"A human-centric perspective exploring the readiness towards smart warehousing: The case of a large retail distribution warehouse"

by Mahroof, Kamran (2019)

Abstract

The explosive rise in technologies has revolutionised the way in which business operate, consumers buy, and the pace at which these activities take place. These advancements continue to have profound impact on business processes across the entire organisation. As such, Logistics and Supply Chain Management (LSCM) are also leveraging benefits from digitisation, allowing organisations to increase efficiency and productivity, whilst also providing greater transparency and accuracy in the movement of goods. While the warehouse is a key component within LSCM, warehousing research remains an understudied area within overall supply chain research, accounting for only a fraction of the overall research within this field. However, of the extant warehouse research, attention has largely been placed on warehouse design, performance and technology use, yet overlooking the determinants of Artificial Intelligence (AI) adoption within warehouses. Accordingly, through proposing an extension of the Technology–Organisation–Environment (TOE) framework, this research explores the barriers and opportunities of AI within the warehouse of a major retailer. The findings for this qualitative study reveal AI challenges resulting from a shortage of both skill and mind-set of operational management, while also uncovering the opportunities presented through existing IT infrastructure and pre-existing AI exposure of management.

Keywords

Artificial Intelligence, Logistics, Warehousing, Technology Readiness, Worker Replacement

Themes

Future of Work, Employment, AI and Computerisation, Automation

Links to Reference

• http://www.sciencedirect.com/science/article/pii/S0268401218306972
• http://dx.doi.org/10.1016/j.ijinfomgt.2018.11.008
• https://www.sciencedirect.com/science/article/pii/S0268401218306972?casa_token=U3BSy3-iUucAAAAA:OvdhnxW_EbHJ5IfQ5Z8AtsENSLVFbbzsoFODTi6QF6Dwk7aZonMP7HxCbR3B424CSNkxLamfOg

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