ArticleNew technology, work and employment2022
COVID-19, economic crises and digitalisation: How algorithmic management became an alternative to automation.
Article in New technology, work and employment, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed.
- Bourdieu's capitals matter: tracking longer working lives across Europe.European journal of ageing · 2026Article
- Platform workers and digital agency: Making out on three types of labor platforms.Frontiers in sociology · 2023Article
- COVID-19, economic crises and digitalisation: How algorithmic management became an alternative to automation.New technology, work and employment · 2022Article
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1 author.
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Abstract
The COVID-19 crisis witnessed a major rise in investment in software for the digital organisation and rationalisation of work, while investment in robotics is continuously lagging behind expectations. This article argues that we can understand this development as the continuation of the rise of algorithmic management as a technological fix for profitability crises. Thus, in the face of falling wage rates and a structural overaccumulation of capital since the 1970s, algorithmic management has become an alternative to automation. The article reconstructs the history of algorithmic management in connection to economic crises. This allows for periodisation of the rise of algorithmic management from 'computer-integrated manufacturing' to remote work in four waves. In times of crisis, algorithmic management functions as a substitute for investment in 'tangible capital' such as robots. Structural economic forces thus interact with labour conflicts at the company level, shaping the rise of algorithmic management.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.