Assessing product availability in omnichannel retail networks in the presence of on-demand inventory transshipment and product substitution *

Retail networks offering high-value products with a broad mix of models, such as cars, employ ondemand inventory transshipments to avoid lost sales due to incomplete product availability. Advances in information technology, digitalization, and new emerging concepts in logistics systems such as the physical internet are facilitating the exploitation of fast and economical on-demand inventory transshipments through shared supply resources, resulting in the broader employment of on-demand transshipments in retailing and the establishment of interconnected retail networks. In such environments, the inventory profile does not alone reflect the readiness of a retail center to satisfy a customer; rather, network availability must be considered in addition to in-stock products to fully account for the potential demand that a retailer can satisfy. We propose a new model to estimate product availability in a closed-form expression under uncertain demand and in the presence of customer substitution and inventory transshipment for an omnichannel retail network consisting of retailers distributing high-value substitutable products. Our model estimates product availability for all available shopping channels considering both in-stock and network availability while accounting for the trade-off between transshipment costs and the additional customer satisfaction gained through exploring more-distant alternatives. The results of implementing the model on a pilot project for a case of recreational vehicles show that monitoring and improving product availability by the proposed model can achieve a significant reduction in supply chain-induced lost sales. (c) 2020 Elsevier Ltd. All rights reserved.

Automated summary

Retail networks utilize on-demand inventory transshipments to avoid lost sales and establish interconnected networks, estimating product availability under uncertain demand and customer substitution. The proposed model considers both in-stock and network availability, balancing transshipment costs and customer satisfaction.