Business Power in Noisy Politics: An Exploration Based on Discourse Network Analysis and Survey Data

Open Access Journal | ISSN: 2183-2463

Article | Open Access

Business Power in Noisy Politics: An Exploration Based on Discourse Network Analysis and Survey Data


  • Adrian Rinscheid Institute for Economy and the Environment, University of St. Gallen, Switzerland


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Abstract:  This study links voter-centred and interest group perspectives to assess the role structurally powerful businesses can play in contested political issues. Revisiting the literature on business influence in politics, incumbent businesses are theorised to strategically use their structural power to influence voters’ preferences. The conceptual framework is illustrated with a case study of a direct democratic vote related to Swiss energy policy. To empirically trace the role incumbent businesses played in the run-up to the vote, the study employs a two-step approach. First, it uses Discourse Network Analysis (DNA) to examine arguments and actor coalitions in the public debate preceding the vote. Second, the DNA results inform a statistical analysis of survey data on voting behaviour. The findings suggest that incumbent businesses can use their structural power strategically to shape voting behaviour. The study stimulates the discussion about political power relationships in societies and enriches the nascent debate about phasing out unsustainable energy infrastructure. Importantly, it opens up ways to combine DNA with other methods, an avenue that shows promise for use and further refinement in future applications.

Keywords:  business; Discourse Network Analysis; direct democracy; energy; energy policy; nuclear power; phase-out; preference formation; structural power; Switzerland

Published:   2 June 2020


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DOI: https://doi.org/10.17645/pag.v8i2.2580


© Adrian Rinscheid. This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 license (http://creativecommons.org/licenses/by/4.0), which permits any use, distribution, and reproduction of the work without further permission provided the original author(s) and source are credited.