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Purpose The application of knowledge management (KM) in government agencies is one strategy to deal with government problems effectively and efficiently. This study aims to identify KM readiness critical success factors (CSFs), measure the level of readiness for KM implementation, identify improvement initiatives and develop KM readiness models for government agencies. This model plays a role in the implementation of KM successful. Design/methodology/approach The level of readiness is obtained by calculating the factor weights of the opinions of experts using the entropy method. The readiness value is calculated from the results of the questionnaire with average descriptive statistics. The method for analysis of improvement initiatives adopts the Asian Productivity Organization framework. The model was developed based on a systems approach and expert validation. Findings Reliability testing with a Cronbach’s alpha value for entropy is 0.861 and the questionnaire is 0.920. The result of measuring KM readiness in government agencies is 75.29% which is at level 3 (ready/needs improvement). The improvement in the level of readiness is divided into two parts: increasing the value of factors that are still less than ready (75%) and increasing the value of all factors to level 4 (84%). The model consists of three main sections: input (KMCSFs), process (KM readiness) and output (KM implementation). Research limitations/implications The first suggestion is that the sample of employees used in this study is still in limited quantities, that is, 50% of the total population. The second limitation is determining KMCSFs. According to experts, combining this study with factor search and correlation computations would make it more complete. The expert’s advice aims to obtain factors that can be truly tested both subjectively and objectively. Finally, regarding literature selection for future research, it is recommended to use a systematic literature review such as the preferred reporting items for systematic reviews and meta-analyses and Kitchenham procedures. Practical implications The management must also prioritize KMCSF according to its level and make KMCSF a key performance indicator. For example, at the priority level, active leadership in KM is the leading performance indicator of a leader. Then at the second priority level, management can make a culture of sharing an indicator of employee performance through a gamification program. The last point that management must pay attention to in implementing all of these recommendations is to collaborate with relevant stakeholders, for example, those authorized to draft regulations and develop human resources. Originality/value This study proposes a novel comprehensive framework to measure and improve KM implementation readiness in government agencies. This study also proposes a KMCSF and novel KM readiness model with its improvement initiatives through this framework.
Purpose The application of knowledge management (KM) in government agencies is one strategy to deal with government problems effectively and efficiently. This study aims to identify KM readiness critical success factors (CSFs), measure the level of readiness for KM implementation, identify improvement initiatives and develop KM readiness models for government agencies. This model plays a role in the implementation of KM successful. Design/methodology/approach The level of readiness is obtained by calculating the factor weights of the opinions of experts using the entropy method. The readiness value is calculated from the results of the questionnaire with average descriptive statistics. The method for analysis of improvement initiatives adopts the Asian Productivity Organization framework. The model was developed based on a systems approach and expert validation. Findings Reliability testing with a Cronbach’s alpha value for entropy is 0.861 and the questionnaire is 0.920. The result of measuring KM readiness in government agencies is 75.29% which is at level 3 (ready/needs improvement). The improvement in the level of readiness is divided into two parts: increasing the value of factors that are still less than ready (75%) and increasing the value of all factors to level 4 (84%). The model consists of three main sections: input (KMCSFs), process (KM readiness) and output (KM implementation). Research limitations/implications The first suggestion is that the sample of employees used in this study is still in limited quantities, that is, 50% of the total population. The second limitation is determining KMCSFs. According to experts, combining this study with factor search and correlation computations would make it more complete. The expert’s advice aims to obtain factors that can be truly tested both subjectively and objectively. Finally, regarding literature selection for future research, it is recommended to use a systematic literature review such as the preferred reporting items for systematic reviews and meta-analyses and Kitchenham procedures. Practical implications The management must also prioritize KMCSF according to its level and make KMCSF a key performance indicator. For example, at the priority level, active leadership in KM is the leading performance indicator of a leader. Then at the second priority level, management can make a culture of sharing an indicator of employee performance through a gamification program. The last point that management must pay attention to in implementing all of these recommendations is to collaborate with relevant stakeholders, for example, those authorized to draft regulations and develop human resources. Originality/value This study proposes a novel comprehensive framework to measure and improve KM implementation readiness in government agencies. This study also proposes a KMCSF and novel KM readiness model with its improvement initiatives through this framework.
Aim of research. Design thinking (DT) is an essential context for knowledge management (KM), as it promotes the link between KM initiatives and an organization's strategic goals and objectives. This article analyzes the DT process in terms of its capability to create KM. The detailed analysis on the aspect of the working mechanism of DT – how KM is represented and created in the process. This article examines the DT procedure in terms of its ability to generate design knowledge. In this regard, the main purpose of this paper is to review the approaches to KM applied to DT and to suggest directions for how such a supervisory system could evolve. Methodology. This study is thematic in its nature and it was prepared on the basis of secondary data and also based on an inclusive review of the literature and similarly computation of secondary information. To formulate this paper the researchers used books, earlier published articles, conference papers, and numerous research reports. Results and conclusions. This article concludes by proposing an intuitive model for DT and KM. KM for its successful application in higher learning institutions in the areas of course design institutional strategy formation and faculty resource sharing.
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