The emergence of conventions in the repeated volunteer's dilemma: The role of social value orientation, payoff asymmetries and focal points.

Conventions are arbitrary rules of behavior that coordinate social interactions. Here we study the effects of individuals' social value orientations (SVO) and situational conditions on the emergence of conventions in the three-person volunteer's dilemma (VOD). The VOD is a step-level collective good game in which only one actor's action is required to produce a benefit for the group. It has been shown that if actors interact in the payoff-symmetric VOD repeatedly, a turn-taking convention emerges, resulting in an equal distribution of payoffs. If the VOD is asymmetric, with one "strong" actor having lower costs of volunteering, a solitary-volunteering convention emerges by which the strong actor volunteers earning less than others. In study 1 we test whether SVO promotes turn-taking and hampers solitary-volunteering. We find that groups with more prosocials engage less in turn-taking and no effect of SVO on the emergence of solitary-volunteering. In study 2 we test whether making one actor focal is sufficient for solitary-volunteering to emerge. We find instead that payoff asymmetry with one strong actor is a necessary precondition. We discuss explanations for our findings and propose directions for future research.

Modeling the micro-macro link: Understanding macro-level outcomes using randomization tests on micro-level data.

Analytical sociology explains macro-level outcomes by referring to micro-level behaviors, and its hypotheses thus take macro-level entities (e.g. groups) as their units of analysis. The statistical analysis of these macro-level units is problematic, since macro units are often few in number, leading to low statistical power. Additionally, micro-level processes take place within macro units, but tests on macro-level units cannot adequately deal with these processes. Consequently, much analytical sociology focuses on testing micro-level predictions. We propose a better alternative; a method to test macro hypotheses on micro data, using randomization tests. The advantages of our method are (i) increased statistical power, (ii) possibilities to control for micro covariates, and (iii) the possibility to test macro hypotheses without macro units. We provide a heuristic description of our method and illustrate it with data from a published study. Data and R-scripts for this paper are available in the Open Science Framework (https://osf.io/scfx3/).