Intelligent Supply Chain Demand Forecasting and Inventory Management Strategies

With the acceleration of globalization and the increasingly fierce competition in the market, demand forecasting and inventory management in supply chain management have become particularly important. Traditional supply chain management methods are difficult to cope with the complex and changing market demand, resulting in the frequent occurrence of inaccurate forecasts, excessive or insufficient inventory, and other problems. This paper aims to explore the application of intelligent technology in supply chain demand forecasting and inventory management, focusing on analyzing how technologies such as big data, artificial intelligence, and machine learning can improve forecasting accuracy and inventory management efficiency. Through the analysis of actual cases, this paper demonstrates the implementation effect of intelligent demand forecasting technology and proposes corresponding inventory management optimization strategies. The study shows that intelligent supply chain management can not only effectively reduce operating costs, but also improve service levels, thus enhancing the competitiveness of enterprises in a dynamic market environment

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Publication Details

Journal
Transactions on Economics Business and Management Research
Published
2024-09-28
DOI
https://doi.org/10.62051/ejb42e55
Citations
1
Primary Topic
Forecasting Techniques and Applications
Type
article
Field-Weighted Citation Impact
0.49
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article

Intelligent Supply Chain Demand Forecasting and Inventory Management Strategies

Shijie Luo
1 citations
Transactions on Economics Business and Management Research
Forecasting Techniques and Applications
0.49
article

Intelligent Supply Chain Demand Forecasting and Inventory Management Strategies

Shijie Luo
article en
1 citations

Abstract

With the acceleration of globalization and the increasingly fierce competition in the market, demand forecasting and inventory management in supply chain management have become particularly important. Traditional supply chain management methods are difficult to cope with the complex and changing market demand, resulting in the frequent occurrence of inaccurate forecasts, excessive or insufficient inventory, and other problems. This paper aims to explore the application of intelligent technology in supply chain demand forecasting and inventory management, focusing on analyzing how technologies such as big data, artificial intelligence, and machine learning can improve forecasting accuracy and inventory management efficiency. Through the analysis of actual cases, this paper demonstrates the implementation effect of intelligent demand forecasting technology and proposes corresponding inventory management optimization strategies. The study shows that intelligent supply chain management can not only effectively reduce operating costs, but also improve service levels, thus enhancing the competitiveness of enterprises in a dynamic market environment

Transactions on Economics Business and Management ResearchVol. 12
Qingdao University of Technology (CN)
Openalex Percentile: Top 31%
Forecasting Techniques and Applications
0.49
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