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

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. Supplementary Information: The online version contains supplementary material available at 10.1007/s10551-022-05128-8.

Improving the measurement of prosociality through aggregation of game behavior.

Prior research has found that people's choices in economic games are often only modestly related to their prosocial personality traits and to mundane prosocial behaviors. The present article reviews the recent literature showing that the strength of these relationships depends on the level of aggregation. Specifically, we demonstrate an increase in behavioral consistency after horizontal aggregation (across multiple game types), vertical aggregation (across multiple game variants), and a combination thereof. Moreover, we show that aggregation increases the magnitude of the relationships of game behavior with prosocial personality and mundane prosocial behavior. These findings illustrate that economic games can genuinely capture a core facet of human prosociality - but that their capacity for doing so is greater when multiple game behaviors are considered.

Is Trust for Sale? The Effectiveness of Financial Compensation for Repairing Competence- versus Integrity-Based Trust Violations.

Despite the popularity of financial compensation as a means for addressing trust violations, the question whether (more) money can indeed buy trust back remains largely unexplored. In the present research, we focus on the role of violation type and compensation size. The results of a scenario study and a laboratory experiment show that financial compensation can effectively promote the restoration of trust for transgressions that indicate a lack of competence. Conversely, for transgressions which signal a lack of integrity, financial compensation is not an effective tool to repair trust. Moreover, our findings indicate that for both violation types, overcompensation has no positive effects on top of the impact of equal compensation. These findings therefore show that when it comes to trust, money cannot buy everything.

More Money, More Trust? Target and Observer Differences in the Effectiveness of Financial Overcompensation to Restore Trust.

Recent research revealed that despite its financial costs, overcompensation is not more effective to restore trust in the perpetrator than equal compensation. In a lab experiment (N = 115), we compared the effects of these compensation sizes for both targets of the compensation and non-involved observers. It was revealed that overcompensation did not yield superior outcomes than equal compensation. Specifically, for targets overcompensation resulted in lower levels of trust than equal compensation, while for observers equal compensation and overcompensation resulted in similar levels of trust. This finding suggests that overcompensation is not a cost-effective trust repair strategy, neither for the targets nor for third party observers. Other implications are discussed as well.