Abstract

This study investigates the evolution and reconfiguration of last-mile delivery strategies in the U.S. e-commerce sector, focusing on both technological and operational innovations. The study was anchored on four research objectives with Theory of Constraint (TOC) providing the theoretical anchor. Quantitative Survey Research Method was used with questionnaire as the instrument of data collection. Using supply chain managers, warehouse coordinators, and last-mile delivery operators working in logistics firms engaged in e-commerce fulfilment as the population of the study, a total of 250 respondents were selected as sample size based on the recommendation of Comrey and Lee (1992) and that of Kline (2005) who posited that in a population without definite number, a sample of 100 is considered small, a sample of 100 to 200 is medium, and a sample over 200 is considered large. Finding revealed that the explosive growth of e-commerce has put significant strain on traditional last-mile delivery models, thus, e-commerce growth has significantly reshaped strategic decision-making in the US’s last-mile logistics. While urban traffic and regulations, suburban route inefficiencies and rural infrastructure gaps were found as the geographical disparities in last-mile delivery efficiency and infrastructure, findings equally revealed that artificial intelligence and route optimization tools are the most widely adopted innovations (mean = 4.21) in last-mile delivery, followed closely by micro-fulfillment strategies (mean = 4.11), while autonomous delivery technologies as well as collaborative delivery platforms followed with (mean = 3.64), and (mean = 3.69) respectively. In light of the findings and guided by the Theory of Constraints (TOC), it was recommended that logistics firms operating within the U.S. e-commerce landscape adopt a constraint-focused approach to last-mile delivery strategy. Firms must first identify the primary bottlenecks, be they infrastructural, technological, labour-related, or geographic and apply tailored innovations to exploit and eventually elevate these constraints.