Abstract
Successful idea generation, selection and management are crucial in the early stages of any innovation process. The use of crowdsourcing during this phase can be beneficial and can lead to product ideas and solutions that are novel, show customer benefit and are likely to be more successful in the market
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than products based on the ideas generated by professionals. However, the underlying mechanisms of innovation crowdsourcing are not yet properly understood and there are open questions regarding the ideation and knowledge production capacities that can be gained using crowdsourcing. In three empirical studies this thesis advances our understanding of crowdsourced idea generation and knowledge production. It sheds light on different characteristics of successful innovation crowdsourcing by focussing on the characteristics of implemented ideas, the online behaviour of successful ideators and on the development of ideas through the crowd’s comments. The insights gained in these studies, as well as through the fast-growing number of empirical research papers that address the different underlying mechanisms of innovation crowdsourcing, clearly show the need for an analytical framework defining the different areas of knowledge production within the innovation crowdsourcing space. The framework developed in this thesis allows us to synthesise the different empirical findings in a meaningful way and to spell out how new ideas and solutions can successfully be sourced from the crowd. As innovation crowdsourcing attempts can differ substantially in their cognitive and social dimensions of knowledge production, four different areas of knowledge production within the innovation crowdsourcing space are defined depending on the level of uncertainty of the innovation task assigned to the crowd and on the mutual dependency among the crowd to produce the ideas or solutions needed. The results of an integrated literature review show that the mechanisms that are important in making crowdsourcing work differ depending on the area of knowledge production. Consequently, there is no single approach or strategy that will be equally useful for all innovation crowdsourcing attempts. Instead, the ways in which the task is formulated and presented to the crowd, the incentives offered to the crowd and the ways in which the idea- or knowledge-seeking organisation interacts with the crowd will have to differ depending on the area of knowledge production within the innovation crowdsourcing space.
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