CCE Theses and Dissertations
Date of Award
2018
Document Type
Dissertation
Degree Name
Doctor of Philosophy in Computer Information Systems (DCIS)
Department
College of Engineering and Computing
Advisor
Peixiang Liu
Committee Member
Gurvirender Tejay
Committee Member
James D. Cannady
Keywords
KMS, Knowledge Management, Knowledge Management Systems, Storytelling, Tacit Knowledge
Abstract
Since the 1990s, Knowledge Management Systems (KMS) have been largely unsuccessful in the collection of tacit knowledge. The process, whether through direct input by the holder of the tacit knowledge or through an intermediary such as the collection of tacit knowledge through interviews and videos, has not succeeded. Reasons encompass the organizational (such as culture of the organization), the technological (example: poor tools), and the individual (example: knowledge is power, i.e. where experts with rare knowledge results in knowledge hoarding instead of transfer). The purpose of this study was to demonstrate that tacit knowledge could be successfully and consistently collected from the participants themselves and placed into a KMS using a storytelling-based approach. This study extended past research that collected stories for KMS’ using interviews and videos by having participants directly entering their data, as stories, into a KMS. This was a new approach and it was posited that having participants use stories to enter their tacit knowledge themselves into a KMS would overcome their reluctance to provide tacit knowledge thus overcoming barriers to providing tacit knowledge into a KMS The validation methodology was based upon three elements: the deep-dive research element, the issues and solution element, and the dissertation proposition element. The deep-dive research element was the extensive research for the study into knowledge management, storytelling, and other various methods for collection of tacit knowledge. The issues and solution element consisted of issues about tacit knowledge that were identified from the deep-dive research element, i.e. general arguments constructed about knowledge management which were backed by data from research into knowledge management systems and storytelling. Theoretical solutions to the issues regarding the capture of tacit knowledge were then constructed which included the storytelling-based approach and a KMS framework for the collection of tacit knowledge. Lastly was the dissertation proposition element which consisted of a thorough analysis of the survey data against each of the dissertation propositions. There were three propositions. Proposition 1 was sharing of knowledge and the storytelling-based approach. Proposition 2 was about the framework, the scenarios, guiding questions, and Communities of Practice (CoP), and Proposition 3 was about participant knowledge and interaction with forums. Each proposition was evaluated independently. The study was successful and validated propositions 1 and 2. For proposition 1, 81% of the participants responded positively to the eight study questions directed towards this proposition. For all eight questions across all 21 participants, the mean was 29.952 against a target test mean of 24 with a range of 27.538-32.367. For proposition 2, 76.19% of participants scored this section positive. For all six questions across all 21 participants, the mean was 23 against a target test mean of 18 with a range of 21.394-24.606. However, the results for proposition 3 were inconclusive and must be considered a failure. Most of the respondents either scored ‘no change’ to at least 50% of the questions or they stated they had never been to a forum. For all four questions across all 21 participants, the mean was 12.905 against a target mean of 12 with a range of 11.896-13.914. Based upon propositions 1 and 2, the null hypothesis was disproved. Participants liked the storytelling-based approach, providing their tacit knowledge, and they liked the framework.
NSUWorks Citation
Nicholas Shaw. 2018. A Knowledge Management System (KMS) Using a Storytelling-based Approach to Collect Tacit Knowledge. Doctoral dissertation. Nova Southeastern University. Retrieved from NSUWorks, College of Engineering and Computing. (1033)
https://nsuworks.nova.edu/gscis_etd/1033.