Ensuring an adequate truck driver workforce is a key policy concern for governments seeking resilient supply chains. In recent years, workforce contraction has intensified this challenge. In the aftermath of the COVID19 pandemic, many national governments introduced recruitment-focused measures, however worker retention received comparatively less attention. Drawing on a 2023 survey designed and administered to UK truck drivers (N = 1756), Structural Equation Modelling (SEM) is used to examine how job satisfaction, health and wellbeing, flexible work arrangements and workplace discrimination are associated with intention to quit or remain working as a truck driver. Drivers reporting higher job satisfaction and wellbeing were less likely to intend to leave the occupation (inter-occupational turnover). The availability and uptake of diverse work arrangements was associated with better retention outcomes through higher satisfaction and wellbeing, whereas experiencing discrimination was associated with lower retention. Company size and worker age also had direct associations with quitting intentions and retention, while contract type and caring responsibilities operated mainly through their relationships with satisfaction, wellbeing and discrimination. The findings indicate how truck driver retention is shaped by the interaction between working conditions, health and the fit between paid work and life outside work. These findings support a shift from recruitment-led responses towards retention-oriented transport policy, including stronger health and wellbeing provision, more predictable working hours and flexible working arrangements, and effective protection against discrimination. These measures will require support through employment regulation, freight procurement standards and buyer-supplier contracting practices, rather than relying on individual firms alone.
CORE (COnnecting REpositories)
CORE (COnnecting REpositories)