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Online reviews are well-known for their ability to reduce information asymmetry between sellers and buyers. However, when faced with a large number of reviews, customers can be overwhelmed by information overload. To address this problem, review systems have introduced design features intended to improve the scanning, reading and processing of online reviews. Yet, to date, we lack a comprehensive overview of these design features. Our research aims to fill this gap by consolidating the state of the art of online review system design features and develop a taxonomy for ‘information search and processing in online review systems’. To this end, we implement a rigorous taxonomy development process, and evaluate the resulting taxonomy by providing evidence of its completeness and usefulness. We contribute to literature and practice by introducing a new taxonomy which provides a first overview of design features of online review systems.



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