Feb 22, 2020 | Current Projects
In the U.S. truckload (TL) industry, shippers and motor carriers face major challenges as a result of uncertainties in the amount and timing of demand for capacity, availability of trucks at the time and locations needed, and external market conditions.
Feb 11, 2020 | Previous Projects
The project aims at predicting long haul truckload spot market rates in continental USA for the near future. Accurate forecasting of transportation costs is a key step in logistical planning. It helps buyers and sellers
of transportation services make better decisions at all stages of a supply chain.
Feb 11, 2020 | Current Projects
We analyze shipment data for assessing the impact of natural disasters on freight movement. Our focus is on North-Atlantic hurricanes that make landfall in the contiguous USA. Quantifying the impact of natural disasters on the truckload industry can help shippers know what costs to expect, what routes to avoid, how to procure and position relief goods.
Feb 11, 2020 | Current Projects
The Driver Initiative looks to uncover new insights and identify specific opportunities to improve the effectiveness, efficiency, and quality of life of American over-the-road truck drivers through an analysis of individual driver actions and behavior using ELD and other related data
Dec 27, 2019 | Previous Projects
This continuing project examines how truckload transportation rates are impacted by different policies, procedures, and network characteristics. Various econometric techniques were employed to quantify these impacts. Additionally, the projects uncovered actions that both shippers and carriers can take to reduce overall transportation cost.
Apr 22, 2017 | Previous Projects
The future rarely moves in predictable, incremental ways. Often seemingly small changes in technology, demographics, regulations, economics, or a myriad of other factors have dramatic and unintended impacts on how companies source, manufacture, distribute and operate in general. These non-linear impacts are very difficult to predict using traditional forecasting methods and techniques since they, by definition, do not follow any historical patterns.