The highly perishable nature of fresh products during distribution creates additional challenges for firms engaged in the supply chain in the process of matching supply with demand. This paper considers a retailer who purchases a batch of fresh products, transports and sells them to multiple consecutive markets. The demand from each market and the quantity loss from perishability during transportation are both assumed to be stochastic. The retailer needs to determine the quantity to be unloaded when he arrives at each market, with the remaining inventory being transported to the next market. The unloading quantity depends on the trade-off among factors including the current inventory level, forecast of demands from the remaining markets, and the potential perishability of products. Based on a multi-period dynamic programming model and using a stochastic modeling approach, we provide an in-depth investigation towards the optimal unloading quantity decisions for the retailer and characterize the structure of the optimal policy. Moreover, the optimal initial inventory decision is studied. By conducting some numerical experiments, we analyze the potential inventory pooling effect from making dynamic decisions. Our results show that making unloading decisions in a dynamic way is more profitable when the inventory surviving factors are negatively correlated, when the products are more perishable, when the perishability risk is high, and when the demand is less uncertain. Our research results provide some interesting and important managerial insights for the management of fresh products across multiple consecutive markets.
Key words
perishable products /
inventory management /
inventory discharge /
inventory pooling effect /
newsvendor models
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References
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