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Understanding Knowledge Storage/Retrieval System Success: An Analytic Network Process Perspective

Taraszewski, Stephen A
http://orcid.org/0000-0001-9525-9098
http://rave.ohiolink.edu/etdc/view?acc_num=csu1493926537562139

Abstract Details

2017, Doctor of Business Administration, Cleveland State University, 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 methodology to address this complexity and further, the ANP is employed in this study in a rather unique manner to determine the ranking of the success constructs. Finally, the ANP row-based influence, marginal, and perspective sensitivity analyses are performed on the synthesized model to more deeply investigate the robustness of the model and help illuminate interesting relationships for practitioners and future researchers alike.
Radha Appan, Ph.D. (Committee Chair)
Oya Tukel, Ph.D. (Committee Member)
Timothy Arndt, Ph.D. (Committee Member)
Birsen Karpak, Ph.D. (Committee Member)
240 p.
Information Systems
KMS; knowledge management systems; storage retrieval system; ANP; analytic network process; sensitivity analysis

Recommended Citations

Citations

  • Taraszewski, S. A. (2017). Understanding Knowledge Storage/Retrieval System Success: An Analytic Network Process Perspective [Doctoral dissertation, Cleveland State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=csu1493926537562139

    APA Style (7th edition)

  • Taraszewski, Stephen. Understanding Knowledge Storage/Retrieval System Success: An Analytic Network Process Perspective. 2017. Cleveland State University, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=csu1493926537562139.

    MLA Style (8th edition)

  • Taraszewski, Stephen. "Understanding Knowledge Storage/Retrieval System Success: An Analytic Network Process Perspective." Doctoral dissertation, Cleveland State University, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=csu1493926537562139

    Chicago Manual of Style (17th edition)

csu1493926537562139
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© 2017, all rights reserved.
This open access ETD is published by Cleveland State University and OhioLINK.