Abstract:The growth of e-commerce has bridged the gap between the consumer and the retailer, bringing prosperity for both. However, in a quest to achieve even larger profits and market share, e-retailers compete to offer consumers cheaper shipping, expedited deliveries, free returns, and other lucrative deals. To keep pace with these growing needs of e-commerce, e-retailers have piloted various alternative distribution strategies. To aid a fuller understanding of the costs and benefits of these distribution strategies in diverse delivery environments, this work develops a multi-echelon last-mile distribution model using Continuous Approximation (CA) techniques. The model results suggest that traditional last-mile delivery with diesel trucks is a good fit for e-retailers delivering in dense environments with lenient temporal constraints (parcel service), a strategy that allows for demand consolidation and thus low-cost low-emission distribution. For e-retailers delivering in sparsely populated environments with stringent temporal constraints (grocery delivery), this work finds outsourcing alternatives (crowdsourced delivery, customer self-collection) to render low-cost distribution albeit with high emissions. As a result, the authors suggest the use of low-volume low-pollution vehicles from smaller consolidation facilities close to the market to provide expedited deliveries at fairly low costs and emissions. The analysis bolsters the case for the use of electric trucks for last-mile deliveries, as the study finds an electric truck fleet to not only eliminate tailpipe emissions but also to lower distribution costs compared to a diesel truck fleet. Thus, with this work the authors discuss the opportunities and challenges associated with different last-mile strategies for e-commerce delivery.

Key words: e-commerce, last-mile delivery, continuous approximation, crowdsourcing, micro-hubs, collection-points