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Most online market exchanges are governed by reputation systems, which allow traders to comment on one another's behavior and attributes with ratings and text messages. These ratings then constitute sellers' reputations that serve as signals of their trustworthiness and competence. The large body of research investigating the effect of reputation on selling performance has produced mixed results, and there is a lack of consensus on whether the reputation effect exists and what it means. After showing how the reputation effect can be derived from a game-theoretic model, we use meta-analysis to synthesize evidence from 107 studies investigating the reputation effect in peer-to-peer online markets. Our results corroborate the existence of the reputation effect across different operationalizations of seller reputation and selling performance. Our results also show the extent to which the reputation effect varies. We discuss potential explanations for the variation in reputation effects that cannot be attributed to sampling error and thereby point out promising avenues for future research.

The published Stata syntax files (do-files) and data can be used to replicate the results reported in the cited article.

Abstract of the journal article:
In 25 years, research on reputation-based online markets has produced robust evidence on the existence of the so-called reputation effect, i.e. the positive relation between online traders' reputations and these traders' market success in terms of sales and prices. However, there is an ongoing debate on what the size of the reputation effect means. We argue that the rate of truthful feedback that traders leave after completed transactions is negatively related to the size of the reputation effect. The higher the rate of truthful feedback, the quicker will untrustworthy traders be screened and disincentivized to enter the market. With mostly trustworthy traders entering the market, buyers will demand smaller price discounts from market entrants without a good reputation. We test this mechanism empirically in two laboratory experiments. In both experiments, we systematically vary the probability with which information about sellers' behavior in an economic trust game is recorded and shown to future interaction partners of these sellers. In the second experiment, we introduce competition among sellers by allowing buyers to choose one of two sellers in each interaction. We find that sellers give discounts to buyers to build or repair their reputation and that sellers who give discounts or have a good reputation are trusted more. However, we do not find support for our hypothesis that a higher feedback rate significantly decreases sellers' propensity to give discounts. We argue and show in exploratory analyses that this is likely due to the high level of unconditional trust buyers exhibit towards sellers without a reputation. Yet, seller competition increases the propensity to offer discounts among sellers without a reputation the most.