This paper develops procedures to identify and quantify the role played by large urban freight traffic generators as contributors of truck traffic in metropolitan areas. Although ports, container terminals, and other industrial sites are usually associated with large generations of truck trips, they only represent a small proportion of the total trips produced and attracted in large metropolitan areas. This paper analyzes the importance of other facilities such as ordinary businesses or buildings that individually or collectively (clusters) generate a large proportion of truck traffic. The paper discusses the opportunities of these large traffic generators for city logistics initiatives. In addition, the paper introduces two effective and complementary procedures to identify these generators using freight trip generation models estimated by the authors.

The COVID-19 pandemic led to a significant breakdown of the traditional retail sector resulting in an unprecedented surge in e-commerce demand for the delivery of essential goods. Consequently, the pandemic raised concerns pertaining to e-retailers' ability to maintain and efficiently restore level of service in the event of such low-probability high-severity market disruptions. Thus, considering e-retailers' role in the supply of essential goods, this study assesses the resilience of last-mile distribution operations under disruptions by integrating a Continuous Approximation (CA) based last-mile distribution model, the resilience triangle concept, and the Robustness, Redundancy, Resourcefulness, and Rapidity (R4) resilience framework. The proposed R4 Last Mile Distribution Resilience Triangle Framework is a novel performance-based qualitative-cum-quantitative domain-agnostic framework. Through a set of empirical analyses, this study highlights the opportunities and challenges of different distribution/outsourcing strategies to cope with disruption. In particular, the authors analyzed the use of an independent crowdsourced fleet (flexible service contingent on driver availability); the use of collection-point pickup (unconstrained downstream capacity contingent on customer willingness to self-collect); and integration with a logistics service provider (reliable service with high distribution costs). Overall, this work recommends the e-retailers to create a suitable platform to ensure reliable crowdsourced deliveries, position sufficient collection-points to ensure customer willingness to self-collect, and negotiate contracts with several logistics service providers to ensure adequate backup distribution.