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α: calibrated so average coauthorship-adjusted count equals average raw count
The rapid growth of online retail in the last decade has led to widespread use of consumer-generated ratings. This paper theoretically and experimentally identifies influences that drive consumers to rate products and examines how those factors can create distortions in product ratings. By manipulating payoffs and effectively “deactivating” either the buyer or seller side of an artificial laboratory market, raters' behavior is decomposed into buyer-centric and seller-centric components. The cost of providing a rating also plays a major role in influencing rating behavior, with high and low quality sellers being rated more often than those of moderate quality.