The growth of e-commerce, spurred by the internet, has bridged the gap between the consumer and the retailer, bringing comfort for the consumer and prosperity for the retailer. However, in a quest to achieve even larger market share, e-retailers make lucrative offers, such as free shipping, free returns, rush deliveries etc. This has made last-mile ever more demanding. To keep pace with growing demands of e-commerce, last-mile operators have implemented various alternate last-mile strategies. This includes use of crowd-shipping services, deployment of consolidation facilities and/or collection-points coupled with use of alternate fuel vehicles, such as electric trucks, cargo-bikes and drones. While these strategies have been extensively studied in the literature, yet a comprehensive knowledge about how different strategies compete and compare is lacking. Thus, the author proposes to develop 1) unique markets and delivery environments by assessing consumer, e-retailer and regulatory body behavior, 2) a Time-Dependent Dynamic-Stochastic Capacitated Vehicle Routing Problem heuristic with Time-Windows (TD-DS-CVRPTW) to model the multi-echelon last-mile operations, and 3) a sustainability assessment tool to evaluate economic and environmental efficacy of last-mile strategies. Thereby, this work expects to develop a comprehensive knowledge of the capabilities of different last-mile strategies and policies for varied markets and delivery environments.