The behavioral effects of content rating information on knowledge system content use

Knowledge management system content reuse is critical to leveraging the intellectual capital within a firm, especially when high quality content is reused. While following the recommendations of others (i.e. ratings) as to what is high quality content can be a good strategy, it is possible that these recommendations are intentionally or unintentionally biased, leading to poor recommendations and inappropriate reuse of content. To address this, knowledge systems offer indicators of credibility in content ratings and content recommendations to better direct knowledge workers to high quality content. Individual psychology theory suggests inaccurate ratings may trigger individuals to use credibility indicators and content recommendations. In this study two different credibility indicators---sample size and source expertise---and one content recommendation characteristic---filter sophistication---are examined to see if individuals can use this information to overcome inaccurate content ratings. Four laboratory experiments provide evidence that ratings have a strong influence on content usage decisions regardless of rating accuracy and the moderating effect of source expertise matters while the effect of sample size as indicators of rating credibility and filter sophistication in content recommendations does not.