Driver retention in logistics: A multi-objective approach
Abstract
Driver retention is an enormous challenge for companies such as logistics service providers and distribution companies. There is a big shortage of drivers in the market, which forces companies to compete for this scarce resource.1,2 One method to hire and retain drivers is to increase driver wages, but this is challenging in a market with low margins and heavy competition. Therefore, this paper reflects on alternative ways to increase driver satisfaction, which affords companies a unique competitive advantage to retain existing drivers or attract new, young drivers. It shows how driver satisfaction can be considered in supply chain planning: it can be modelled such that the driver’s needs and wishes can be included into operational and tactical planning decisions. These needs differ per industry, whereas personalisation plays a crucial role as well. The paper elaborates on how increasing driver satisfaction may have an impact on operational efficiency and shows that with only a slight increase in operational costs, substantial steps can be taken to create plans that are perceived as ‘better’ by the drivers. Balancing between costs, sustainability, driver satisfaction and other objectives is becoming increasingly important and requires a multi-objective approach. This paper describes such a new optimum approach and gives examples of how this can be implemented in practice.
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Author's Biography
Leendert Kok is Chief Science Architect at ORTEC. Starting as an operations research engineer specialising in vehicle routing algorithms, Leendert broadened the scope of his work into workforce and load optimisation algorithms. Next, he established the Math Innovation Team at ORTEC, focusing on broadening the scope of mathematical techniques in ORTEC’s portfolio, including data science and artificial intelligence (AI). In his current role, Leendert drives the research, innovation and development roadmaps for ORTEC’s optimisation and learning engines. He frequently speaks at academic and industrial conferences and shares ORTEC’s vision on optimisation and learning engines at key ORTEC accounts. Leendert holds an MSc in applied mathematics from the University of Twente and a PhD in industrial engineering and logistics from the same university.
Lotte Berghman is Expert Operations Research Engineer at ORTEC. After an academic career of ten years, she infused the Math Innovation Team with her knowledge on mathematical programming, algorithms and operational research. Originally, Lotte specialised in machine scheduling and supply chain optimisation problems, but recently she became immersed in the human side of optimisation problems. In her current role, Lotte is roadmap owner of all research topics concerning the new optimum and workforce scheduling at ORTEC. Moreover, she is Math Innovation Partner Lead and has regular contact with privileged clients to brainstorm about new developments. Lotte holds an MSc in commercial engineering from the Katholieke Universiteit Leuven and a PhD in applied economics from the same university. She was a researcher and teacher at Toulouse Business School, where she was Associate Professor in Supply Chain Management and Operations Research for the last four years.
Tom Bruinink is a Junior Operations Research Engineer at ORTEC, which he joined as a Master’s thesis intern on the Math Innovation Team. He focused on exploring the topic of driver happiness in vehicle routing problems, applying the expertise gained during his Master’s programme in analytics and operations research in logistics at Erasmus University. Following graduation, Tom continued his research on driver happiness while pursuing a second Master’s degree in transport infrastructure and logistics at TU Delft.
Citation
Kok, Leendert, Berghman, Lotte and Bruinink, Tom (2025, February 26). Driver retention in logistics: A multi-objective approach. In the Journal of Supply Chain Management, Logistics and Procurement, Volume 7, Issue 3. https://doi.org/10.69554/EFSU1925.
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