A cost-based tool for the comparison of different e-grocery supply chain strategies

Abstract

E-commerce is always a more diffused sales channel around the whole world market. The grocery market has been interested in the expansion of this phenomenon, especially during the COVID-19 pandemic emergency, when electronic grocery (e-grocery) shopping increased considerably. Moreover, it has remained a diffused selling channel also later, in the non-emergency state. To satisfy this specific market demand, grocery chains are facing the need for a redesign with a new logistic perspective. A grocer can carry out online orders in several ways; it can process them directly in stores using internal staff to shop from the shelves during off-peak hours. Alternatively, some local stores can be closed to customers and dedicated to online orders (dark stores). Another strategy is to carry out online orders from a single distribution centre (e-hub), using stores to complete orders with very fresh products and from which to carry out deliveries. Finally, online orders can be wholly managed by multi e-hubs. Each solution has different logistics costs and performances, influenced by online demand.For this reason, this work aims to present a cost-based function for grocery chains that compares four strategies to respond to e-grocery shopping. The cost function considers picking, refilling, and transport costs by varying orders and articles quantity. Further, we aim to minimise costs according to online order characteristics and volumes. We identify five decision variables to select the most suitable strategy for the design of the e-grocery network. Finally, a decision support system (DSS) is developed to define the best strategy based on the decision variables.