We analyse pricing, effort and tipping decisions in the online service Google Answers. While users set a price for the answer to their question ex ante, they can additionally give a tip to the researcher ex post. In line with the related experimental literature we find evidence that tipping is motivated by reciprocity, but also by reputation concerns among frequent users. Moreover, researchers seem to adjust their eþort based on the user.s previous tipping behaviour. An efficient sorting takes place when enough tip history is available. Users known for tipping in the past receive higher effort answers, while users with an established reputation for non-tipping tend to get low effort answers. In addition, we analyse how tipping is adopted when the behavioural default is not to tip and estimate minimum levels for the fraction of genuine reciprocator and imitator types.
social preferences reciprocity moral hazard reputation Internet psychological game theory