An Asymmetric Logistic Growth Model for Stock-Dependent Demand Items

Key Points

• The research aims to develop and analyze an asymmetric logistic growth model specifically for stock-dependent demand items.
• Developed a mathematical model to describe stock-dependent demand dynamics.
• Analyzed market data to validate the model's effectiveness in predicting demand patterns.
• Tested the model's application across various stock-dependent items.
• The asymmetric logistic growth model showed a significant improvement in demand prediction accuracy.
• Demand forecasts aligned closely with market data, enhancing stock optimization strategies.
• Application of the model demonstrated a potential increase in sales efficiency.