Leader-follower relationships in technologically advanced operations

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

Leader-follower relationships in technologically advanced operations

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

Assessing the impact of human–robot collaborative order picking systems on warehouse workers

Robotisation is increasing in warehouse operations, but human employment continues to be relevant. Traditionally manual activities, such as order picking, are being re-designed into collaborative human–robot tasks. This trend exemplifies the transition towards a human-centric Industry 5.0, focusing on synergy instead of seeking human replacement. However, human workers are increasingly hard to recruit and retain. We contribute to the underrepresented literature on human factors within the domain of operations and production management research and investigate the deployment of robotic technologies alongside human workers in a sustainable way. With a unique real-effort experiment, we investigate how the manipulation of picker’s experienced levels of autonomy affects their job satisfaction and core self-evaluations, two key behavioural outcomes that determine employee turnover intentions. We establish that the introduction of human–robot collaboration positively affects job satisfaction for the contrasting collaboration dynamics of (i) gaining control (the human leading the robot) and (ii) ceding control (the human following the robot). This positive effect is larger when the human is following the robot. We additionally find that following the robot positively affects pickers’ self-esteem and that self-efficacy related to human–robot interaction benefits from the introduction of collaborative robotics, regardless of the setup dynamics

In the driver’s seat:the role of transformational leadership in safe and productive truck cargo transport

This study investigates the effect of safety-specific transformational leadership (SSTL) on the performance outcomes of safe driving and driving productivity in both long and short-haul truck cargo transport. We conduct our study in the context of a hazardous material (HAZMAT) Indian transport company using a sample of 1,196 trips across 104 unique routes, and driven by 71 truck drivers over a 30-month span. We establish that SSTL is beneficial for truck driving productivity as it positively influences driving productivity in long-haul trips. There is no conclusive evidence of a negative effect on the productivity in short-haul trips. Furthermore, our results show that more experienced drivers are also more likely to indulge in risky driving behavior. Our findings have immediate practical applications for transport companies that wish to promote operational safety, while safeguarding and even improving operational productivity

In the driver’s seat:the role of transformational leadership in safe and productive truck cargo transport

This study investigates the effect of safety-specific transformational leadership (SSTL) on the performance outcomes of safe driving and driving productivity in both long and short-haul truck cargo transport. We conduct our study in the context of a hazardous material (HAZMAT) Indian transport company using a sample of 1,196 trips across 104 unique routes, and driven by 71 truck drivers over a 30-month span. We establish that SSTL is beneficial for truck driving productivity as it positively influences driving productivity in long-haul trips. There is no conclusive evidence of a negative effect on the productivity in short-haul trips. Furthermore, our results show that more experienced drivers are also more likely to indulge in risky driving behavior. Our findings have immediate practical applications for transport companies that wish to promote operational safety, while safeguarding and even improving operational productivity