Evaluating Knowledge Management Maturity by Interval Type 2 Fuzzy Sets

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RONAGHI MOHAMMAD HOSSEIN

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Journal: LIBRARY AND INFORMATION SCIENCE Year:2021 | Volume:24 | Issue:1 (93) Page(s): 156-173

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Title

Evaluating Knowledge Management Maturity by Interval Type 2 Fuzzy Sets

Author(s)

RONAGHI MOHAMMAD HOSSEIN | Issue Writer Certificate

Keywords

Knowledge management maturityQ1

Knowledge management processQ1

Knowledge management technologyQ1

AHPQ1

Type-2 fuzzy setsQ1

Abstract

Objective: Knowledge management (KM) is a concept of managing knowledge in the company. The implementation of concept has different levels in each company. Organizations implement KM practices and technologies based on the promise of increasing their effectiveness, efficiency, and competitiveness. The concept of maturity can be used for defining the state of effectiveness of an organization or the state of its capability and competency in managing the processes, programs or projects effectively. KM maturity is a guide or measure of the company's position in managing of knowledge. The multi-criteria decision making (MCDM) is widely used method to evaluate criteria that are typically multiple. crisp decision-making method is not appropriate because many of the maintenance goals taken as criteria are nonmonetary and difficult to be quantified. Type-2 fuzzy sets are used for modeling uncertainty and imprecision in a better way because of fuzzy membership function. Some fuzzy multicriteria methods have recently been extended by using Type-2 fuzzy sets. Analytic Hierarchy Process (AHP) is a widely used multicriteria method that can take into account various and conflicting criteria at the same time. Therefore, the aim of this study is to evaluate KM maturity using Analytic Hierarchy Process method under interval type-2 fuzzy environment. Methodology: This research is a descriptive survey. KM dimensions were ranked by a panel of experts, which consists of seven members. Experts panel consist of faculty of management who published papers and books in KM field. To clarify the evaluation process, an IT company is taken as a case and using APQC's (American Productivity and Quality Center) model. APQC’ s Levels of KM maturity provide a road map for moving from immature, inconsistent KM activities to mature; disciplined approaches aligned with strategic business imperatives. The survey sample population consisted of 273 employees and managers of the case. Findings: According to fuzzy analytic hierarchy process results KM process (0. 24), technology (0. 23), evaluation (0. 20), KM culture (0. 18) and leadership (0. 15) are the most important dimensions of KM maturity. it was revealed that the importance of KM processes could be ordered as following: Knowledge Capturing, Knowledge Creation, Knowledge Transferring, and Knowledge Reusing. Also, the results showed the case is located on third level of Km maturity (standardize). The primary focus at Level 3 is to manage the KM strategy, processes, and approaches identified and defined in Level 2. Conclusion: An important part of the results revealed how to use fuzzy analytic hierarchy process for evaluating KM maturity and the importance of processes and technology in KM maturity. In addition, the case is located on third level of KM maturity; during this third level, the KM team often evolves into a KM Center of Excellence with oversight responsibilities for the KM approaches and processes. Oversight includes identifying opportunities to apply select KM approaches and processes, securing funding and resources for the pilots, marketing and communicating the strategy, implementing a change management strategy, and refining the KM approaches and processes into standard, replicable methodologies.

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APA: Copy

RONAGHI, MOHAMMAD HOSSEIN. (2021). Evaluating Knowledge Management Maturity by Interval Type 2 Fuzzy Sets. LIBRARY AND INFORMATION SCIENCE, 24(1 (93) ), 156-173. SID. https://sid.ir/paper/388511/en

Vancouver: Copy

RONAGHI MOHAMMAD HOSSEIN. Evaluating Knowledge Management Maturity by Interval Type 2 Fuzzy Sets. LIBRARY AND INFORMATION SCIENCE[Internet]. 2021;24(1 (93) ):156-173. Available from: https://sid.ir/paper/388511/en

IEEE: Copy

MOHAMMAD HOSSEIN RONAGHI, “Evaluating Knowledge Management Maturity by Interval Type 2 Fuzzy Sets,” LIBRARY AND INFORMATION SCIENCE, vol. 24, no. 1 (93) , pp. 156–173, 2021, [Online]. Available: https://sid.ir/paper/388511/en

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