4.7 Article

WAx: An integrated conceptual framework for the analysis of cyber-socio-technical systems

期刊

SAFETY SCIENCE
卷 136, 期 -, 页码 -

出版社

ELSEVIER
DOI: 10.1016/j.ssci.2020.105142

关键词

Complex adaptive systems; Resilience engineering; Knowledge management; Conceptual model; Industry 4.0

资金

  1. H(CS)2I project - Italian National Institute for Insurance against Accidents at Work (INAIL)
  2. Institution of Occupational Safety and Health (IOSH) under the 2018 SAF(sic)RA EU funding scheme

向作者/读者索取更多资源

This paper explores the relationships between different social and technical actors in modern work domains, as well as their collaborative role in system functioning. It proposes a conceptual framework on knowledge creation and conversion within cyber-socio-technical systems, rooted in in-depth analysis of work practices and contexts.
Modern work domains are constituted by an intertwined set of social and technical actors with different, often conflicting, functional purposes. These agents act jointly to ensure system's functioning under both expected and unexpected working conditions. Considering the increasing digitalization and automation of work processes, socio-technical systems are progressively including interconnected cyber technical artefacts, thus becoming cyber-socio-technical systems (CSTSs). Adopting a natural science perspective, this paper aims to explore knowledge creation and knowledge conversion within CSTSs, as rooted in an in-depth analysis of work practices and work contexts. The paper proposes a conceptual framework which unveils the relationships between different work representations, i.e. relying on Work-As-Imagined, Work-As-Done, Work-As-Disclosed, Work-As-Observed, intended as knowledge entities generated by different agents, i.e. sharp-end operators, blunt-end operators, and analysts. The recursive and fractal nature of the proposed WAx (Work-As-x) framework ensures its adaptability for different granularity levels of analysis, fostering the understanding, modeling, and analysis of work practices, while abandoning reductionist and over-simplistic approaches.

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