No abstract

An important element of the U.S. motor carrier industry is the transportation spot market. The transportation spot market consists of shipments handled on a one-time, load-by-load basis and exists to facilitate urgent or unfulfilled demand. This market is characterized by price volatility and uncertainty in the availability of capacity. These aspects of the spot market make it challenging for shippers who rely on it. Because of the severe shortage of spot market capacity and the relatively high and volatile prices, shippers must actively seek carrier capacity (i.e., conduct traditional transportation auctions). Often, shippers employ the help of third parties. This research yields insight into the spot market by presenting some results of a hypothetical field experiment on spot market transactions for truckload shipments. The assumption was that a shipper's efforts to secure truckload capacity could be improved with better information on how carriers valued potential transactions differently. The research demonstrated that given choice data, accurate estimation of the minimum amount of compensation various carriers require to provide capacity (i.e., the reservation price) was possible. Furthermore, the research explored the practice of sourcing multiple spot market loads simultaneously, or bundling. The insights from this study can lead to improved decision making and improved business outcomes for shippers and carriers alike.

No abstract

Pricing shipments and sourcing capacity for a third-party logistics (3PL) provider operating in a spot market requires real-time decision making that is ripe for computer-based support driven by analytics. A decision support system outlined here leverages the 3PL provider's historical shipment data along with its knowledge of both sides of the shipping process to increase profits and to better perform the pricing and sourcing tasks. At the core of the system are discrete choice models for shippers and carriers along with a profit maximization model. The discrete choice models predict the acceptance or rejection of an offer for a shipment to shippers and a bid for capacity to carriers. The profit maximization model determines the shipper price that maximizes the 3PL provider's expected profit. In addition to those models are procedures for determining a list of potential carriers for an incoming shipment and also for ranking those carriers. As its main outputs, the system produces a shipper price and a ranked carrier list. The system is applied to real-world data provided by a 3PL company, with excellent results. The system is able to produce competitive yet profitable prices and to select potential carriers that would increase the 3PL provider's profits.

No abstract