Abstract
This paper investigates online feedback systems and their perceived diagnosticity in the book industry, using a mixed methods approach, with data retrieved from Amazon. Several variables concur to give the overall perceived diagnosticity of customer reviews: score systems, written text and its themes, and reviews date. Even though reviews are positively biased, long negative reviews are perceived as the most diagnostic. The older the review, the higher the perceived diagnosticity, due to the combined effects of early bird bias and winner circle bias. By understanding the role that variables have on diagnosticity, the findings can be used by scholars, as well as by e-commerce and marketplace webmasters who seek ways to improve the feedback systems of the online platforms in or outside the book industry.
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