نشریه مدیریت راهبردی دانش سازمانی
پیاپی 25 (تابستان 1403)

Nowadays, knowledge-based governance can have a valuable impact on improving the performance of both government and private institutions. However, there is a possibility of overlooking the influential factors on this type of governance. Therefore, adherence to the principles of knowledge-based governance can contribute to improving the situation of organizations, and society, allowing for the maximum utilization of individuals' abilities, reducing societal challenges, and ultimately pursuing the public welfare. This research has employed a qualitative methodology and is based on Grounded theory, using the approaches of Strauss and Corbin. The study population consists of experts familiar with the subject, with 12 of them being selected through purposive and snowball sampling methods for in-depth interviews. We used MAXQDA software to analyse the data. 302 codes are identified and placed in the 46 subcategories and 18 main categories, which are in 6 main categories under the headings of causal conditions, including sharing, creating, preserving and maintaining knowledge, competence of managers. background conditions, including creating infrastructure, structure organization and culture of the organization. Intermediate conditions include rules and procedures, performance evaluation, transparency, team building, recruitment and retention, planning and administration system. The innovation dynamic capability and development strategy are strategic conditions. The performance of the society, organization and the employees are the consequence. The central condition is knowledge-based governance. The Grounded approach and model design in executive organizations has a unique aspect and facilitate the implementation of knowledge governance in executive organizations of the country.

Today, the efficient sharing of knowledge increases the chances of survival of organizations and is considered as a strategic resource for improving the productivity of organizations. The purpose of this research is to identify knowledge sharing mindsets among generation Z employees in a defense research training center in Malik Ashtar University of Technology. The current research is cross-sectional in terms of practical purpose, in terms of descriptive method, in terms of quantitative and qualitative (mixed) data collection, and in terms of time horizon, and as far as the researchers have investigated, no research with this title has been conducted. The statistical population of the research consisted of 20 employees of generation Z (born in 1373 and later) and several university faculty members who were selected purposefully. Q methodology has been used to analyze the collected statistical data. In this research, after reviewing the subject literature and conducting interviews with several university experts, different propositions regarding the research topic (36 indicators) were identified and extracted. Then the questionnaires were completed by 20 participants in the research and the collected data were analyzed by exploratory factor analysis. Seven different mentalities and viewpoints with the names of good sense of knowledge sharing, knowledge-oriented leadership, teamwork, reward system, perception of relative benefits, job satisfaction and organizational commitment were discovered and identified, which explain and cover 77% of the total variance.

The current research has been done with the aim of presenting a model of knowledge management in universities. In terms of methodology, this research is of the type of applied studies, and in terms of method, it is among the qualitative and meta-composite researches. For this purpose, it was used through searching in the internal and external scientific databases of the Iran Scientific Information and Documents Center (IranDac), Jihad Academic Database, Islamic World Citation Database, Web of Science, ProQuest, Scopus, Google Scholar and Science Direct. 786 articles were extracted according to the defined search strategy, and at the end of the review process, 41 sources were selected for final analysis. The content validity of these documents was verified by the Critical Assessment Tool (CASP) method. In the analysis stage of the selected documents, the sub-components and open codes of these documents were extracted by the qualitative content analysis method and then categorized and combined under the main components and dimensions of the research. In order to validate the findings, the method of comparing the opinion of researchers with an expert was used, and the Kappa agreement coefficient was 0.783. The results showed that according to the nature of the university, four main categories can be considered for the model of knowledge management in universities. Knowledge vision plan, knowledge flow, knowledge transformation and knowledge evaluation. Also, the results showed that the four factors of culture, technology, environment and stakeholders play an important role in the success of the knowledge management model based on the context of knowledge management in the university. In a general summary, it can be said that knowledge management in universities is not limited to a specific time and program, and with the end of the four stages of this model, knowledge management will enter the stage of a new knowledge plan.

Knowledge hoarding by knowledge workers deprives the organization of very valuable resources and can have many direct and indirect consequences. This research was conducted with the aim of identifying and validating its. This applied research has been done with a mixed sequential exploratory approach. Factors have been identified with a qualitative approach using thematic analysis method. The participants of this stage were the selected technical experts of Nahaja, and a semi-structured interview was used to survey their views. The quantitative stage was carried out in order to validate the identified factors. For this purpose, a questionnaire distributed among selected thecnical experts. These data were analysed through structural equation modeling (confirmatory factor analysis) and Smart Pls version 3 software. The findings showed that the antecedents of knowledge hoarding include individual factors (tendencies and interests, concerns and worries, motivations, individual traits and characteristics), interpersonal factors (communication factors), organizational factors (occupational factors, culture organizational, managerial factors, and structural factors), extra-organizational factors (social, cultural and economic factors). Also, the consequences of knowledge hoarding were classified into two categories of individual and organizational consequences. Quantitative analyzes also confirmed the significance of the relationship between the desired indicators and components. The results of this research can provide useful knowledge in this field to manage the phenomenon of knowledge hoarding. The simultaneous identification of factors affecting the occurrence of knowledge hoarding in the aforementioned four levels, as well as the consequences of this complication for knowledge workers and the organization, can provide an effective understanding for the management of this destructive organizational behavior. The simultaneous attention to the roots and individual and organizational consequences of this complication is considered the outstanding distinguishing feature of this research.

Considering the importance of knowledge management in improving the performance of various industries, including the electricity industry, in areas such as reducing safety risks, using complex systems, etc., it is necessary to maintain and absorb knowledge in order to improve the skill level of employees. The purpose of this research is to investigate how Metaverse technology works in retention and absorbing knowledge in the electricity industry of the country. In order to carry out the present research, at first, 12 achievements resulting from the operation of Metaverse technology were identified by reviewing the background of the research and were approved by the experts and managers of the country's electricity industry. In the following, by using judgmental sampling method and asking opinions from 15 academic experts and managers of the country's electricity industry, the relationship between the achievements of Metaverse technology in the country's electricity industry was identified and a conceptual model of how Metaverse technology works in retention and absorbing knowledge. It was presented in the electricity industry of the country. In order to fit the presented model, structural equation modeling approach and Smart PLS software were used. Interpretive structural modeling has shortcomings such as relying on the intuition and judgment of the participants. This problem affects the validity of interpretive structural modeling approach. To solve this problem and in order to validate the presented model resulting from the interpretive structural modeling approach, the structural equation modeling approach and Smart PLS software were used. Using available sampling method, 350 questionnaires were distributed among the employees and managers of the country's electricity industry, and 307 questionnaires were returned. The results of this research showed that metaverse technology through capabilities such as environmental artificial intelligence, simulation, natural language processing, use of social networks, data analysis, knowledge organization, cooperation, knowledge sharing. Access to extensive resources, interactive education, knowledge storage and knowledge updating play a fundamental role in retention and absorbing knowledge.

The aim of the current research was to apply the clustering technique in order to analyze the state of knowledge management in Golestan University, so this research is applied, in terms of descriptive-survey purpose. In this research, the researchers have taken a holistic and systemic view of the knowledge management category and did not consider the implementation of knowledge management in the university to be dependent on the availability or need of a specific group. The members of the statistical sample were 281 administrators, faculty members, and scientific assistants of Golestan University, who were selected through stratified sampling and they were measured through Newman and Conrad's general management questionnaire, whose reliability and validity were confirmed using Cronbach's alpha and confirmatory factor analysis, respectively. In the first step, according to the four dimensions of the knowledge management cycle, the current state of knowledge management in Golestan University was analyzed at three levels of managers, faculty members and scientific assistants using non-hierarchical cluster analysis and Rapidminer software, and the number of optimal clusters according to the index Davis-Bouldin was obtained. In the second step, the members of the statistical sample placed in each cluster were analyzed based on their demographic characteristics. The results showed that in both clusters, the status of the four dimensions of knowledge management at the confidence level of 0.95 was lower than the number 3, and the analysis of the demographic characteristics of the clusters with the chi-square test at the confidence level of 0.95 showed that the results obtained with mental templates Preformed has a significant difference. The research results emphasize the implementation of knowledge management in Golestan University.