Logistic regression is a statistical analysis method used in logistics and supply chain analytics to model the probability of a binary outcome, such as delivery success or failure. It helps organizations predict risks, optimize routes, and improve operational decisions based on historical data. Logistic regression is widely applied in demand forecasting, inventory planning, and predictive maintenance.
Characteristics:
- Models probability of binary outcomes
- Supports risk prediction in logistics operations
- Optimizes transportation routes
- Aids demand forecasting and inventory planning
- Enables data-driven decision-making
