6. Conclusions
This paper develops an inventory model with non-instantaneously
delivery under trade credit and logistics risk. This
research seeks to determine the optimal replenishment policy
for a retailer given uncertainty in a supply-chain’s logistics
network due to unforeseeable disruption or various types
of defects (e.g. shipping damage, missing parts, misplacing
products and or disasters such as earthquake or hurricane).
Also, the supplier may often provide forward financing to
the retailer in practice. As a result, the influences of trade
credit cannot be ignored on modeling inventory system. This
paper considers that the supplier provides a credit period
to the retailer. The objective is to determine the optimal
replenishment policy under trade credit and logistics risk.
Two solution procedures from the perspectives of risk-neutral
and risk-averse are provided respectively. For the risk-neutral
solution, the objective is to determine the cycle time to
minimize the expected total cost. For the risk-averse solution,
the model limits the solution space to the set of cycle
times which guarantees an upper bound of defective products
under contingency. The risk management operations research
technology is very useful for the case of a low-probability highconsequence
contingency event. From numerical experiments,
we obtain that the retailer will increase the cost under riskaverse
solution. This is due to the retailer want to make sure that
the expected number of defective products is less than an upper
bound. For the further research, this paper can be extended to
consider other realistic situations, such as for deteriorating item
or seasonal product.