This paper proposes a decision-making framework to help vendors and retailers choose between vendor-managed inventory (VMI) and retailer-managed inventory (RMI) contracts under deterministic and stochastic demand conditions. While VMI is widely adopted, its cost-effectiveness depends on the specific supply chain context, creating a need for structured decision support. The study develops two mixed-integer linear programming formulations based on four VMI contract variants derived from inventory ownership and transportation cost-sharing principles inspired by INCOTERMS.

Two decision tools are introduced. The “All or Nothing” model selects VMI only when it achieves the lowest supply chain cost without increasing either partner’s individual cost; otherwise, RMI is chosen. The “Best VMI” model is more flexible and accepts a VMI contract whenever it reduces total cost relative to RMI without worsening individual costs. A ranking tool is also proposed to help vendors choose contracts according to their preferences regarding inventory and transportation responsibilities.

The framework is evaluated under different demand patterns, volumes, variability levels, and intermittent demand. The results show that transportation and inventory costs, demand volume, variability, and intermittence strongly influence VMI adoption, while seasonality has little impact. The study also extends the analysis to stochastic and risk-averse settings.