Integrative Solutions in Online Crowdsourcing Innovation Challenges

Abstract

Online crowdsourcing challenges are widely used for problem-solving and innovation. Existing theory has characterized such challenges as tools for tapping distant knowledge. By building on information processing theory we move beyond this characterization and present a perspective that describes innovation challenges as virtual places in which ideas are not simply submitted or commented upon but knowledge is integrated. This perspective shifts the role of crowdsourcing challenges from mere tools for gathering ideas to representing the locus of innovation. Our perspective suggests that three types of knowledge affect the quality of integrative solutions: elementary ideas, facts, and analogical examples. Based on a large dataset, we find that elementary ideas and analogical examples are related to increased solution quality, while facts are related to decreased solution quality. We expand the research on online crowdsourcing innovation challenges to include how crowd participants influence the quality of solutions through the content of their postings.