Human Factors on the Road: Truck Drivers’ Heterogeneity in Distribution

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While human factors in warehousing have received considerable attention in recent years, they remain largely underexamined in transportation. This is surprising, given that truck driver shortage and load space scarcity are recent key challenges in the logistics industry that significantly hamper the growth potential of European economies. While increasing demand for loadspace meets a decreasing availability of professional truck drivers, managers across all industries need to think about how scarce human resources can be deployed more efficiently. Therefore, the goal of this study is to quantify truck drivers’ heterogeneity in retail distribution. We formulate and apply a mixed-effect multilevel regression model where delivery routes are nested within truck drivers. The model is applied to a unique empirical dataset, including N = 51,164 routes performed by 218 truck drivers in a six-month time frame in 2021, obtained in collaboration with a German brick-and-mortar grocery retailer. We find that truck drivers’ heterogeneity accounts for 29.9% of the total route duration time variation. This impact is significantly higher compared to existing empirical research on the quantification of heterogeneity for warehouse workers and proposes a higher potential for transport managers to increase efficiency in collection and distribution by taking into account driver heterogeneity in tour planning and allocation.