/** * Open all external links in a new window */ jQuery(document).ready(function($) { $('a') .filter('[href^="http"], [href^="//"]') .not('[href*="' + window.location.host + '"]') .attr('rel', 'noopener noreferrer') .attr('target', '_blank'); });

Freight contract performance & portfolio strategies

 

Research publications

Research Team

Contact Team

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. These issues justify – and are exacerbated by – the non-binding nature of TL contracts. In this research, we motivate the need for improved TL contracting methods by evaluating the impact of dynamic economic environments on shipper and carrier behaviors and modeling the performance of TL contracts over their lifetimes and the corresponding cost overruns. Further, we demonstrate the performance of a portfolio of contracts as compared to traditional contracting methods.

 

Research Studies

Shipper-carrier reciprocity in dynamic freight markets

We consider the overall economic environment and analyze how market cycles impact performance and pricing for distinct shipper-carrier pairs as power dynamics fluctuate over time. In particular, we use the context of the in the truckload transportation market in 2017 Q3, when capacity tightened severely, and the subsequent soft market in 2019, and applying econometric modeling techniques and statistical analysis, explore whether (i) primary carriers maintain high freight acceptance ratios for their shippers that had proven consistent performance and competitive pricing in previous soft markets, and (ii) shippers maintain consistent tendering behavior and prices for carriers that had stuck with them in the tight market.

We demonstrate if shippers and carriers reciprocate each other’s past behaviors and as a result, whether they should continue to invest in future relationships.

Alternatives to traditional freight procurement: Market-based contracts

Perpetual freight market fluctuations are often to blame for limited capacity availability and shipper’s transportation cost overruns. Our previous research has shown that to ensure primary, or contracted carriers maintain high acceptance ratios, shippers need to keep freight rates from becoming stale as market conditions change.

We establish a method to analyze freight contracts that incorporate market-based pricing as compared to traditional fixed-price agreements. Probabilistic models of both primary and backup carriers’ freight acceptance that capture real-world uncertainties are combined with a market simulation engine to compare expected costs and carrier acceptance for different pricing strategies under various market conditions, demand patterns, carrier service types, and lane characteristics.

The results offer insights for shippers to determine how to design a market-based pricing strategy and quantify where it may be beneficial to do so. The intended benefit for carriers is to encourage shippers to adopt contractual strategies that better align with the economic dynamics carriers typically face.

Optimal contract portfolio policies

Given the uncertainties shippers face, in particular due to imperfect demand forecasts, carrier capacity availability, and overall market conditions, we propose a portfolio approach to TL fright contracting.

We determine how a shipper should cover its realized demand through a combination of contract types – including long-term fixed-price contracts, market-based contracts, short-term agreements, and spot transactions – to reduce cost and carrier performance uncertainties that are often not addressed by the traditional freight procurement process and resulting contract agreements.

 

Research Publications

Research Team

Angi Acocella

Angi Acocella

Research Assistant

Dr. Chris Caplice

Dr. Chris Caplice

Co-Director

Get In Touch

Interested in collaborating with us?

Send us a note to acocella@mit.edu