What Drives the Crowd? A study of user motivations on web-based innovation platforms

Detta är en Master-uppsats från Göteborgs universitet/Graduate School

Sammanfattning: Crowdsourcing has during the last decade gone from an obscure phenomenon to a widely accepted way to improve business processes. As companies struggle to implement crowdsourcing in their operations, purpose-specific online platforms are being launched worldwide, providing companies with access to the crowd through a third party. The study was performed in collaboration with Realize; a company that provides consultancy services in the areas of business development, ideation, innovation, i.a., interested in the aspects associated with developing and launching a web-based innovation platform (WBIP). Thus, the aim of the study is to provide insight in the motivational drivers and factors that drive user participation and contribution in a WBIP environment. This was approached through interviews performed with existing crowdsourcing platforms, along with results from previous studies on user motivation, organized using the Genex framework - a framework developed to aid developers in designing tools that support creativity in an online context. The resulting outcome of this study is the FEMM framework; a framework that links specific user motivators with certain activities in the creative process, for which they are used to drive user participation in. This framework provides, in addition to the identification of connections between user motivators and activities in the creative process, examples of tools and functionalities available to Realize in encouraging the partaking in activities. The provided FEMM framework, and associated visualization, will benefit Realize in the process of development, as well as attracting a user base - identifying aspects that are considered necessary, and aspects that could provide Realize with a competitive advantage. The authors suggest that further studies aim to validate the FEMM framework, mainly through the studying of a significantly larger sample size, in order to increase the external reliability and the generalizability. Other areas include firm incentives, key platform attributes, and risks involved.

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