An Empirical Investigation

Nonexpert peer-based knowledge refinement, it turns out, is just as helpful as expert-centric knowledge refinement for improving the quality of results. 83 Knowledge management (KM) repository-based systems (such as those involving " best practices " and " lessons learned " applications) are generally costly to operate since they require expert judgment to determine which knowledge submissions are to be included in the system and refined to make them as effica-cious as possible. Empirical evidence in cognitive psychology suggests that experts may not be needed for such refinement when the knowledge consumers are nonexperts. The knowledge " distance " between experts and nonexperts may indeed weaken expert-centric knowledge refinement. In addition , peer judgments delivered to nonexpert end users may substitute well for expert judgments. Multiple peer judgments, especially when provided through computer-supported knowledge-refinement systems, may be much less costly and just as good or perhaps even better than expert judgments , since peers are likely to think more like nonexpert users. A computer-support system is helpful for facilitating peer-based knowledge refinement, since more peers than experts are probably required for peer-based refinement