University of Tehran Press Advances in Industrial Engineering 2783-1744 60 1 2026 06 01 Development of an Inventory Management Strategy Model (Two-Products) Based on Demand Predicting in Digital Supply Chain Networks by Combining Data Analysis Methods 165 184 106091 10.22059/aie.2026.406483.1962 EN Ehsan Mardan Assistant Professor, Department of Industrial Engineering, Semnan University, Semnan, Iran. 0000-0002-3611-2683 Ali Qorbani M.Sc., Department of Industrial Engineering, Semnan University, Semnan, Iran. 0000-0003-0850-8661 Journal Article 2025 11 17 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. https://aie.ut.ac.ir/article_106091_7f827b8e863d484b8b48234c2491fd8a.pdf