How Market Memory Impacts Truckload Performance

Can shippers promote more stable relationships by offering carriers consistent business and fair pricing even when the TL market pendulum swings in shippers’ favor?

Much depends on the extent to which carriers remember such largesse when negotiating the next contract, especially in tight markets when TL capacity is in short supply. In other words, whether carriers display short-term (goldfish) or long-term (elephant) memories.

Research carried out by the MIT FreightLab suggests that the goldfish usually win out. Which begs the question: How can shippers build dependable relationships with memory-challenged carriers?

The Cost of Unreliability

As the blog post mentioned above explains, carriers behave opportunistically when they reject freight loads they are contracted to carry.

There are various reasons for this conduct. For example, the trucking company’s transportation network or fleet may have changed since the contract was signed.

Shippers can act in a similar fashion. Perhaps the company’s business has changed, and the loads it offered in the contract phase are no longer available.

Whatever the reason, opportunism comes at a cost. Shippers have to find alternative capacity when their loads are rejected, which is often more expensive. Carriers are deprived of business, and their network efficiency may fall because they have positioned vehicles to carry freight that is no longer available.

A key performance indicator used by shippers is a primary carrier’s (a carrier that has been contracted business and is top of the list of favored providers for a specific lane) acceptance ratio (PAR).

This measure is the fraction of loads the carrier accepts relative to the number of loads that it is offered by the shipper on a lane it has won as primary carrier. A key challenge is how to achieve consistently high PARs even in tight markets.

Why Largesse Doesn’t Pay

The MIT FreightLab team analyzed four years of TL freight transactions from September 2015 to May 2019, which covers two complete market periods (soft and tight) provided by a logistics and transportation company, to find possible solutions to the PAR conundrum. The data covers almost 2 million loads offered by 71 shippers, tendered to 1,650 primary carriers, both asset and non-asset (brokers and third-party logistics or 3PL) providers.

The results suggest that carriers have short memories when market conditions change (goldfish). Shippers that “pay it forward” during soft markets by offering high pricing relative to the market or consistent volume do not necessarily reap better carrier behavior (i.e., higher PAR) when markets tighten.

Moreover, the converse appears to apply too: Shippers that pay below-market prices in soft market periods are not more likely to see PAR decrease when markets tighten. Carriers appear to be more focused on short-term prospects; they respond to higher current market period pricing, consistent and frequent tendering, and low dwell times (waiting times at freight facilities) with higher PAR.

Interestingly, while the findings hold across carrier service types — asset and non-asset carriers seem to demonstrate similarly myopic behaviors — different shippers may have different experiences. Larger shippers are more likely to see lower PAR in tight markets.

A possible reason is that these larger players interact with more primary carriers — including those that are more likely to reject loads because their market outlook is especially myopic.

Ways to improve behavior

In light of these findings, how can shippers strive to put relationships with carriers on a firmer footing?

The model developed by the MIT FreightLab team allows us to determine which market-specific behaviors, shipper-carrier relationship factors, and shipper and carrier characteristics are important in determining tight market PAR.

Here are some potential strategies:

• Price competitively relative to current market rates.
• Find ways to foster consistent tendering behavior. The possibilities include improving forecasting models, contracting with a larger set of carriers on volatile lanes, and bunding lanes for primary carriers to even out overall volatility.
• Reduce dwell times at destination facilities by, for example, improving truck appointment scheduling or making sure that facilities are staffed adequately during busy periods.

As a mitigating strategy to keep rates competitive with current market prices and incentivize both sides to stick with their contracts, shippers and carriers alike are considering index-based contract pricing.

Our ongoing research models carrier price sensitivities for different lane demand patterns, geographies, and carrier and freight segments. The goal is to offer insights on where the best opportunities for index-based pricing lie and suggest how shippers and carriers should design these alternative freight contracts.

Future freight research

Although the research sheds light on carrier reliability, it does have limitations. For example, while our model is a valuable tool for anticipating market behaviors, its predictive powers are relatively weak. Also, factors external to load acceptance or rejection decisions — what other lanes a carrier is serving at the time, for example — are only accounted for to a limited degree.

These limitations reinforce the case for further research, which the MIT FreightLab is pursuing. The team is developing improved carrier load acceptance predictive models. Extensions of the above models include additional shipper and carrier interactions such as how much volume the shipper tenders to the primary carrier relative to the contracted volume (e.g., surge volume and “ghost” freight — contracted demand that never actually materializes).

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