Learning to be selfish? A large-scale longitudinal analysis of Dictator games played on Amazon Mechanical Turk

被引:8
作者
Arechar, Antonio A. [1 ,2 ,3 ]
Rand, David G. [3 ,4 ]
机构
[1] Ctr Res & Teaching Econ, CIDE, Aguascalientes, Aguascalientes, Mexico
[2] Univ Nottingham, Ctr Decis Res & Expt Econ, CeDEx, Nottingham, England
[3] MIT, Sloan Sch Management, Cambridge, MA 02139 USA
[4] MIT, Dept Brain & Cognit Sci, Cambridge, MA 02139 USA
关键词
Dictator game; Selection; Experience; Learning; Cooperation; Decision-making; Mturk; EXPERIENCE; BEHAVIOR;
D O I
10.1016/j.joep.2022.102490
中图分类号
F [经济];
学科分类号
02 ;
摘要
We investigate the role of experience playing the Dictator Game (DG) on allocations by aggregating data from 37 studies conducted on Amazon Mechanical Turk over a seven-year period. While prior evidence has shown a correlation between experience on Amazon Mechanical Turk and selfishness, it is unclear to what extent this is the result of selection versus learning. Examining a total of 27,266 decisions made by 17,791 unique individuals, our data shows evidence of significant negative effects of both selection and learning. First, people who participated in a greater total number of our studies were more selfish, even in their first game - indicating that people who are more likely to participate in our studies are more selfish. Second, a given individual tends to transfer less money over successive studies - indicating that experience with the DG leads to greater selfishness. These results provide clear evidence of learning even in this nonstrategic social setting.
引用
收藏
页数:6
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