Competition and moral behavior: A meta-analysis of forty-five crowd-sourced experimental designs.

This is the final version. Available from PNAS via the DOI in this record. ; Data, Materials, and Software Availability. The data and analysis code are available at the project’s OSF repository (osf.io/r6anc). The mean and standard error resulting from each experimental design for the different analytical approaches and the peer rating for each experimental design are tabulated in SI Appendix, Tables S1–S4. The PAP of the overall project, the preregistration of each experimental design, the materials submitted by RTs to collect data for each experimental design, and the individual level data for each experimental design are available at the project’s OSF repository (osf.io/r6anc). Anonymized pre-analysis plan, experimental design proposals, materials, data and codes data have been deposited in OSF Open Science Framework osf.io/r6anc. ; Does competition affect moral behavior? This fundamental question has been debated among leading scholars for centuries, and more recently, it has been tested in experimental studies yielding a body of rather inconclusive empirical evidence. A potential source of ambivalent empirical results on the same hypothesis is design heterogeneity-variation in true effect sizes across various reasonable experimental research protocols. To provide further evidence on whether competition affects moral behavior and to examine whether the generalizability of a single experimental study is jeopardized by design heterogeneity, we invited independent research teams to contribute experimental designs to a crowd-sourced project. In a large-scale online data collection, 18,123 experimental participants were randomly allocated to 45 randomly selected experimental designs out of 95 submitted designs. We find a small adverse effect of competition on moral behavior in a meta-analysis of the pooled data. The crowd-sourced design of our study allows for a clean identification and estimation of the variation in effect sizes above and beyond what could be expected due to sampling variance. We find ...