The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
When should workers embrace or resist new technology?
Abstract
The question of how workers might respond to new technologies has lurked behind many debates on the subject. It has not been posed directly, in part because of concerns about the determinism of asking about the effects of a technology. A preliminary is to set aside these concerns by showing that effects can be identified without determinism. The main argument is that technologies can be assessed on six dimensions: intended or unintended effects; direct and indirect effects; degree of reconstitution in use; immanence; degree of success and degree of discontinuity with the past. These dimensions can then be used to pose questions about any one technology. Three illustrations suggest how such questions can be posed in concrete conditions. Technologies can be challenged so that alternatives to extant systems of work organisation can be considered.
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“Those we have published to date have tended to make a big impact on our understanding of the relationship between technology, work and workers (see e.g., Edwards and Ramirez 2016; Howcroft and Taylor 2023).”
From Reflecting on 40 Years of New Technology, Work and Employment: Insights From the Current Editors on the Past and Prospects for the Future (2026) · cites this paper as Edwards and Ramirez 2016
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Cites
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Cited by
Coombs, C., Hislop, D., Taneva, S. K., & Barnard, S. (2020) · The Journal of Strategic Information Systems · doi:10.1016/j.jsis.2020.101600 · Cited by 301
Hodder, A., Valizade, D., Hardy, K., MacKenzie, R., & Smith, A. (2026) · New Technology, Work and Employment · doi:10.1111/ntwe.70054
Metadata
- Authors
- Edwards, P., & Ramirez, P.
- Venue
- New Technology, Work and Employment
- Publisher
- Wiley
- Published
- 2016-07
- Volume
- 31
- Issue
- 2
- Pages
- 99-113
- ISSN
- 0268-1072
- 1468-005X
- Cited by
- 90
- References
- 2
- Language
- en
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
