Qiao, DandanLee, Shun-YangWhinston, AndrewWei, Qiang2016-12-292016-12-292017-01-04978-0-9981331-0-2http://hdl.handle.net/10125/41838Individuals’ pro-social behaviors are driven by altruistic and selfish motivations. In this paper we explore how the introduction of external incentives would influence one’s pro-social behavior both in the short term and in the long run. Using a large data set on Amazon product reviews, we design a quasi-experimental approach where we combine a propensity score matching (PSM) and a difference-in-differences (DiD) method to empirically study the effect of incentive provision on reviewer’s behavior. We apply techniques from linguistics, language processing, and machine learning to propose several novel measures to capture reviews’ writing style and quality. We find evidences consistent with crowding-out and overjustification effects. Our study contributes to the understanding of pro-social behavior and sheds light on how incentives would shift individual behavior.10 pagesengAttribution-NonCommercial-NoDerivatives 4.0 InternationalAltruismCrowding-out effectIncentiveOverjustification effectPro-social behaviorConference Paper10.24251/HICSS.2017.675