Centralized Time-Dependent Multiple-Carrier Collaboration Problem for Less-Than-Truckload Carriers

cooperative alliances also arises from the need to address emerging concerns, such as the increase in shipper requirements and the role of the Internet and ICT in enhancing competition. Thus, a key operational challenge for carrier–carrier collaborative networks is to address these issues within a cooperative alliance and create win–win situations for all members in the alliance. LTL carrier collaboration can be a powerful new paradigm to improve operations. By collaborating, smallto medium-sized LTL carriers can increase asset utilization (such as unused capacity) and strengthen their market positions. The challenge for a collaborative effort is to find a balance between the multiple requests from the LTL carriers for resources and the available transportation capacity to meet those requests. This balance depends on the affordability of the transportation services provided to the collaborative member carriers and on the shipment size and value. An agreement between member carriers would entail that both parties involved in a collaborative transaction believe that they are benefiting from that transaction (for example, through reduced costs or increased profits). Carrier collaboration among multiple carriers can be induced from the identification of win–win solutions for the members in the collaborative. One potential approach to identify such solutions is to study the rate-setting dynamics (behavior) of these smallto medium-sized LTL carriers. These rate-setting behavioral strategies can provide insights into the operational characteristics that may lead to a successful collaborative effort. For example, carriers that are trying to establish density between specific facilities or on certain transit corridors may charge reduced rates to provide capacity on those corridors in a collaborative setting. From an implementation perspective, if a third-party logistics (3PL) firm undertook the task of identifying collaborative opportunities for member clients in need of capacity, it could first search for carriers that are trying to establish density on various transit corridors. With the advances in the ICT domain, 3PL firms can easily keep track of carriers and update their rate-setting tendencies (rates may also change depending on the economic climate or other unforeseen events). Each carrier may consider different factors to determine the rate it will charge to fulfill a collaborative shipment request; for example, based on the shipment type, a carrier may charge different rates to ship perishable as opposed to nonperishable goods. In this study, three rate-setting behavioral strategies are considered. First, some carriers may be revenue driven. They will charge higher collaborative rates, independent of the volume the carrier serves; in essence, these carriers will charge a rate based on the current market value for moving a shipment (2). Second, some carriers may be volume oriented. They will be more concerned with establishing density on shipment routes between certain terminals; these carriers’ rates will typically be set Centralized Time-Dependent Multiple-Carrier Collaboration Problem for Less-Than-Truckload Carriers