How customer requirements impact the operational performance of LTL carriers

Jacques Renaud, Leandro C. Coelho and Quentin Marissiaux

Transportation Research Part A: Policy and Practice, 2026, vol. 211, issue C

Abstract: Less-than-truckload (LTL) carriers play a central role in goods distribution. Their operations face numerous challenges such as traffic congestion, next-day delivery, and the various requirements of their customers. Environmental and government pressure to reduce greenhouse gas emissions pushes the road freight industry to constantly improve its operations. Using data from three major carriers in the province of Québec, in eastern Canada, we demonstrate the impact of constraints imposed by their customers, specifically time windows that limit when they must be visited. We show that the performance of carriers is close to optimal with empty mileage percentages of 4.4 to 11.2% and with no possible distance improvement given the presence of required time windows (visiting times imposed by the customers). Relaxing this constraint to two-hour windows allows improvements of 4.2 to 10.2%; completely removing these constraints allows improvements of 7.8 to 13.4%, with some routing saving as much as 42.5%. These numbers directly indicate that strict customer requirements negatively affect the performance of the transportation industry. These time windows lead to increased mileage, fuel consumption, greenhouse gas emissions, and congestion. We have also evaluated the impact of technology and dispatching optimization, showing that when all routes are globally optimized without time windows, gains of more than 30% are typical, and with tight time windows of 2h the average savings reach 23.3%. These results show that dispatchers are efficient in individual route optimization, but transportation management systems are still far from providing global optimization. Finally, we demonstrate the major negative impact of time windows that customers impose.

Keywords: Less-than-truckload; Road freight; Customer requirements; Real data analysis (search for similar items in EconPapers)
Date: 2026
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DOI: 10.1016/j.tra.2026.105123

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