Eliciting and integrating order picker preferences in the evaluation of job assignment mechanisms in warehousing

Abstract

Human operators remain essential for product retrieval in warehouses, also known as order picking. Due to its large share in warehousing costs, order picking often emerges at the centre of attention for efficiency improvements. While its physically demanding nature justifies the many efforts to reduce physical strain, an expanding number of studies call for increased attention to workers’ psychosocial well-being to cope with growing labour shortages. Accordingly, recent studies have questioned the traditional top-down job assignment paradigm to elevate order pickers’ job satisfaction by giving them the autonomy to choose their preferred task. Experimental trials demonstrated the potential of these participative systems to elevate job satisfaction, even with minimal attention paid to the determination of the choice alternatives. This paper adopts an Empirically Grounded Analytics approach to explore whether the positive impacts of a participatory system can be further improved by presenting more strategically determined choice alternatives to workers. We conduct a real-effort experiment (N = 165) to collect data on worker productivity and task utility, the latter defined as how much a worker appreciates a task. These empirical data are integrated into analytical models to assess various participatory system configurations. Numerical results show that participatory systems with productivity-oriented choice alternatives can reduce makespan by 8.4 %, while a focus on task utility can increase average task utility by 6.8 % compared to traditional top-down order assignment systems. The actual impact is thus contingent upon design choices. These results highlight the importance of intelligently determining choice alternatives to fully leverage the benefits of participatory systems.