We use a novel laboratory experiment involving a die rolling task embedded within a coordination game to investigate whether complicity can emerge when decision-making is simultaneous, the potential accomplices are strangers and neither communication nor signaling is possible. Then, by comparing the behavior observed in this original game to that in a variant in which die-roll reporting players are paired with passive players instead of other die-roll reporters, while everything else is held constant, we isolate the effect of having a potential accomplice on the likelihood of an individual acting immorally. We find that complicity can emerge between strangers in the absence of opportunities to communicate or signal and that having a potential accomplice increases the likelihood of an individual acting immorally.This network project brings together economists, psychologists, computer and complexity scientists from three leading centres for behavioural social science at Nottingham, Warwick and UEA. This group will lead a research programme with two broad objectives: to develop and test cross-disciplinary models of human behaviour and behaviour change; to draw out their implications for the formulation and evaluation of public policy. Foundational research will focus on three inter-related themes: understanding individual behaviour and behaviour change; understanding social and interactive behaviour; rethinking the foundations of policy analysis. The project will explore implications of the basic science for policy via a series of applied projects connecting naturally with the three themes. These will include: the determinants of consumer credit behaviour; the formation of social values; strategies for evaluation of policies affecting health and safety. The research will integrate theoretical perspectives from multiple disciplines and utilise a wide range of complementary methodologies including: theoretical modeling of individuals, groups and complex systems; conceptual analysis; lab and field experiments; analysis of large data sets. The Network will promote high quality cross-disciplinary research and serve as a policy forum for understanding behaviour and behaviour change.

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