International Conference on Information Systems ( ICIS ) 2010 RATING SCALES FOR COLLECTIVE INTELLIGENCE IN INNOVATION COMMUNITIES : WHY QUICK AND EASY DECISION MAKING DOES NOT GET IT RIGHT
International Conference on Information Systems ( ICIS ) 2010 RATING SCALES FOR COLLECTIVE INTELLIGENCE IN INNOVATION COMMUNITIES : WHY QUICK AND EASY DECISION MAKING DOES NOT GET IT RIGHT
复制标题
DOI：
--
复制
发表时间：
2017
期刊：
影响因子：
--
通讯作者：
Christoph Riedl
中科院分区：
文献类型：
--
作者：
Christoph Riedl
开放式创新方法的日益普及导致了互联网上各种创新平台的兴起，这些平台可能包含10.000个用户生成的想法。然而，一个公司的吸收能力是有限的，容纳这么多的想法，所以有一个强烈的需要机制，以确定最好的想法。扩展以往的决策管理研究，我们集中分析有效的想法评级和选择机制，在网上创新社区和潜在的解释。我们的研究采用了多方法，包括一个基于网络的评级实验，313名参与者对来自现实世界创新社区的24个想法进行了评估，数据来自一项测量参与者评级满意度的调查，以及来自独立的xpert评审团的想法评级。我们的研究结果表明，尽管它在在线创新社区中的流行使用，但诸如竖起大拇指/向下评级或5-星星评级等简单的评级机制并不能产生有效的想法，并且被多属性量表显著优于。
The increasing popularity of open innovation approa ches has lead to the rise of various innovation platforms on the Internet which might co ntain 10.000s user-generated ideas. However, a company’s absorptive capacity is limited regardin g such an amount of ideas so that there is a strong need for mechanism to identify the best idea s. Extending previous decision management research we focus on analyzing effective idea ratin g and selection mechanisms in online innovation communities and underlying explanations. Using a multi-method approach our research comprises a web-based rating experiment wi th 313 participants evaluating 24 ideas from a real-world innovation community, data from a surv ey measuring rating satisfaction of participants, and idea ratings from an independent xpert jury. Our findings show that, despite its popular use in online innovation communities, simpl e rating mechanisms such as thumbs up/down rating or 5-star rating do not produce valid idea r nkings and are significantly outperformed by the multi-attribute scale.