerce data electronically within the new age of information and development has many benefits for sellers and consumers in the online supply chain. We can predict customer purchase behavior patterns by analyzing this classified data. In recent years, digital stores have received additional attention due to their advantages. On the other hand, the performance of these stores is directly associated with the performance of their suppliers. Hence, supply chain management is essential during this sales system. In this investigation, the classification methods (WFRM), demand prediction analysis (Binary Logistic Regression), data classification (Discriminant Analysis), time series analysis (Trend Analysis), and mathematical modeling have been used to select suppliers to order led to the development of a management strategy to prevent shortages and reduce the average inventory and costs of sending and producing for suppliers. It ultimately covers a 29% error in sales data for assigning suppliers to orders. | ||
| کلیدواژهها | ||
| Customer Clustering؛ Data Mining؛ logistic Regression؛ Online Supply Chain؛ Demand Forecast | ||
| مراجع | ||
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آمار تعداد مشاهده مقاله: 127 تعداد دریافت فایل اصل مقاله: 60 |
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