Generalized Reciprocity: Can Generosity Become Contagious?

点击翻译按钮获取中文摘要

Every day, millions of people donate blood, stop to help a stranded motorist, participate in unpaid surveys, review restaurants, leave online product ratings, answer questions on Ask.com, contribute code to open-source software, and edit Wikipedia articles, often anonymously, without social recognition or opportunity to benefit from direct reciprocation. This widespread willingness to help a stranger poses a fascinating theoretical puzzle with enormous practical implications. An important key to the puzzle may be the possibility that helping behavior can be contagious--people respond to being helped by "paying it forward" to a third person. Known as "generalized reciprocity," this behavior has the potential to trigger a chain of helping that reaches far beyond the original act. Generalized reciprocity bridges two largely disconnected existing literatures on social contagion and altruistic behavior. Integrating these two research traditions, this project identifies and tests four specific conditions expected to alter the probability that a recipient of help will pay it forward: group size, observation of generalized reciprocity by others, the number of others from whom help has been received, and the number of others who will benefit. Data will be collected from a large field experiment in an online labor market and validated with a small-group experiment run in a traditional laboratory setting. The results will advance theoretical knowledge about helping behavior and its diffusion, as well as new methodologies for online research, both within sociology and across multiple fields, including social psychology, behavioral economics, moral philosophy, computer science, communication, and information science.Broader ImpactThe potential ripple effect of generalized reciprocity means that when we help others, we may also be indirectly helping many -- both online and offline -- to mobilize voluntary contributions by more effectively targeting those who have benefited in the past. In addition, the project will have practical benefits for the scientific community by developing and demonstrating an innovative method for large online field experiments that can be adapted for a wide range of other studies of decision-making and diffusion.