Abstract
Background: Warehouses are experiencing rapid technological transformations to enhance efficiency. Digital technologies and automation present both opportunities and challenges, redefining roles and requiring new skills. Understanding these trends and their effects on workforce dynamics is crucial for enabling workers to adapt.
Objectives: This study assesses the impact of digitalisation and automation on workforce dynamics in the warehousing industry, using bibliometric analysis and Latent Dirichlet Allocation (LDA) modelling to identify technological trends and workforce adaptations.
Method: A bibliometric analysis was performed on documents from Scopus, Web of Science, and Google Scholar. LDA modelling identified topics related to technological innovations and workforce dynamics. Findings were refined and validated through a survey and semi-structured interviews with industry experts.
Results: The research reveals trends such as IoT, AI, and robotics, driving workforce changes including reskilling in digital and technical skills and shifts in traditional roles. Key outcomes include increased productivity and efficiency, highlighting the need for continuous training and upskilling to align workforce strategies with technological advancements.
Conclusion: Automation enhances efficiency but necessitates workforce reskilling. Targeted training programmes are essential for enabling workers to thrive in automated environments.
Contribution: By focusing on South Africa, this study enhances understanding of digital transformation’s impact on workforce dynamics, not only in South Africa’s warehousing sector, but also more broadly in Africa and the Global South. This region is underrepresented in the prevailing academic debates. Furthermore, it introduces LDA as a novel methodological approach, yet not widely used in existing studies.