Rate or Trade? Identifying Winning Ideas in Open Idea Sourcing
Information technology (IT) has created new patterns of digitally-mediated collaboration that allow open sourcing of ideas for new products and services. These novel sociotechnical arrangements afford finely-grained manipulation of how tasks can be represented and have changed the way organizations ideate. In this paper, we investigate differences in behavioral decision-making resulting from IT-based support of open idea evaluation. We report results from a randomized experiment of 120 participants comparing IT-based decision-making support using a rating scale (representing a judgment task) and a preference market (representing a choice task). We find that the rating scale-based task invokes significantly higher perceived ease of use than the preference market-based task and that perceived ease of use mediates the effect of the task representation treatment on the usersâ€™ decision quality. Furthermore, we find that the understandability of ideas being evaluated, which we assess through the ideasâ€™ readability, and the perception of the taskâ€™s variability moderate the strength of this mediation effect, which becomes stronger with increasing perceived task variability and decreasing understandability of the ideas. We contribute to the literature by explaining how perceptual differences of task representations for open idea evaluation affect the decision quality of users and translate into differences in mechanism accuracy. These results enhance our understanding of how crowdsourcing as a novel mode of value creation may effectively complement traditional work structures.