Application of supportive and substitutive technologies in manual warehouse order picking: a content analysis
Eric H. Grosse
International Journal of Production Research, 2024, vol. 62, issue 3, 685-704
Abstract:
Order picking in warehouses is a labour- and time-intensive logistical process that significantly impacts the efficiency of supply chains. Although technical progress facilitates the automation of specific order picking tasks, human workers remain the primary actors of order picking. Owing to high operating costs associated with manual order picking, its design and management have been increasingly researched for decades. Because manual order picking systems are socio-technical systems, human factors and workers’ interaction with technology are essential for operational success. As innovative technologies become increasingly utilised, such as augmented reality or exoskeletons, warehouse managers need to consider the effects of supportive and substitutive technologies on operational outcomes. However, the potentials and obstacles of using technologies in manual order picking require further investigations. Therefore, this study analyses literature content on supportive and substitutive technologies in manual warehouse order picking and investigates the existing state of research in this field. Text mining is employed to enhance the insights regarding the content analysis. Additionally, future research opportunities on the integration of supportive and substitutive technologies are proposed for manual order picking improvement and development of sustainable and human-centered logistics systems, according to the Industry 5.0 vision.
Date: 2024
References: Add references at CitEc
Citations: View citations in EconPapers (2)
Downloads: (external link)
http://hdl.handle.net/10.1080/00207543.2023.2169383 (text/html)
Access to full text is restricted to subscribers.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:taf:tprsxx:v:62:y:2024:i:3:p:685-704
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/TPRS20
DOI: 10.1080/00207543.2023.2169383
Access Statistics for this article
International Journal of Production Research is currently edited by Professor A. Dolgui
More articles in International Journal of Production Research from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().