Modeling of collaborative less-than-truckload carrier freight networks

Less-than-truckload (LTL) carriers, which operate on thin margins, have significant negative impacts due to empty trips, idled capacity on lots, and rising energy costs. The impacts can cascade to other industries; for example, empty trips may affect global food prices. Recent advances in Internet and information communication technologies (ICT) foster the possibility of innovative new business and operational paradigms within the small- to medium-sized LTL industry to address these concerns. One promising innovation is the concept of LTL carrier-carrier collaboration, which provides opportunities for LTL carriers to exploit synergies in operations (such as excess capacity), reduce costs associated with fleet operation, decrease lead times, increase asset utilization (power units), and enhance overall service levels. LTL carrier-carrier collaboration is a relatively unexplored concept within the freight domain, where past studies have focused on collaboration within the truckload (TL) carrier, liner shipping, airline, and rail industries. This research seeks to understand and develop LTL collaborative paradigms from the supply and demand perspectives, thereby filling a key gap in the current freight collaboration literature. From the supply perspective, three models were developed. First, a static single carrier collaboration problem (SCCP) was addressed to gain insights on the effects of single and multiple products with fixed and variable transfer costs on the LTL collaborative paradigm from a planning perspective. Second, we extend the SCCP to a deterministic dynamic single carrier collaboration problem (DDSCCP) that captures the impacts of the time dimension on the costs associated to congestion effects (such as holding costs). Then, we extend the single carrier problem to a time-dependent multiple carrier collaboration problem (TD-MCCP) to gain insights on the effect of multiple carriers collaborating. From the demand perspective, a survey was conducted to capture the LTL trucking industry’s propensity to collaborate. Using the survey data, a mixed (random parameters) logit model methodology was developed to better understand the factors that may induce carriers to collaborate. The aforementioned models provide an analytical foundation for exploring the LTL carrier collaboration paradigm