Dynamic Quality Management for Cloud Labor Services

Cloud labor services extend the cloud computing paradigm by providing human workforce as a scalable resource over the Internet. The approach can help labor-intensive industries to react more flexibly to varying demands but at the same time introduces severe challenges regarding quality management. This thesis addresses the challenges by using a combination of statistical quality control and newly developed dynamic voting mechanisms. Several case studies illustrate the benefits of the approach.