Doctor of Business Administration, Cleveland State University, 2017, Monte Ahuja College of Business

Organizations often begin knowledge management (KM) efforts by building knowledge repositories to store organizational knowledge to ensure that it may be later retrieved to reuse, share with, and transfer to knowledge workers. The use of such storage/retrieval systems (S/RS) are particularly relevant in preserving and restoring internal organizational knowledge; such implementations support reduced costs associated with knowledge reacquisition, recreation, and reinvention, thus increasing the efficiency of knowledge transfer. Additionally, there is an increased interest in newer uses of S/RS to support large-scale knowledge-bases and knowledge sharing communities. Therefore, it is important for organizations to understand the factors that influence success in S/RS, as generally, KM systems (KMS) initiatives have failed to realize promised results. This study focuses on knowledge flow from the knowledge repository to the knowledge consumer to facilitate and enable knowledge transfer (FEKT). Because of the strong relationship between S/RS processes and technologies and IS/IT, DeLone and McLean's (2003) IS success model serves as the foundation for the S/RS success model, which is modified here to include the complexities inherent in an S/RS. This empirical study presents a model of S/RS success in FEKT and identifies, prioritizes, and weights both the constructs that define S/RS success and the critical success factors (CSF) that influence these success constructs. In addition to informing KM practitioners, this research also addresses a research gap in the KM literature in respect to storage/retrieval systems in facilitating knowledge transfer. Moreover, while prior KMS research has generally assumed an independence in factors and constructs when empirically testing KMS success, this study embraces the notion that real-world factors and constructs are interrelated, intertwined, and interdependent; thus, the analytic network process (ANP) is used as an analytic method (open full item for complete abstract)

Committee: Radha Appan Ph.D. (Committee Chair); Oya Tukel Ph.D. (Committee Member); Timothy Arndt Ph.D. (Committee Member); Birsen Karpak Ph.D. (Committee Member) Subjects: Information Systems