A systems thinking framework of human–machine interactions and their impact on warehouse operations

The emergence of warehouse automation has caused debate about the impact on human labour, highlighting the need to understand human–machine interactions in warehouse operations to assess the overall efficiency and facilitate developing appropriate intervention strategies. Many studies in the past looked at human–machine interactions in isolation e.g. in order-picking areas of warehouses ignoring the other substantial activities. This study moves away from the isolated approach and develops a comprehensive view of the system structure by using qualitative system dynamic through Causal Loop Diagrams. This research follows a Delphi-style approach and held three rounds of consultations with experts. The model developed provides new insights between human factors and warehouse operations which can be used to develop intervention strategies, recognising the level of collaboration between humans and machines, enhancing productivity, improving knowledge and promoting well-being of workers. The outcomes of this research could assist the design of future-focused Industry 4.0 warehouse operations.