Online reputation mechanisms Sample Clauses

Online reputation mechanisms eBay, Amazon Auctions and OnSale‌ eBay3, Amazon Auctions4 and OnSale Exchange5 are good examples of online marketplaces that use reputation mechanisms. eBay is one of the world’s largest online auction sites. Most items on eBay are sold through English auctions, where the auctioneer announces a reserve price and afterwards accepts increasingly higher bids. The bidder with the highest bid wins the item for the value of its bid. The reputation mechanism used is based on the ratings that users perform after the completion of a transaction. The user can give three possible values: positive(1), negative(-1) or neutral(0). The reputation value is computed as the sum of those ratings over the last six months. Similarly, Amazon Auctions and OnSale Exchange use also a mean (in this case of all ratings) to assign a reputation value. All these models consider reputation as a global property and use a single value that is not dependent on the context. The information source used to build the reputation value is the in- formation that comes from other agents that previously interacted with the target agent (witness information). They do not provide explicit mechanisms to deal with users that provide false in- formation. A great number of opinions that “dilute” false or biased information is the only way to increase the reliability of the reputation value. Dellarocas [72] points out that the commercial success of online electronic markets suggests the models have achieved their primary objective: ‘generate sufficient trust among buyers to persuade them to assume the risk of transacting with complete strangers’. Certainly these reputation mechanisms have contributed to the success of e-markets like eBay but what is not clear is to which extend. There are several studies that try to analyse the properties of these models specially based on eBay data sets (see again [72]).
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