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January 1, 2026International Journal of Mathematics in Operational Research

An Asymmetric Logistic Growth Model for Stock-Dependent Demand Items

Anthony G. McVeigh N.A.

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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.

Implication

Examines stock-dependent demand modeling in market dynamics, suggesting improvements for demand forecasting.

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Cite This Study

Anthony G. McVeigh N.A. (2026) studied this question.

synapsesocial.com/papers/6a153a88b5d9c58d83e8d1ff https://doi.org/10.1504/ijmor.2026.10078714

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