A new web personalization decision-support artifact for utility-sensitive customer review analysis

摘要

In recent years there has been increased consumer use of the vast array of online reviews. Given the increasingly high volume of such reviews, automatic analyses of their quality have become imperative. Not surprisingly, this situation has attracted the interest of researchers. However, prior approaches are insufficient to address the consumers' need for non-burdensome sense making of online reviews. This research attempts to close this gap by proposing novel design science artifacts (i.e. construct, architecture, algorithms and prototype) to address the consumers' need. We evaluate these artifacts using a set of experiments and hypothesis tests. The results validate the effectiveness and efficiency of the proposed artifacts. We demonstrate their practical utility and relevance using real world pilot experiments. This paper contributes theoretical knowledge to the review quality literature and, what we believe is the first exemplifier for adequately validating the solutions of review quality research. (C) 2016 Elsevier B.V. All rights reserved.