Abstract
Understanding what motivates and fosters collective actions has major implications in the governance and management of organizations, in the regulation and design of public policies, and has long attracted the interests of scholars and practitioners in business and economics. This paper deals with how groups of agents emerge in a dynamic contest characterized by lack of formal structure and uncertainty regarding the possible individual outcomes, focusing on the features of the cooperators and on the dynamics emerging among them. Through the development of a stylized agent-based model we start by showing how similarity in values can be a successful driver for cooperation but are also able to highlight the limits of such process, by looking at how and how much agents cooperate with similar others. A second-version of the model, where memory of past interactions has a role, introduces further dynamics and is able to create successful and relatively stable groups.
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Notes
Cruciani et al. (2013) showed how within this model the convergence of values is able to reduce the effect of potential within-group segregation that kicks in when, for instance, better information is available and agents more quickly learn about potential partnership (through experience). This links the present work and its possible extensions to the literature on social identity, which points out that if subjects have similar values but different endowments, the willingness to support the lower-endowed with the same identity (high similarity) is increased (Klor and Shayo 2010).
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Cruciani, C., Moretti, A. & Pellizzari, P. Dynamic patterns in similarity-based cooperation: an agent-based investigation. J Econ Interact Coord 12, 121–141 (2017). https://doi.org/10.1007/s11403-015-0155-7
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DOI: https://doi.org/10.1007/s11403-015-0155-7