Drought Hits Shippers on Great Lakes
Question 4
The shipment size decision is difficult to analyze and to model because of the lack of data. Trade-off between shipment size and operations flexibility depends on key factors: commodity, size and weight, distance, value, desired travel time, costs and service level requirements. In regard to bulk deliveries of items such as iron, steel, cotton, wheat between two destinations – negative effect is observed on large carriers whose logistics dictate to charge clients on “per weight” basis. With each inch of lower water at ports, those carriers lower loads by 1200-1500 tons, which is substantial blow to their earnings and ability to make a delivery in one transaction. This is also not cost-effective from operational perspective – with fuel, labor, HR, insurance cost doubling if another trip is necessary. However, with less weight on the vessel: the speed of delivery, loading, offloading, and insurance cost taken all decrease, thus having a positive effect on the triple bottom line.
Increase of logistic systems efficiencies, both being able to send smaller shipments when needed and in using the whole capacity of vehicles in order to move freight cheaply as much as possible – this technological approach has increased the demand for smaller, faster, frequent, “on-demand” shipments. As levels dropped, early adopters to smaller freight shipments took advantage of this approach. Smaller vessels have easier approach and maneuverability – allows for multiple stops, pick and drop off, which larger vessels do not offer. It is important to understand that demand for both types of vessels and weight exists in parallel. Trade-off can be quantified in terms of: cost, time elasticity, distance travelled, and shipment size. Formula below is derived to help understand logistics of choice and trade-off. “y=β0+nXi=1βiδi!n(D) +η” (Holguin-Veras 2002). By placing mentioned above variables into formula, one can better understand the specifics of each delivery
The shipment size decision is difficult to analyze and to model because of the lack of data. Trade-off between shipment size and operations flexibility depends on key factors: commodity, size and weight, distance, value, desired travel time, costs and service level requirements. In regard to bulk deliveries of items such as iron, steel, cotton, wheat between two destinations – negative effect is observed on large carriers whose logistics dictate to charge clients on “per weight” basis. With each inch of lower water at ports, those carriers lower loads by 1200-1500 tons, which is substantial blow to their earnings and ability to make a delivery in one transaction. This is also not cost-effective from operational perspective – with fuel, labor, HR, insurance cost doubling if another trip is necessary. However, with less weight on the vessel: the speed of delivery, loading, offloading, and insurance cost taken all decrease, thus having a positive effect on the triple bottom line.
Increase of logistic systems efficiencies, both being able to send smaller shipments when needed and in using the whole capacity of vehicles in order to move freight cheaply as much as possible – this technological approach has increased the demand for smaller, faster, frequent, “on-demand” shipments. As levels dropped, early adopters to smaller freight shipments took advantage of this approach. Smaller vessels have easier approach and maneuverability – allows for multiple stops, pick and drop off, which larger vessels do not offer. It is important to understand that demand for both types of vessels and weight exists in parallel. Trade-off can be quantified in terms of: cost, time elasticity, distance travelled, and shipment size. Formula below is derived to help understand logistics of choice and trade-off. “y=β0+nXi=1βiδi!n(D) +η” (Holguin-Veras 2002). By placing mentioned above variables into formula, one can better understand the specifics of each delivery
Bibliography: page: Gouvernalt, Elizabeth, and Lorant Tavazzy. "The Choice of Shipment Size in Freight Transport." University of Paris, 14 Dec. 2009. Web. 24 June 2013