Abstract
Advanced technologies reshape operations at a staggering pace, with promises of lucrative improvements in a plethora of performance indicators, such as safety, speed, productivity, accuracy, and turnover. Companies that seek competitive advantage, however, often adopt new technologies without considering crucial human factors. Humans will remain an essential part of operations systems for the foreseeable future. As such we need to consider them when designing and implementing any advanced technology that affects their objective performance as well as their subjective experience. This dissertation includes three studies that deepen our understanding of human factors in terms of traditional and emerging leader-follower relationships, for the benefit of effectively designing and implementing advanced technologies within the field of operations management. Study 1 investigates a traditional hierarchical leader-follower relationship between a truck driver and his or her direct manager. It establishes the effect of safety-specific transformational leadership (SSTL) on the performance metrics of safe driving and driving productivity in long and short-haul truck cargo transport. Study 2 recognizes and investigates the novel leader-follower relationship that emerges during the interaction of humans with robots in collaborative order picking in warehouses. It empirically investigates this relationship and compares the objective performance outcomes of productivity and accuracy in two human-robot collaborative order picking setups (human leading the robot, human following the robot). Study 3 expands on the concept of human-robot collaborative order picking, and explores the effects that introducing this novel leader-follower relationship has on the subjective experience of human workers.
Original language | English |
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Award date | 2 Nov 2023 |
Place of Publication | Rotterdam |
Print ISBNs | 978-90-5892-673-9 |
Publication status | Published - 2 Nov 2023 |
Series
- ERIM PhD Series Research in Management