Abstract:
Crowdsourcing can be an efficient organisational strategy to harness innovation and agility by distributing work to Internet users. As crowdsourcing is different from other business strategies, organisations are often unsure about how to structure crowdsourcing as a business process. We identify two challenges: first, crowdsourcing has been perceived as a one-off endeavour and a comprehensive repeatable crowdsourcing process has not been defined yet. Second, while organisations need a solid knowledge base in order to integrate crowdsourcing with their business processes, the domain knowledge remains unstructured, scattered, and sometimes conflicting. Together, these challenges indicate that crowdsourcing needs to evolve from an immature form towards a more repeatable business process.
The research adopts the design science paradigm and follows four research stages. We first synthesise existing knowledge in the domain, which identifies twelve repeatable building blocks of crowdsourcing processes. Second, we define a model of business process crowdsourcing (BPC). The model has seven processes organised in three stages: decision to crowdsource, process design, and technical configuration. The model was empirically evaluated using two existing crowdsourcing projects. The results suggest the usefulness of the model for structuring crowdsourcing processes.
Third, we turn the BPC model into a heavyweight ontology that consolidates the domain knowledge. The ontology captures the following domain concepts: business processes, activities, data entities, data attributes, and their hierarchical relationships. It also captures decision-making relationships. We evaluated the ontology by triangulation. The findings are that the ontology provides a high coverage and clarity of the domain.
Finally, based on the ontology, a decision tool is developed. The tool provides advice to make informed decisions about BPC establishment. Using experiments and focus groups to evaluate the tool, the quantitative and qualitative results confirm its utility and show that the tool improves decision-making performance.
The dissertation contributes to the body of knowledge in several ways. It promotes and conceptualises crowdsourcing as an organisational business process. It offers a process model, ontology, and decision tool for BPC. It also provides empirical results about the use of the decision tool. By doing so, we hope that the dissertation will motivate organisations to further assimilate crowdsourcing.
