... from the ad hoc survey using the data mining (deep learning) technique. Findings The research sets out and tests factors relevant to understanding how to predict innovation in uncertain business environments. This study identifies four factors fostering innovation in SMEs: knowledge...

... decisions. Design/methodology/approach This research methodology uses combination approaches, namely, contingency factor analysis (CFA), the cross-industry standard process for data mining (CRISP-DM) and knowledge management system development life cycle (KMSDLC). The CFA for KM solution design...

... to show that whether knowledge workers’ behavior patterns in sharing information and knowledge throughout a KMS have any specific effect or not. Design/methodology/approach This paper proposed a framework to mine knowledge workers’ raw data using data mining techniques such as clustering...

.... fragmented view of the knowledge discovery and data mining (KDDM) process; lack of support for the end-to-end KDDM process; and lack of adequate attention toward business understanding phase. 12 01 2015 30 07 2015 14 11 2015 07 12 2015 © Emerald Group Publishing Limited...

... data. The market criterion analyzes the marketing capacity of the target company, in terms of supply and demand, and uses the following patento-scientometric indicators: Data mining Patents Business intelligence Innovation management Evaluation Entrepreneurship Studies...

... proposed is Knowledge4Scrum, a novel knowledge management tool for agile distributed teams. Knowledge4Scrum will act as a global repository for knowledge sharing in Scrum distributed teams with the possibility of creating new knowledge through data mining techniques. Valid past projects data have been...