Divergent Innovation: Directing the Wisdom of Crowd to Tackle Societal Challenges

Crowdsourcing is acknowledged as a promising avenue for addressing societal challenges by drawing on the wisdom of the crowd to offer diverse solutions to complex problems. Advancing a new conceptual framework of ‘divergent innovation’ which delineates between topic and quality divergence as focal metrics of performance when crowdsourcing for solutions to societal challenges, this study investigates the impacts of four ideation stimuli on divergent innovation. These four stimuli include task description concreteness, resource richness, topic entropy, and judging criteria comprehensiveness. Empirical analysis based on data sourced from an online crowd-ideation platform reveals that task description concreteness negatively affects topic divergence but positively influences quality divergence, whereas resource richness positively affects topic divergence but negatively influences quality divergence. Additionally, the relationship between topic entropy and topic divergence is U-shaped, with no significant impact on quality divergence. These findings contribute to extant literature on crowdsourcing and offer invaluable insights for practitioners.