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With prevalence of online shopping, consumer reliance on consumer generated reviews increased tremendously over the last 22 years. It was, an online retailer who started consumer generated review in 1995. It has since been a major success and source of consumer trust. However, over the years,, academics and the news media noticed an increase of fake reviews whose purpose is to motivate consumers into purchasing a product based on those fictitious reviews. has been on a spree to catch numerous fake reviewers and fake review providers while academic research focused on how to recognize fake reviews, distributions of reviews and differences between incentivized and verified reviews. Further, has also been concerned with biased reviews of consumers who write reviews of free or nearly free products in return for a review. No studies to date appear to be published analyzing the community of reviewers who write reviews “in return for an honest review”.

The current study attempts to fill the gap by analyzing the community of incentivized reviewers, typical behaviors, the rules and dynamics driving these communities. This paper relied on a netnography, to gain insights into incentivized Amazon reviewers’ community. Because a netnography is non-obtrusive, it permitted to observe participants in their “natural” environment. The study, conducted over the period of 1.5 years uncovered behaviors that contribute to j-distribution of reviews, questionable morality of reviewers and different behaviors during different times. Above all, the findings suggest manipulations to the system with an attempt to boost sales and the fact that most reviews are not fake but biased instead. Finally, while others can conduct a netnography on the reviewers community, this study is unique in that it analyzed the community mid the incentivized reviewing boom, followed by Amazon’s ban to incentivized reviewing to revival of reviewing activity post ban. That being said, given the changes to Amazon’s Terms of Service, this study documents changes future studies will not be able to uncover. The findings give insights into overconsumption driven by an opportunity to receive free product, introduction of review bias into the public domain and attempted manipulation to Amazon’s algorithms. While this study focuses specifically on Amazon, similar behaviors can be found in other reviewing cites. However, given the impact Amazon reviews have on consumer, this study caries potential to impact not only marketers but also consumers.

About the Authors

Dr. Ania Izabela Rynarzewska is an Assistant Professor in Sports Marketing and Analytics at Mercer University. She teaches consumer behavior, social media marketing, research methods and analytics courses in Stetson School of Business Economics.

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