A Network Approach to Compliance: A Complexity Science Understanding of How Rules Shape Behavior

Malouke Esra Kuiper (), Monique Chambon (), Anne Leonore Bruijn (), Chris Reinders Folmer (), Elke Hindina Olthuis (), Megan Brownlee (), Emmeke Barbara Kooistra (), Adam Fine (), Frenk Harreveld (), Gabriela Lunansky () and Benjamin Rooij ()
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Malouke Esra Kuiper: University of Amsterdam
Monique Chambon: University of Amsterdam
Anne Leonore Bruijn: University of Amsterdam
Chris Reinders Folmer: University of Amsterdam
Elke Hindina Olthuis: University of Amsterdam
Megan Brownlee: University of Amsterdam
Emmeke Barbara Kooistra: University of Amsterdam
Adam Fine: Arizona State University
Frenk Harreveld: University of Amsterdam
Gabriela Lunansky: University of Amsterdam
Benjamin Rooij: University of Amsterdam

Journal of Business Ethics, 2023, vol. 184, issue 2, No 9, 479-504

Abstract: Abstract To understand how compliance develops both in everyday and corporate environments, it is crucial to understand how different mechanisms work together to shape individuals’ (non)compliant behavior. Existing compliance studies typically focus on a subset of theories (i.e., rational choice theories, social theories, legitimacy theories, capacity theories, and opportunity theories) to understand how key variables from one or several of these theories shape individual compliance. The present study provides a first integrated understanding of compliance, rooted in complexity science, in which key elements from these theories are considered simultaneously, and their relations to compliance and each other are explored using network analysis. This approach is developed by analyzing online survey data (N = 562) about compliance with COVID-19 mitigation measures. Traditional regression analysis shows that elements from nearly all major compliance theories (except for social theories) are associated with compliance. The network analysis revealed groupings and interconnections of variables that did not track the existing compliance theories and point to a complexity overlooked in existing compliance research. These findings demonstrate a fundamentally different perspective on compliance, which moves away from traditional narrow, non-network approaches. Instead, they showcase a complexity science understanding of compliance, in which compliance is understood as a network of interacting variables derived from different theories that interact with compliance. This points to a new research agenda that is oriented on mapping compliance networks, and testing and modelling how regulatory and management interventions interact with each other and compliance within such networks.

Keywords: Network analysis; Compliance; Complexity science (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s10551-022-05128-8

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