The purpose of this research is to carry out a comparative analysis of organizational factors that facilitate knowledge sharing and business process, ultimately contributing to the improvement of organizational performance. The literature considers knowledge sharing a key factor for driving innovation as well as the organization's business performance, as both explicit and tacit knowledge sharing promotes a novel robust approach for business-knowledge process. This research explores the application of fuzzy-set qualitative comparative analysis as a set-theoretic comparative analysis approach to investigate the relationships between knowledge sharing, business process, and organizational performance through the identification of key organizational operation factors. Based on empirical data collected from 28 cases, the analysis results demonstrate the important role of organizational operation factors in knowledge sharing and business-knowledge process, which directly contribute to the improvement of organizational performance.

This study investigates the development of a structured knowledge-network model in information technology (IT) innovative and implementable projects to facilitate knowledge sharing and transfer in a multi-organization context. The study employs a practice-based perspective by using an exploratory case-study approach and a combination of thematicanalysis and comparative analysis to analyze the data across public organizations, private organizations, and international companies. The results identify organizational factors and their influence on knowledge channels and knowledge networks. The study contributes to organizational, administrative and knowledge management theories regarding organizational strategy, organizational culture, organizational capacity, knowledge network externalities, knowledge network intermediaries, and knowledge network infrastructures.

This paper focuses on knowledge management to enhance decision support systems for strategic intervention in IT project-oriented change management. It proposes a model of change management knowledge networks (CMKNM) to support decision by tackling three existing issues: insufficient knowledge traceability based on the relationships between knowledge elements and key factors; lack of procedural knowledge to provide adequate policies to guide changes; and lack of "lessons learned" documentation in knowledge-bases. A qualitative method was used to investigate issues surrounding knowledge mobilisation and knowledge networks. Empirical study was undertaken with industries to test the CMKNM. Results are presented from the empirical study on the key factors influencing knowledge mobilisation in IT project-oriented change management, knowledge networks and connections. The CMKNM model allows key knowledge mobilisation factors to be aligned with each other; it also defines the connections between knowledge networks allowing knowledge to be mobilised by tracing knowledge channels to support decision.

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