Knowledge Management Maturity Level Research Articles

Designing an expert fuzzy system to select the appropriate knowledge management strategy in accordance with APO model and Bloodgood KM strategies

PurposeSelection of knowledge management strategies (KMS) is one of the most important and effective factors in acquiring the competitive advantage and elevating the knowledge level of the organizations. Those organizations that have taken steps toward knowledge management necessarily need to pay utmost attention to the matter of KMS before taking any further steps in their activities. One of the effective ways in adopting the proper KMS is evaluating the knowledge management maturity level in the organization. The purpose of this paper is to design an expert fuzzy system to adopt the KMS based on Bloodgood model in accordance with the maturity level of the organization.Design/methodology/approachIn this method, with the help of expert fuzzy system, a model has been designed, by using MATLAB software, to adopt the KMS. The KM maturity level, tacit knowledge and explicit knowledge are chosen as inputs, and each one of Bloodgood’s KMS (production, transfer and protecting the knowledge) are chosen as outputs. To perform the system, the maturity level of knowledge management of an industrial organization that has been evaluated by the standard Asian Productivity Organization questionnaire is used as the input, which has been given to expert fuzzy system. Then, considering the output of the system, KMS for the organization have been recommended.FindingsKnowledge management maturity level of the organization is on Level 4; considering the expert fuzzy system that has been designed, “knowledge production” strategy is recommended for the organization under study.Originality/valueAn expert fuzzy system has been designed regarding the maturity of knowledge management and Bloodgood model that can be used as a guide for organizations and academic people as an appropriate practical model for selecting knowledge management strategies.

Strategies of Knowledge Management Implementation for Academic Services Improvement of Indonesian Higher Education

This study aimed to analyse the implementation form and the maturity level of knowledge management (KM) and formulate recommendations of KM implementation strategies for improvement of academic services at universities in Indonesia. The analysis of the KM implementation was conducted at four top universities in Indonesia based on the ranking of the Indonesian Ministry of Research, Technology and Higher Education 2016, viz., ITB, UGM, UI and IPB. Primary data were obtained from the library of ITB, UGM, UI, and IPB and from 510 academicians of IPB, while secondary data was obtained by content analysis. The result showed that the top four universities in Indonesia have had the basic infrastructure for KM implementation; their management have been actively participating in the promotion of KM initiatives by articulating KM strategy and providing budgetary allocations and rewards system. Several pilot projects were undertaken to develop KM application into a higher level. The utilisation of KM application has not been optimal; knowledge sharing has not yet become a culture. The KM maturity implementation in the library of ITB, UGM, UI and IPB is at the third level. The result of the measurement of interoperability maturity level of seven IPB academic service applications just on the average reaches third level and is still in the stage of data integration. The KM implementation strategies that were recommended to improve the academic services at IPB, among other things, the reinforcement of the role of chief knowledge officer, the promotion of knowledge sharing culture with the knowledge repository optimisation, the formation of a community of practices, the development of knowledge portal, the optimisation of e-learning system and the improvement of rewards system.

Knowledge Management Patterns Model for a Flight Test Environment

This paper investigates how Knowledge Management patterns in a Brazilian Air Force flight test environment can be simulated using a System Dynamics approach. The research has been conducted initially by a literature review on the main Knowledge Management and System Dynamics theories. Data for this research has been collected in a previous study consisted of documental research regarding the flight test environment Knowledge Management and a questionnaire-based survey which identified both a low Knowledge Management maturity level and the flight test core competence as the capability of performing flight test campaigns. The issued problem was the tradeoff between actions focused on performing flight test campaigns versus Knowledge Management to transfer the core competence inside organization in order to keep it in a high level. A system dynamics quantitative model has been developed as a result of this research. Fluxes and stokes were identified within the model and the relation between them emerged by identifying systemic feedback loops that may compromise the Knowledge Management and the core competence transferring. These features enable a holistic visualization and better understanding of the problem as well as the possibilities of identifying ways of improvement.

An application of the knowledge management maturity model: the case of credit unions

The purpose of this study is to investigate the level of knowledge management (KM) maturity of credit unions. The application of a maturity model to 15 credit unions in North America revealed that an overall level of KM maturity is at an early stage of development, but there are signs of future improvement. Credit unions operate in a highly competitive, knowledge-intensive financial industry and experience various pressures to increase their efficiency, which they can achieve through the implementation of KM solutions. Despite the absence of official KM strategies, KM projects were introduced locally in order to fill particular knowledge gaps. The availability of IT infrastructure and the implementation of KM-related technologies alone are insufficient to ensure universal success of organizational KM activities. Credit union managers periodically access and use academic research in their decision making. At the same time, they prefer accessing scholarly knowledge in translated form from books, practitioner magazines, and consultants. It was concluded that organizations competing in the knowledge-intensive sector have an inner need for KM solutions.

Explanation of Valuation Criteria Based on Maturity Level of Knowledge Management

Explanation of Valuation Criteria Based on Maturity Level of Knowledge Management

Middle managers, their organization and knowledge sharing: Examination of knowledge sharing maturity

The purpose of this paper is to highlight the role of middle managers in the knowledge sharing process by presenting the results of a survey aiming to reveal the elements of middle managers knowledge sharing maturity and individual and organizational characteristics affecting them. The paper is based on quantitative research. The data were gathered through questionnaires. Based on 400 usable survey responses, the authors applied principal component analysis, decision tree, analysis of variance, and post-hoc test to reveal the elements of middle managers knowledge sharing maturity and the differences individual and organizational characteristics result in them. The study results indicate that middle managers knowledge sharing maturity is measured with four elements and based on individual and organizational characteristics there are differences in certain elements. The originality of the paper is that past research did not investigate middle managers or their knowledge sharing maturity, only focused on the organizational level of knowledge management maturity. The effect of individual and organizational characteristics on knowledge sharing maturity has not been investigated either. This paper focuses on these aspects. The results of the survey could help not only middle managers, but top managers and other employees as well in learning how to foster knowledge sharing.

Knowledge Management Maturity in Construction Companies

Knowledge management is a concept of managing of knowledge in the company. The implementation of concept has different levels in each company. Knowledge management maturity is a guide or measure of the company's position in managing of knowledge. The objective of the study is to identify knowledge management maturity in Indonesian construction companies. This study used a survey method and conducted by distributing questionnaires to large construction companies that implement knowledge management activities. Four level of knowledge management maturity was proposed on this study. The results show that 29 contractors at the practiced level, 20 contractors at managed level and 5 contractors at continuously improved level.

Providing a pattern for planning and Leading Knowledge Management in special Holding Companies

It is widely recognized that knowledge is an essential strategic resource for a firm to retain sustainable competitive advantage. Knowledge management systems usually will be responsible for this role. Organizations for effective and efficient management of knowledge must have a documented strategic plan. Holding companies (HCs) differ in their nature and behavior from other types of companies. However, due to the specific features and conditions of Holding Companies in our country, the usual Knowledge management strategic planning methods are not appropriate and it’s necessary to design a method to suit them. This paper has tried to use strategic control perspective, and presented a four-step methodology for planning strategic knowledge management programs at Holding Companies. The findings indicate a four-step methodology (including a general formulation, organizing, classifying companies based on the maturity level of knowledge management and integration of operational planning at the level of the subsidiary companies) based on strategic control to plan and lead knowledge management in holding companies due to the maturity level of knowledge of in subsidiary companies.

Exploring the Correlation Between Knowledge Management Maturity and Intellectual Capital Efficiency in Mainland Chinese Listed Companies

In today's knowledge-based society, discussion on intellectual capital (IC) has become intertwined with knowledge management (KM). KM may be viewed as the activities and processes to create and maximise IC. It may be possible to suggest that an organisation's level of knowledge utilisation is associated with its level of intellectual capital. The purpose of this research was to explore whether there is an association between KM maturity level, as a proxy of assessing the level of KM efficacy and IC utilisation efficiency in companies listed on CSI 100 (China Securities Index Co., Ltd.) in mainland China. A self-assessment of KM maturity level, developed based on the KM self-assessment framework proposed by Collison and Parcell, was used to gauge the knowledge utilisation of an organisation. The intellectual capital efficiency coefficient (ICE), component of the Value Added Intellectual Coefficient (VAIC™), was used to assess the efficiency of intellectual capital. Overall, 26 questionnaires were collected from the surveyed organisations to evaluate their level of KM, which accounted for 25% of the sample. Finally, correlation analysis with SPSS was performed to examine if there was a correlation between ICE and the maturity level of KM in the sampled companies in mainland China. The results showed that the association between the two variables was not statistically significant. In fact, no conclusive evidence was found to support an association between efficiency of utilising intellectual capital, and KM maturity score. The lack of an association may suggest that there may be other intervening variables yet to be identified in the relationship between KM and IC. This study is an attempt to explore the above assertion and to conduct empirical studies in studying their applicability in China, one of the fastest growing economies in the world. While we are not seeking to generalise the results, it may serve as a good reference for further studies in examining the intricate "relationship" between IC and KM, that is, linking a process view of KM to the measurement of value creating intangibles of a corporation epitomised by IC.

Using communities of practice towards the next level of knowledge-management maturity

Background: Effective communities of practice undoubtedly impact organisations’ knowledge management and contribute towards building a learning-organisation culture. Communities of practice represent an environment conducive to learning and for exchanging ideas, and they are a formal learning forum. However, the level of organisational learning to which communities of practice contribute is difficult to measure.Objectives: The research was conducted to analyse the impact of communities of practice on building a learning organisation. The organisational system, culture and people offer the key towards leveraging knowledge as a strategic resource in a learning organisation. The awareness of the organisation concerning knowledge management was measured on a replicated knowledge management maturity model.Method: The organisational knowledge base was analysed prior to the implementation of the communities of practice and was compared to the situation three years later. The research was based on experiential learning cycles that consisted of five consequential but perpetual stages,namely reflect, plan, act, observe and reflect again.Results: The results indicated that communities of practice were instrumental in leveraging the organisation to the next level in the knowledge-management maturity model. A collaboration framework was developed for each business unit to work towards a common goal by harnessing the knowledge that was shared.Conclusion: Although a positive impact by communities of practice is visible, an instrument for the measurement of intellectual capital is necessary. It is recommended that the monetary value of knowledge as an asset is determined so that the value of the potential intellectual capital can be measured.

Measurement of knowledge management maturity level within organizations

PurposeThe purpose of this paper is to develop a model for measuring knowledge management maturity level in organizations.Design/methodology/approachThis paper defines and extracts effective factors and indicators on knowledge management and proposes a schema for prioritizing and specifying the weight of each factor and variable. The paper further surveys and evaluates existing knowledge management models and presents a knowledge management maturity model with defined factors and variables.FindingsDefining and extracting 8 factors and 42 variables that affect knowledge management and subsequently developing a knowledge management maturity model. The model of this study is practical and helps to determine the maturity position of an organization in knowledge management by defining existing status of in factors and variables, and from the prioritization of factors and variables enabling the organization to optimize its profile.Research limitations/implicationsFor increasing generalization of model, future should utilize other organizations in diverse industries.Originality/valueThe base model of this research is CMMI instead of CMM and instead of KPAs we use CSFs and for measuring maturity position of organization using a questionnaire. This research model can be utilized as an alternative model in comparison to existing models.

The construction and application of knowledge navigator model (KNM™): An evaluation of knowledge management maturity

This study develops a knowledge navigator model (KNM™) to navigate knowledge management (KM) implementation journey. The KNM comprises two frameworks: evaluation and calculation framework. Qualitative research methods, including a literature review, in-depth interviews, focus groups and content analysis, are conducted to construct the evaluation framework of KNM. An algorithm model is proposed in the calculation framework and a 30 cases survey was employed to obtain the initial version of the score ranges used to differentiate maturity levels. Several propositions and the corresponding KNM were constructed. We define the KM maturity level into five stages: knowledge chaotic stage, knowledge conscientious stage, KM stage, KM advanced stage, and KM integration stage. The evaluation framework of KNM consists of three aspects: three target management objects (culture, KM process, and information technology), 68 KM activities, and 16 key areas (KAs). The initial version of the score ranges was identified. The study results can be referenced and the methodology can be applied to other countries, although the sample is confined to industries in Taiwan.

Assessing the enterprise's knowledge management maturity level

Knowledge is not manageable, as if it were data or information. Consequently, Knowledge Management (KM) must address activities that utilise and create knowledge, instead of addressing knowledge by itself. With regard to this issue, we elaborated on a sociotechnical approach of KM within the enterprise, and we synthesised it into an empirical model called the Model for General Knowledge Management within the Enterprise (MGKME). One purpose of this model is to serve as a template to enable assessing the enterprise's KM maturity level.

Guidelines for assessing the knowledge management maturity of organizations

In a recent article Kruger and Snyman hypothesized that progressions in knowledge management maturity (from a strategic perspective) are directly related to an increased ability to speed up the strategic cycle of imitation, consolidation and innovation. The arguments proposed, however, neglected to supply the reader with a practical toolkit or even a roadmap (a time-related matrix, or questionnaire) to successfully measure succession in knowledge management maturity. This article builds on the previous one and proposes a questionnaire consisting of six sections, containing 101 descriptive questions, to enable organizations to test and assess their knowledge management maturity empirically. The development of an instrument to measure knowledge management maturity required adhering to a research design that combined theoretical propositions with practical experimentation. As a point of departure, a knowledge management maturity matrix consisting of seven maturity levels was formulated. All questions contained within the matrix were benchmarked against a survey questionnaire developed by the public management service of the OECD (PUMA) and were also pre-tested and validated. This process of refinement led to the formulation of the Knowledge Management Maturity Questionnaire. To avoid any taint of this research being based only on theoretical propositions, the questionnaire was tested by 178 master students of the University of Pretoria, South Africa, in nine different industries. The proposed questionnaire provides a bridge between theoretical propositions and practical usability, not only enabling knowledge management practitioners to assess the level of knowledge management maturity reached successfully but, more importantly, also serving as a guideline to institutionalize further and future knowledge management endeavours.