Reputation and uncertainty in online markets

One of the main problems which occurs in electronic markets is the information asymmetry between buyers and sellers. Buyers do not have the same information about the products as sellers do. The most important part of information advantage sellers have, has to do with the quality of the product. Sellers know the real quality, while buyers must rely on the description text provided by the seller. A well-known concept in the context of information asymmetry is moral hazard, which occurs when one party carries more risk than the other party. This happens in electronic markets when the buyer needs to complete the payment before the seller sends the product. In this way, the seller carries more risk. One of the most common types of internet fraud has to do with non-existing sellers or sellers who deliver unrepresented goods or even no goods at all. One way to overcome this information asymmetry is to build a relation with the other party. The problem is that for offline transactions this seems to be feasible, but for online transactions building a relationship seems to be harder. Therefore, the online reputation systems are introduced. In this way buyers can rate the behavior of the sellers, so that the more reliable sellers stand out against the unreliable sellers. Rating sellers may help other buyers in their decision process, so the online reputation system is a good example of consumer value creation.

In the article by Rice (2012) reputation and uncertainty in online markets are tested in a game setting. The game setting is as follows:

Game sequence

In this game setting there are two groups: buyers and sellers. Buyers have an amount of money which they ‘invest’ in the seller. The seller decides on how much of that investment he will return. Therefore the ‘investment’ can be seen as a price, and the ‘return’ can be seen as a delivered good. Initially the sellers announces how much he will return (e.g. quality of a good). Then, the buyer chooses how much he wants to invest in the seller (e.g. how much does the buyer wants to pay for the product). After that, the seller chooses how much of that money which was invested by the buyer he will return to the buyer (e.g. what quality will he deliver). Finally, the buyer has the opportunity to rate the seller. There is also an uncertainty factor included in the game setting. This provides the uncertainty that the returned amount can be intercepted by the researchers with a chance of 30%. The findings suggest that the occurrence of reputation systems stimulates people to take part in a transaction. Buyers who don’t meet expectations receive poorer ratings, while buyers who exceed expectations receive higher ratings. But when the buyers doubt whether the unmeet expectations are not caused by the seller, fewer poor ratings occur. This is related to the uncertainty factor. It seems that the higher the uncertainty factor, the more the buyers tend to trust the other party. Also, sellers’ positive ratings result in a higher investment of buyers. In some cases, a poor rating is weighted more heavily than a good rating.

I think the article highlights some very interesting aspects of online reputation systems, but I still have one question on my mind after reading this article. Nowadays, a lot of these online reputation systems are extended with visual text instead of just a scale rating. These text boxes mostly have much more details about the transaction experience with a specific seller and have therefore more value. I am wondering whether the findings of this article are also relevant in reputation systems with boxes of text, because these text-based reputation systems seemed to be more popular in the recent years. What do you think?


Sarah C. Rice, (2012) Reputation and Uncertainty in Online Markets: An Experimental Study. Information Systems Research. 23(2):436-452., retrieved 22 April, 2015, retrieved 22 April, 2015

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