Innovation in business Intelligence systems

Abstract

Innovation crowdsourcing communities play a central role for companies to advance their innovation capabilities and portfolio by leveraging crowd intelligence and knowledge. However, it remains unclear how the mechanisms and structure of innovation crowdsourcing communities affect firms' innovation performance. Based on the open innovation theory and knowledge-based view (KBV), this study develops a research model to investigate how the structure and mechanisms of innovation crowdsourcing influence firms' knowledge management and innovation performance. The model was tested using structural equation modeling based on a dataset from the Microsoft community for business intelligence tools. The results show that both organizational and technical mechanisms of the community positively influence the community structure. The community structure positively influences knowledge acquisition, knowledge transformation, and the size and diversity of crowd participation. In turn, innovation crowdsourcing mechanisms and knowledge transformation have a strong influence on innovation performance.