Why did Brexit happen? Using causal mapping to analyse secondary, longitudinal data theory and methodology


The outcome of the UK's referendum on whether the UK should leave or remain in the European Union (so-called Brexit) came as a jolt to many across Europe. In this paper, we use causal mapping from soft OR to analyse longitudinal data from nine televised Brexit debates spread across the 4 weeks leading up to the referendum. We analyse these causal maps to build one view on why Brexit happened. The maps are analysed for the breadth, depth and consistency of arguments in the debate and, broadly, finds that the Leave campaign focused more consistently on a smaller set of campaign themes, contributed more detail to those themes, and focused on their own core issues rather than being diverted onto Remain strongholds. In contrast, Remain shared more information but across a broader range of themes (meaning they were less consistent), and followed Leave into themes that were clearly not their core battleground. The novelties for soft OR in this paper include: the difficulties of building and validating causal maps from secondary data; new techniques for analysing a group of causal maps to uncover the properties of arguments that spread longitudinally through a campaign; a methodology for a teaching case using publicly availability data; linking the paper, philosophically, to critical realism given the unique dataset. Finally, we identify differences in the Leave and Remain debate campaigns to offer one answer to the question ‘Why did Brexit happen?’.

Publication DOI: https://doi.org/10.1016/j.ejor.2017.05.051
Divisions: College of Business and Social Sciences > Aston Business School > Work & Organisational Psychology
College of Business and Social Sciences > Aston Business School
Additional Information: © 2017, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/
Uncontrolled Keywords: Brexit,soft OR,causal mapping,longitudinal analysis,secondary data,Modelling and Simulation,Management Science and Operations Research,Information Systems and Management
Publication ISSN: 1872-6860
Last Modified: 19 Apr 2024 07:13
Date Deposited: 02 May 2017 14:40
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Related URLs: http://www.scop ... tnerID=8YFLogxK (Scopus URL)
PURE Output Type: Article
Published Date: 2017-12-16
Published Online Date: 2017-06-01
Accepted Date: 2017-04-26
Submitted Date: 2016-11-18
Authors: Shaw, Duncan
Smith, Chris M.
Scully, Judy (ORCID Profile 0000-0002-0968-0941)

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