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Digital Transformation of Retail Work: The Rise of Chaotic Rationalisation

Chris Tilly & Françoise Carré

British Journal of Industrial Relations2026https://doi.org/10.1111/bjir.70051article
AJG 4ABDC A*
Weight
0.50

Abstract

We examine how new digital technologies are transforming labour processes in frontline jobs in United States (US) store‐based retail, examining the US as an extreme case of labour market liberalisation. Research on technological change presents three scenarios: job displacement, job enrichment and ‘digital Taylorism’ involving heightened surveillance and control. However, this research typically overlooks the role of customers and the frequency of technology failure. Drawing on interviews with frontline employees and managers supplemented by other sources, we find little evidence for job enhancement and limited evidence of job displacement. Retailers have used digital technologies to heighten Taylorisation, speedup and surveillance in some frontline jobs. However, interviews reveal multiple sources of chaos in the jobs, including unpredictable customer interactions, staffing patterns that make it hard for retail workers to rely on co‐workers, and flaws in digital technologies themselves. We summarise the current impact of digital technology adoption on US store‐based retail work as ‘chaotic rationalisation’—retail employers aim to use technology to rationalise work, but the result diverges from Taylorism because of chaotic elements in retail workplaces.

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https://doi.org/https://doi.org/10.1111/bjir.70051

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@article{chris2026,
  title        = {{Digital Transformation of Retail Work: The Rise of Chaotic Rationalisation}},
  author       = {Chris Tilly & Françoise Carré},
  journal      = {British Journal of Industrial Relations},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1111/bjir.70051},
}

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.