Datafication of Knowledge Work: A Framework and Research Agenda
- Nico Wunderlich,
Research Output:
Journal Article or Conference Article in Journal
Conference article
Peer-reviewOpen access
Publication Information
Output type
Research Output:
Journal Article or Conference Article in Journal
Conference article
Peer-reviewOriginal language
EnglishPages from-to (Number of pages)
Pages 5769-5778 (10 pages)Journal (Volume, Issue Number)
Proceedings of the Annual Hawaii International Conference on System SciencesPublication milestones
- Published - 05/01/2021
Publication status
Published - 05/01/2021
ISSN
1060-3425Publication IDs
- Scopus: 85108314900
Abstract
Datafication is moving into the center of value creation in the knowledge intensive organization. Datafication describes the transformation of qualitative behavior and
tacit knowledge into quantified actions and codified data. While traditional assumptions on knowledge work highlights individual autonomy in shaping job tasks and fitting abilities for productive work, the consequences of datafication for knowledge work are not yet well understood. We build on the contingency theory of performance as theoretical lens to derive a framework that addresses relevant future research questions in the evolving field of datafication in knowledge work. The proposed multi-level framework considers assumptions and elements from traditional productive knowledge work in combination with determinants of digital workplaces and organizational factors along the lines of data-based value creation and (semi-)automated decision making. For the future, we suggest viewing datafied knowledge work as a socio-technical phenomenon, thereby constituted of human-dominated knowledge work in convergence with technological-dominated algorithmic thinking.
tacit knowledge into quantified actions and codified data. While traditional assumptions on knowledge work highlights individual autonomy in shaping job tasks and fitting abilities for productive work, the consequences of datafication for knowledge work are not yet well understood. We build on the contingency theory of performance as theoretical lens to derive a framework that addresses relevant future research questions in the evolving field of datafication in knowledge work. The proposed multi-level framework considers assumptions and elements from traditional productive knowledge work in combination with determinants of digital workplaces and organizational factors along the lines of data-based value creation and (semi-)automated decision making. For the future, we suggest viewing datafied knowledge work as a socio-technical phenomenon, thereby constituted of human-dominated knowledge work in convergence with technological-dominated algorithmic thinking.
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