When lone wolf defectors undermine the power of the opt-out default

Autor: Ruslan Shichman, Jonathan H. W. Tan, Eamonn Ferguson
Přispěvatelé: School of Social Sciences
Jazyk: angličtina
Rok vydání: 2020
Předmět:
Zdroj: Scientific Reports, Vol 10, Iss 1, Pp 1-12 (2020)
Scientific Reports
Popis: High levels of cooperation are a central feature of human society, and conditional cooperation has been proposed as one proximal mechanism to support this. The counterforce of free-riding can, however, undermine cooperation and as such a number of external mechanisms have been proposed to ameliorate the effects of free-riding. One such mechanism is setting cooperation as the default (i.e., an opt-out default). We posit, however, that in dynamic settings where people can observe and condition their actions on others’ behaviour, ‘lone wolf’ defectors undermine initial cooperation encouraged by an opt-out default, while ‘good shepherds’ defeat the free-riding encouraged by an opt-in default. Thus, we examine the dynamic emergence of conditional cooperation under different default settings. Specifically, we develop a game theoretical model to analyse cooperation under defaults for cooperation (opt-out) and defection (opt-in). The model predicts that the ‘lone wolf’ effect is stronger than the ‘good shepherd’ effect, which – if anticipated by players – should strategically deter free-riding under opt-out and cooperation under opt-in. Our experimental games confirm the existence of both ‘lone wolf’ defectors and ‘good shepherd’ cooperators, and that the ‘lone wolf’effect is stronger in the context of organ donation registration behaviour. We thus show a potential ‘dark side’ to conditional cooperation (‘lone wolf effect’) and draw implications for the adoption of an opt-out organ donation policy. Nanyang Technological University Published version Thanks to Callum Findlater and Pheobe Galbraith for helping with data collection for wave 1 and wave 2 of the experiment in the Supplementary files on perceptions of the defaults. Many thanks to Judd Kessler and Alvin Roth for the permission to use their z-Tree codes. We would like to acknowledge the advice and encouragement from Friedel Bolle, Yves Breitmoser, Jack Knetsch, Daniel Houser, Manfred Königstein, and participants to the seminar in Brigham Young University, the EBES Conference in Bali, and the Singapore Economic Review Conference in 2019. We are grateful to the Handling Editorial Board Member Valerio Capraro and three anonymous reviewers for the constructive comments and suggestions. The experiment was funded by a pump priming award from the School of Psychology, University of Nottingham to E.F. and J.T. and further funding via J.T. from Nottingham University Business School. The research received financial support from the Nanyang Technological University under J.T.’s Start-Up Grant. None of these institutions had any influence over the design, analysis, interpretation and writing of the paper.
Databáze: OpenAIRE