Abstract
Contemporary digital ecosystems produce vast amounts of data every day. The data are often no more than microscopic log entries generated by the elements of an information infrastructure or system. Although such records may represent a variety of things outside the system, their powers go beyond the capacity to carry semantic content. In this article, we harness critical realism to explain how such data come to matter in specific business operations. We analyse the production of an advertising audience from data tokens extracted from a telecommunications network. The research is based on an intensive case study of a mobile network operator that tries to turn its subscribers into an advertising audience. We identify three mechanisms that shape data-based production and three properties that characterize the underlying pool of data. The findings advance the understanding of many organizational settings that are centred on data processing.
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Notes
By metatheory we refer to reasoning behind empirical research designs; a framework that provides the rationale and practical guidance on how the different aspects of research are brought together into a coherent argument. The term is largely synonymous with theoretical perspective (Crotty, 1998), yet ‘metatheory’ communicates explicitly the idea of theory about research and distinguishes it, in our case, from substantive theorizing of technology in particular settings.
A mobile virtual network operator (MVNO) is a telecommunications operator that does not own a physical network infrastructure but leases it from another operator.
We are not allowed to reproduce an actual CDR from the research site.
Advenage SMS Gateway Router 1.0 documentation.
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Acknowledgements
The authors would like to thank Jannis Kallinikos and Carsten Sørensen for their support and feedback. We are also grateful to the anonymous reviewers for their constructive and helpful feedback throughout the process.
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Aaltonen, A., Tempini, N. Everything counts in large amounts: a critical realist case study on data-based production. J Inf Technol 29, 97–110 (2014). https://doi.org/10.1057/jit.2013.29
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DOI: https://doi.org/10.1057/jit.2013.29