In control or under control? Human–robot collaboration in warehouse order picking

Purpose Warehouse operations are rapidly becoming more robotized to increase performance and reduce costs. A key innovation in the field is human–robot collaboration (HRC). Despite the essential role of human behavior in operational performance, human factors in HRC are still understudied in Operations Management literature. To address this gap, we conducted a unique real-effort experiment in a warehouse especially erected for this study and ground our analysis in Self-Determination Theory, Leader-Member Exchange Theory and Regulatory Focus Theory. Design/methodology/approach The experiment compares the objective outcomes of collaborative productivity, collaborative accuracy and human pick time between a configuration with the human leading the robot and a configuration with the human following the robot. Additionally, we investigate the behavioral mechanism governing human reactions to the novel collaboration with robots. Findings We find that human leading allows for superior collaborative order picking productivity, while human following allows for greater collaborative order picking accuracy. Especially when picking involves traveling between locations, human leading results in shorter pick times. We additionally establish a prevention focus as the factor that allows workers to bridge the productivity gap between the two setups. Research limitations/implications A limitation of the lab experiment is its short duration, which necessitates follow-up research in field experiments. Originality/value These insights will help warehousing service providers to tailor collaborative robotic solutions based on quantifiable trade-offs between system speed and accuracy.

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Publication Details

Journal
Logistics Research
Published
2026-02-23
DOI
https://doi.org/10.1108/lore-03-2025-0028
Primary Topic
Advanced Manufacturing and Logistics Optimization
Type
article
Field-Weighted Citation Impact
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article

In control or under control? Human–robot collaboration in warehouse order picking

J. de Vries, Alexandros Pasparakis, René De Koster
Logistics Research
Advanced Manufacturing and Logistics Optimization
article

In control or under control? Human–robot collaboration in warehouse order picking

J. de Vries, Alexandros Pasparakis, René De Koster
article en

Abstract

Purpose Warehouse operations are rapidly becoming more robotized to increase performance and reduce costs. A key innovation in the field is human–robot collaboration (HRC). Despite the essential role of human behavior in operational performance, human factors in HRC are still understudied in Operations Management literature. To address this gap, we conducted a unique real-effort experiment in a warehouse especially erected for this study and ground our analysis in Self-Determination Theory, Leader-Member Exchange Theory and Regulatory Focus Theory. Design/methodology/approach The experiment compares the objective outcomes of collaborative productivity, collaborative accuracy and human pick time between a configuration with the human leading the robot and a configuration with the human following the robot. Additionally, we investigate the behavioral mechanism governing human reactions to the novel collaboration with robots. Findings We find that human leading allows for superior collaborative order picking productivity, while human following allows for greater collaborative order picking accuracy. Especially when picking involves traveling between locations, human leading results in shorter pick times. We additionally establish a prevention focus as the factor that allows workers to bridge the productivity gap between the two setups. Research limitations/implications A limitation of the lab experiment is its short duration, which necessitates follow-up research in field experiments. Originality/value These insights will help warehousing service providers to tailor collaborative robotic solutions based on quantifiable trade-offs between system speed and accuracy.

Logistics Research
Tilburg University (NL), Erasmus University Rotterdam (NL)
Industry, innovation and infrastructure
Openalex Percentile: Top 49%
Advanced Manufacturing and Logistics Optimization
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