When faced with a large number of reviews, customers can easily be overwhelmed by information overload. To address this problem, review systems have introduced design features aimed at improving the scanning, reading, and processing of online reviews. Though previous research has examined the effect of selected design features on information overload, a comprehensive and up-to-date overview of these features remains outstanding. We therefore develop and evaluate a taxonomy for information search and processing in online review systems. Based on a sample of 65 review systems, drawn from a variety of online platform environments, our taxonomy presents 50 distinct characteristics alongside the knowledge status quo of the features currently implemented. Our study enables both scholars and practitioners to better understand, compare and further analyze the (potential) effects that specific design features, and their combinations, have on information overload, and to use these features accordingly to improve online review systems for consumers.

当面对大量评论时，客户很容易因信息过载而不知所措。为了解决这个问题，评论系统引入了旨在改进在线评论的扫描、阅读和处理的设计功能。尽管之前的研究已经检验了所选设计特征对信息过载的影响，但对这些特征的全面且最新的概述仍然很突出。因此，我们开发和评估在线评论系统中信息搜索和处理的分类法。基于从各种在线平台环境中抽取的 65 个评论系统样本，我们的分类法呈现了 50 个不同的特征以及当前实施的功能的知识现状。我们的研究使学者和实践者能够更好地理解，