Enhancing Knowledge Work Through Crowdsourcing in Adaptive Case Management Systems

Increasing the productivity of Knowledge Workers is considered as an important management challenge for an information society. The complexity of Knowledge Work confronts Knowledge Workers with tasks outside their expertise or overextend their physical capabilities. Crowdsourcing solves this problem by allowing Knowledge Workers to employ a global pool of work force for various types of applications. While utilizing Crowdsourcing, Knowledge Workers have to deal with additional efforts which reduce their overall productivity. A holistic solution, that combines the scopes of Knowledge Work and Crowdsourcing, promises to overcome these problems. This thesis analyses state of the art approaches within Knowledge Work and Crowdsourcing, and introduces a concept which allows the integration of Crowdsourcing in the process of Knowledge Work. In addition to the theoretical examinations, an implemented prototype demonstrates the applicability of the concept.