RATING SCALES FOR COLLECTIVE INTELLIGENCE IN INNOVATION COMMUNITIES:WHY QUICK AND EASY DECISION MAKING DOES NOT GET IT RIGHT

摘要: The increasing popularity of open innovation approa ches has lead to the rise various platforms on Internet which might co ntain 10.000s user-generated ideas. However, a company’s absorptive capacity is limited regardin g such an amount ideas so that there strong need for mechanism identify best idea s. Extending previous decision management research we focus analyzing effective ratin and selection mechanisms in online communities underlying explanations. Using multi-method approach our comprises web-based rating experiment wi th 313 participants evaluating 24 from real-world community, data surv ey measuring satisfaction participants, ratings independent expert jury. Our findings show that, despite its popular use communities, simpl e as thumbs up/down or 5-star do not produce valid r ankings are significantly outperformed by multi-attribute scale.