Field Of Knowledge Management Research Articles

How does innovative customer knowledge influence electronic word-of-mouth recommendation behavior through egoistic and altruistic approaches? Testing a moderated mediation model

IntroductionAt present, innovative customer knowledge on social media platforms is mostly treated as a kind of “self-entertainment” activity content, and has not been effectively integrated and used by sales-oriented social media enterprises. As a result, the problem of electronic word-of-mouth recommendation reducing for such enterprises is more prominent. Theoretically, on the one hand, researches in the field of customer knowledge are mainly concentrated in the field of knowledge management led by the enterprise, which lacks to discuss the influence of innovative knowledge on electronic word-of-mouth recommendation behavior from the perspective of customer dominance. On the other hand, previous studies lack to explore the formation mechanism of electronic word-of-mouth recommendation behavior of innovative customers from the dual paths of altruism and egoism. The professional characteristics and social characteristics of innovative customers are not analyzed as boundary conditions. In this context, based on social learning theory and social identity theory, this study explores the influence mechanism of innovative customer knowledge on electronic word-of-mouth recommendation behavior.MethodsData were collected by Likert 5-level scale using questionnaire survey method. A total of 452 valid questionnaires were collected from Northeast, Northwest, East, North, Central, South and southwest China by random sampling method. SPSS21.0 software and Bootstrap (PROCESS3.0) program were used to analyze the multilevel linear regression, structural equation model and robustness test of the model.Results(1) Innovative customer knowledge had a significant positive impact on electronic word-of-mouth recommendation behavior and professional identity; (2) Professional identity had a significant positive effect on electronic word-of-mouth recommendation behavior; (3) Professional identity played mediating role between innovative customer knowledge and electronic word-of-mouth recommendation behavior; (4) Compared with high professional status and high social status, low professional status and low social status had a stronger moderating effect on the relationship between professional identity and electronic word-of-mouth recommendation behavior, and there was a moderated mediation effect.DiscussionInnovative customer knowledge generates electronic word-of-mouth recommendation behavior through two paths: altruism and egoism. These two paths are affected by the external characteristics of innovative customers, that is, professional characteristics and social characteristics have a moderating effect on them.

When knowledge workers meet AI? The double-edged sword effects of AI adoption on innovative work behavior

Purpose The purpose of this study was to investigate the impact of artificial intelligence (AI) adoption on knowledge workers' innovative work behaviors (IWB), as well as the mediating role of stress appraisal and the moderating role of individual learning abilities. Design/methodology/approach This study analyzed the questionnaire results of 313 knowledge workers, and data analysis was conducted by using SPSS 25.0, SPSS 25.0 macro-PROCESS and AMOS 28.0. Findings This study found that AI adoption has a double-edged sword effect on knowledge workers' IWB. Specifically, AI adoption can promote IWB by enhancing knowledge workers' challenging stress appraisal, while inhibiting IWB by fostering their hindering stress appraisal. Moreover, individual learning ability significantly moderated the relationship between AI adoption and stress appraisal, which further influenced IWB. Originality/value This study integrates the conflicting findings of previous studies and proposes a comprehensive theoretical model based on the theory of cognitive appraisal of stress. This study enriches the research on AI in the field of knowledge management, especially extending the understanding of the relationship between AI adoption and knowledge workers’ IWB by unraveling the psychological mechanisms and behavior outcomes of users' technology usage. Additionally, we provide new insights and suggestions for organizations to seek the cooperation and support of employees in introducing new technologies or driving intelligent transformation.

The relationship among the innovation environment, transactive memory system of the R&D team, and knowledge collaboration

The innovation environment is the basis for the operation of the innovation ecosystem. In an era where knowledge resources are increasingly recognized as core assets, the advent of transactive memory system (TMS) has significantly enhanced the knowledge collaboration among R&D (Research & Development) teams, thereby boosting their innovation performance. Based on the empirical analysis of 235 valid questionnaires, this paper explores the relationship among the innovation environment, R&D Team's TMS, and knowledge collaboration. The results show that: (1) the Innovation environment has a direct and significant positive effect on the team's TMS and knowledge collaboration; (2) Team's TMS has some direct and significant positive effects and mediating effects on Knowledge Collaboration, and the Coordination of team's TMS has no significant effect on the Knowledge Integration process of Knowledge Collaboration; (3) The innovation environment can indirectly affect the knowledge collaboration process through the Specialization and Credibility of the TMS. This study further enriches the relevant research in the field of knowledge management and provides theoretical support and countermeasures for enterprises to promote innovation and development by optimizing knowledge management.

Classifying the Breadth of Knowledge Management Frameworks

This study aims to analyze Knowledge Management frameworks and categorize them based on their specification breadth. A total of 27 frameworks, selected from the temporal spectrum spanning 1995 to 2016 and representative of the field of Knowledge Management, were examined using content analysis. This research employs a qualitative, exploratory, descriptive, and bibliographic approach. Among the 27 frameworks examined, 12 were identified as descriptive, while 15 exhibited hybrid characteristics. Additionally, existing typologies lack sufficient detail for successful replication. Consequently, it is imperative to develop structures underpinned by a conjunctive approach. Such structures should provide both a comprehensive overview and detailed prescriptions of the “what,” “why,” “who,” “how,” and “when” aspects of implementing and operationalizing Knowledge Management. The prevalence of hybrid frameworks is notable within the examined set, highlighting the need for an integrated approach that combines breadth and depth. Organizations require a sufficiently comprehensive and detailed roadmap to implement Knowledge Management effectively. This analysis expands upon prior research concerning the classification of Knowledge Management frameworks and introduces a novel and anticipated approach to classifying specification breadth.

Natural Experiments and Causation in Strategy Research

Research to inform organizational strategy decisions studies the impact of specific managerial decisions on performance. While links from decisions to outcomes can be convincingly identified in individual, specific circumstances, trying to do the same with a larger set of decisions and outcomes can be problematic. In a situation with a substantive sample, relying on standard metrics such as financial statements, the link to particular outcomes can be difficult to establish. Especially when trying to choose metrics not already correlated in some way. Our research is generally in the field of knowledge management (KM). The discipline has an extensive history of attempts to link better management of knowledge and other intangibles to performance outcomes. While the performance outcomes are fairly straightforward (financial success such as profitability or return on investment, innovation success, etc.), the metric for knowledge management is harder to pin down. The literature shows dozens of approaches. Some are for single firms or a small sample, but even if focusing only on metrics for a larger sample of firms, disagreement exists. But even when a KM metric is chosen for a larger sample, there is often a direct tie between input and output measures, making correlation difficult to establish, let alone causation. If profitability is part of both the input and output measures, of course they are correlated. The most advanced statistical techniques don’t establish anything more than what the researcher should already know from a cursory look at the logic of the study and the specifics of the variables. As a result, whether KM actually results in better organizational performance is still an open and much debated question in the field. One research approach that can get around this issue is the natural experiment. Pioneered by Nobel winner David Card and others, the natural experiment uses two measurements with a clear, consequential event separating the two—minimizing the impact of samples that might otherwise be connected contemporaneously. The event, such as a change in law, provides a change in circumstances delinking the measures. Whether structured as a pre/post experiment (measuring before or after the intervening event) or control/experimental group experiment (one group exposed to the event, the other not), the outcome can provide convincing results and can even suggest causation. This paper will cover our work with natural experiments in relation to KM and performance outcomes for merger and acquisition (M&A) activity. Can KM metrics before an M&A event predict the success of the event? Success can be defined by the change in financial performance after the event takes place.

The impact of knowledge characteristics on process performance: experimenting with the conversion perspective on knowledge transfer velocity

PurposeWith shorter product cycles and a growing number of knowledge-intensive business processes, time consumption is a highly relevant target factor in measuring the performance of contemporary business processes. This research aims to extend prior research on the effects of knowledge transfer velocity at the individual level by considering the effect of complexity, stickiness, competencies, and further demographic factors on knowledge-intensive business processes at the conversion-specific levels.Design/methodology/approachWe empirically assess the impact of situation-dependent knowledge transfer velocities on time consumption in teams and individuals. Further, we issue the demographic effect on this relationship. We study a sample of 178 experiments of project teams and individuals applying ordinary least squares (OLS) for regression analysis-based modeling.FindingsThe authors find that time consumed at knowledge transfers is negatively associated with the complexity of tasks. Moreover, competence among team members has a complementary effect on this relationship and stickiness retards knowledge transfers. Thus, while demographic factors urgently need to be considered for effective and speedy knowledge transfers, these influencing factors should be addressed on a conversion-specific basis so that some tasks are realized in teams best while others are not. Guidelines and interventions are derived to identify best task realization variants, so that process performance is improved by a new kind of process improvement method.Research limitations/implicationsThis study establishes empirically the importance of conversion-specific influence factors and demographic factors as drivers of high knowledge transfer velocities in teams and among individuals. The contribution connects the field of knowledge management to important streams in the wider business literature: process improvement, management of knowledge resources, design of information systems, etc. Whereas the model is highly bound to the experiment tasks, it has high explanatory power and high generalizability to other contexts.Practical implicationsTeam managers should take care to allow the optimal knowledge transfer situation within the team. This is particularly important when knowledge sharing is central, e.g. in product development and consulting processes. If this is not possible, interventions should be applied to the individual knowledge transfer situation to improve knowledge transfers among team members.Social implicationsFaster and more effective knowledge transfers improve the performance of both commercial and non-commercial organizations. As nowadays, the individual is faced with time pressure to finalize tasks, the deliberated increase of knowledge transfer velocity is a core capability to realize this goal. Quantitative knowledge transfer models result in more reliable predictions about the duration of knowledge transfers. These allow the target-oriented modification of knowledge transfer situations so that processes speed up, private firms are more competitive and public services are faster to citizens.Originality/valueTime consumption is an increasingly relevant factor in contemporary business but so far not been explored in experiments at all. This study extends current knowledge by considering quantitative effects on knowledge velocity and improved knowledge transfers.

Presenting a Personal Knowledge Management Model of Self-Care and Experience in Individuals with Bipolar Disorder and Families: A Study Protocol

Background. Bipolar disorder is a chronic condition that necessitates lifelong medication, therapeutic interventions, and self-care. People with bipolar disorder and their families may have varied experiences regarding sleep management, stress, interpersonal relationships, and anger, which are frequently overlooked. In the current study, the knowledge acquired by patients with bipolar disorder and their families was evaluated. Then, an appropriate model for managing self-care knowledge among individuals with bipolar disorder was proposed. Methods. The current mixed-methods study was conducted in four stages. The first stage involved a systematic review and meta-synthesis study in the field of knowledge management in the healthcare system. The second stage involved assessing the self-care experiences of patients with bipolar disorder. In the third stage, the codes obtained from the previous stages were prioritized by experts using Delphi techniques. In the fourth stage, a researcher prepared, validated, and distributed a questionnaire among mental health service providers stages. Finally, the personal knowledge management model of self-care and experience in individuals with bipolar disorder and their families was presented. Conclusion. Almost half of patients with bipolar disorder do not adhere to their long-term treatment. Also, this disease requires patients to perform self-care activities in addition to drug therapy. So, the design and implementation of a knowledge management model for self-care and experience in people with bipolar disorder can be effective in improving their self-care behaviors and quality of life.

Knowledge Management: Any changes in the Research Agenda?

The concept of knowledge management formed at the end of the 20th century. At the same time, the vector of this concept is evolving due to the emergence of new business models, technologies, and the recognition of the “soft” components of success or the so-called “soft skills”, and changes in the strategies of organizations.The article is a systematic scientific review, the purpose of which is to identify the mainstream in the field of economics and knowledge management. The methodology of the article is based on a set of approaches, including the knowledgebased theory of the firm, the concepts of knowledge engineering, organizational learning, dynamic capabilities and knowledge transformation, etc., and the research methodology is based on taxonomic and cluster analysis of the most cited English-language publications using tools embedded in the VOSviewer software product. The information base consisted of articles for 2018–2024, selected according to the research topic and keywords “Knowledge Management”, and placed in the Dimensions database. As a result, we identified 6 clusters and formalized the directions of modern research in the field of knowledge management. In each cluster, a content analysis of the most cited articles was carried out. The research agenda is currently focused on two main issues: the impact of digitalization and digital technologies on the choice, generation and dissemination of knowledge in an organization; the impact of knowledge on innovation as a mediator of business performance, including its environmental and social aspects. In fact, a consensus has been found in understanding the basic postulates of the concept of knowledge management. However, the problem of finding the “good” metrics for assessing the knowledge of an organization and the impact of their level on business performance remains relevant. It is shown that among the theoretical frameworks in knowledge management, the most popular are knowledge engineering and knowledge-based theory of the firm. The results of the study will be useful to managers-practitioners and researchers in the development of effective knowledge management systems.

Doc‐KG: Unstructured documents to knowledge graph construction, identification and validation with Wikidata

AbstractThe exponential growth of textual data in the digital era underlines the pivotal role of Knowledge Graphs (KGs) in effectively storing, managing, and utilizing this vast reservoir of information. Despite the copious amounts of text available on the web, a significant portion remains unstructured, presenting a substantial barrier to the automatic construction and enrichment of KGs. To address this issue, we introduce an enhanced Doc‐KG model, a sophisticated approach designed to transform unstructured documents into structured knowledge by generating local KGs and mapping these to a target KG, such as Wikidata. Our model innovatively leverages syntactic information to extract entities and predicates efficiently, integrating them into triples with improved accuracy. Furthermore, the Doc‐KG model's performance surpasses existing methodologies by utilizing advanced algorithms for both the extraction of triples and their subsequent identification within Wikidata, employing Wikidata's Unified Resource Identifiers for precise mapping. This dual capability not only facilitates the construction of KGs directly from unstructured texts but also enhances the process of identifying triple mentions within Wikidata, marking a significant advancement in the domain. Our comprehensive evaluation, conducted using the renowned WebNLG benchmark dataset, reveals the Doc‐KG model's superior performance in triple extraction tasks, achieving an unprecedented accuracy rate of 86.64%. In the domain of triple identification, the model demonstrated exceptional efficacy by mapping 61.35% of the local KG to Wikidata, thereby contributing 38.65% of novel information for KG enrichment. A qualitative analysis based on a manually annotated dataset further confirms the model's excellence, outshining baseline methods in extracting high‐fidelity triples. This research embodies a novel contribution to the field of knowledge extraction and management, offering a robust framework for the semantic structuring of unstructured data and paving the way for the next generation of KGs.

The Practicing Degree by Basic Schools’ Principals in the North Region within the Green Line for Knowledge Management and its Relationship with Institutional Excellence

The study aimed to disclose the practicing degree among primary school principals in the North District within the Green Line for knowledge management and its relationship to the level of institutional excellence, through the use of the descriptive correlational metodology, and the questionnaire as a tool for collecting information after ensuring its validity and reliability, as it was applied to a simple random sample of (362) teachers. The main results of the study indicated a high degree of practice among primary school principals in the North District within the Green Line for knowledge management, and a high level of institutional excellence in those schools. The results also showed a positive a correlational relationship between the practice of knowledge management and the level of institutional excellence. The study recommended the involvement of experts in the field of knowledge management to train school cadres, and to deepen cooperation between the school and service recipients.

КОРПОРАТИВНЫЕ УНИВЕРСИТЕТЫ: ПРИОРИТЕТЫ УПРАВЛЕНИЯ, РЕШЕНИЯ, ПЕРСПЕКТИВЫ. ЧАСТЬ 1

The article presents an analytical review of the research of corporate universities as knowledge management institutions implementing strategies for the formation of intellectual capital based on the knowledge network, reveals the role of corporate universities in continuing professional education and training.
 The aim of the project is to systematize the theoretical results of relevant research, summarize the main conceptual solutions in the field of knowledge management, identify key priorities and promising strategies of corporate universities in Russia, China and other countries in this area.
 The main task is to determine the role of corporate universities in the implementation of the strategy of continuing education, in improving the quality of professional education and the formation of corporate culture within the framework of a comparative analysis of specific cases of knowledge management in corporate universities.
 Improving the quality of vocational education and solving the problems of continuing education is largely associated with the development of modern corporate universities and improving the quality of knowledge management.
 One of the advantages of corporate universities is their potential in ensuring the integration of corporate needs into higher education. In this regard, the role of knowledge management 
 is increasing as a way to implement the educational strategy of a corporate university, which involves achieving the goals of the organization by increasing intellectual capital as a decisive factor in the development of innovative systems.
 The tendency of corporate universities to go beyond the function of continuous learning as an additional component is revealed, in such a way that the function of continuous learning plays an increasingly important role in ensuring the development of organizations and institutions.
 The formation of a theoretical basis for the study of strategies of corporate universities in various countries in the field of knowledge management based on their comparative analysis 
 is becoming in demand.
 An analytical review of the scientific literature confirms the gradual formation of a special conceptual framework for knowledge management research in corporate universities around 
 the world.
 Methodology. The principles of the methodology of comparative analysis were used, qualitative analysis and theoretical generalization were carried out.

Performance study of knowledge integration in marketing-oriented small and medium enterprises

Purpose: This study aims to examine the impact of the knowledge fermentation field on the knowledge integration performance of marketing-oriented SMEs. This research will help develop more useful market policies for company management. Design/Methodology/Approach: This research focuses on marketing-oriented SMEs, conducting a survey among 700 employees from 421 such enterprises. The collected data were analyzed to understand the influence of the knowledge fermentation field on the knowledge integration performance of these enterprises.
 Findings: Knowledge management plays a crucial role in marketing-oriented SMEs especially in terms of knowledge integration. Effective knowledge management strategies significantly enhance the market adaptability and innovation capabilities of these enterprises.
 Conclusion: The knowledge fermentation field in marketing-oriented SMEs positively impacts the enterprise's knowledge integration performance. The relationship between the field of knowledge fermentation and the performance of knowledge integration in marketing-oriented SMEs is moderated by the knowledge spiral fermentation system.
 Research Limitations and Implications: The study primarily targets marketing-oriented SMEs in a specific region and may not be entirely applicable to other regions or different types of enterprises. The influence of temporal variations on business knowledge integration performance may not have been properly taken into account during data collection.
 Practical Implications: This study provides businesses with an effective tool for developing and comprehending knowledge creation and innovation in the spiral fermentation system model of the knowledge ecosystem in small and medium-sized marketing companies. It fosters a healthier development path for the knowledge ecosystem in these enterprises.
 Contribution to the Literature: This study proposes a new theoretical framework in the field of knowledge management for marketing-oriented SMEs. It offers new perspectives and theoretical support for understanding and enhancing knowledge management practices in SMEs by integrating the concepts of the knowledge ecosystem and knowledge integration performance.

The Influence of Knowledge Management and Motivation on Job Satisfaction and Employee Performance in the Population and Civil Registration Office of DKI Jakarta Province

This study aims to analyze the influence of Knowledge Management (KM) and motivation on employee job satisfaction and performance at the Population and Civil Registration Office of DKI Jakarta Province. The analytical method used is Partial Least Squares (PLS), a statistical approach capable of handling complex structural models with relatively small samples. Data collection method through a survey of 150 employees randomly selected from various work units at the Population and Civil Registration Office of DKI Jakarta Province. Using the Partial Least Squares (PLS) approach to test the relationships between variables, the survey instrument used has been validated and its reliability tested before distribution. The results of the analysis indicate that there is a positive and significant influence of Knowledge Management (KM) on employee motivation. Additionally, motivation also has a positive and significant effect on employee job satisfaction and performance. However, the direct influence of Knowledge Management (KM) on job satisfaction is not significant. The analysis also shows that there is a positive and significant indirect influence of Knowledge Management (KM) on employee performance through motivation. These findings provide practical implications for management at the Population and Civil Registration Office of DKI Jakarta Province in managing Knowledge Management (KM) and motivating employees to enhance their job satisfaction and performance. This study also contributes to the literature in the field of human resource management and Knowledge Management.

Perceived climate of Cha-xu and trust on knowledge sharing: a moderated mediation model

PurposeThis study aims to identify an antecedent that hinders knowledge sharing, namely, the perceived climate of Cha-xu. Based on the social exchange perspective, the authors propose a theoretical model that links the perceived climate of Cha-xu to employee knowledge sharing. This model focuses on the mediating role of two types of trust (vertical and horizontal trust) and the moderating role of task interdependence in influencing the mediation.Design/methodology/approachUsing a sample of 509 Chinese employees, this study carried out a survey on an online platform. This study developed a structural equation model and tested the moderated mediation hypothesis by using Mplus 8.0.FindingsThe results showed that two types of trust act as mediators in the relationship between the perceived climate of Cha-xu and knowledge-sharing processes. The mediating effect of horizontal trust is stronger. Most significantly, findings show that this mediated relationship is contingent on the level of task interdependence.Originality/valueThis paper provides evidence for distinguishing vertical trust and horizontal trust in the field of knowledge management. From a managerial perspective, this study identifies traditional cultural factors for hindering knowledge-sharing processes within Chinese organizations.

The influence of supervisor bottom-line mentality on knowledge territorial behavior and knowledge sabotage behavior

PurposeBased on social cognitive theory, this study aims to explore the influence of supervisor bottom-line mentality (SBLM) on employee knowledge behavior (knowledge territorial behavior and knowledge sabotage behavior). The study first investigates the role of an ethical decision-making mechanism (moral disengagement) in mediating this relationship. In addition, it considers the possible boundary conditions to supplement research on the influence of SBLM in the knowledge management field.Design/methodology/approachThe authors collected 256 data points from employees across three stages using convenience sampling. The authors then tested the proposed hypothesis using hierarchical regression and bootstrap methods.FindingsThe results demonstrated that SBLM promotes employees’ moral disengagement, leading to more knowledge territorial behavior and knowledge sabotage behavior. Furthermore, high power distance orientation among employees exacerbates the ill effects of SBLM according to the first stage of a moderated mediation model. Employees with such an orientation are more likely to respond to a SBLM by exhibiting a higher level of moral disengagement, thus increasing their knowledge territorial behavior and knowledge sabotage behavior.Originality/valueResearch on the influence of SBLM in the knowledge management field is limited. This study not only clarifies the relationships between SBLM and two types of knowledge behavior (knowledge territorial behavior and knowledge sabotage behavior) but also enriches the research on the antecedents of these two types of knowledge behavior.

Knowledge management positioning in the information science era: Bibliometric analysis for the time frame from 2000-2023

INTRODUCTION: To navigate the field of knowledge management (KM) for effective performance in data science, business intelligence, and database systems, all stakeholders, including academicians and professionals, must be informed of the recent state of practice and theory in KM. A detailed bibliometric study of publications can help with this problem by giving a comprehensive picture of the publications' trends and progression. From 2000 to 2023 OBJECTIVES: To examine the pattern of publication in the area of knowledge management. METHODS: Two methodologies are employed to examine and interpret the bibliometric data acquired from the Scopus database. Citation and publication building evaluations were performed to gauge the emergence of the field of knowledge management, and secondly, VOS viewer software was used to simulate the projection of knowledge management grounded on bibliographic coupling (BC), co-citation, and co-occurrence (CC). RESULTS: The citation and publication structures indicate a steady improvement in the findings..

A Proposed Model for Implementing Knowledge Management Training in Automotive After-Sales Service Companies

The present study aims to propose a model for knowledge management training in ISACO automotive after-sales service companies. The research method is applied in terms of objectives and exploratory mixed-method (qualitative-quantitative) in terms of data. In the qualitative dimension, it is a self-emerging grounded theory, and in the quantitative dimension, it is a cross-sectional survey. The research field includes several experts (individuals introduced by professors, holding a PhD and conducting research in the field of knowledge management) in this domain, and in the quantitative section, all company employees (holding a bachelor's degree or higher and familiar with knowledge management) totaling 140 people. The sampling method in the qualitative section was purposive and snowball sampling, with 18 experts selected, reaching theoretical saturation at the 15th expert. In the quantitative section, based on the Morgan formula for sample size determination, 106 people were selected as the sample size. In the present study, after open and axial coding, the measurement tool was developed in the form of a questionnaire, which was sent to the experts for selective coding and validation. Consequently, a researcher-made questionnaire was designed and distributed randomly among the stratified sample. The collected data were analyzed using descriptive and inferential statistics, and finally, a model consisting of 7 dimensions, 26 components, and 138 indicators was identified. The identified dimensions, within a homogeneous structure, support the constructs of the proposed knowledge management training model in automotive after-sales service companies. According to this model, companies in this industry can progress toward the enhancement of knowledge management training. The proposed model can be used as a framework for organizations to define improvement and development actions.

Knowledge management practices in Russian educational institutions

Goal: the aim of this study is to analyze the practices of knowledge management in Russian educational institutions and compare the obtained results with foreign practices. Metodology: the systematic analysis of literature and the quantitative survey of respondents of Russian educational institutions were carried out. The content of 57 scientific articles was analyzed; 74 unique knowledge management practices were identified and grouped for the survey. Based on the responses of 120 heads of administrative divisions of educational organizations, redistribution of the identified practices was carried out in the key areas of application, thereby forming a different set of practices from foreign countries. Findings: the analysis and systematization of secondary sources of information revealed a set of knowledge management practices in Russian educational institutions that differ from the foreign practices. The descriptive research and literature review identified the mostly used knowledge management practices in Russia. Originality and contribution of the authors: the work contributes to the field of knowledge management by proposing the differences between foreign and Russian knowledge management practices, as well as supplementing and modifying the existing set of practices in the context of educational organizations.

PREDICTIVE ANALYTICS IN HUMAN RESOURCES USING MACHINE LEARNING AND DATA MINING

Human resource management information systems (HRIS) are rapidly evolving as a result of today's technologies and global technological developments. With the digitalization of businesses, it is widely used in predictive applications in human resources (HR) and HRIS. HR and HRIS, better managing human resources data and making more accurate and reliable decisions are of critical importance for businesses. In this field, data mining and machine learning approaches are used to reveal meaningful relationships and trends between data in management decisions through predictive analysis. Both approaches are very important in the field of HR and are very effective for businesses to transform data sets into useful information. It helps businesses understand trends that can lead to more accurate and reliable business decisions by using analytical capabilities. Within the scope of this study, research was conducted on the use of the HRIS system with white-collar employees of a company in the automotive sector in Bursa. The cost, time saving and strategic impact of the human resources information system on the company and information technology infrastructure, its differences and relationships according to the department worked, age, gender and education level were investigated through statistics and data mining. Knime and SPSS Statistics programs, which are machine learning tools, were used in the research. HRIS results were evaluated and suggestions were made for future planning.

Actualization of cyber resilience and historical origins of the concept of "resilience"

In this article, cyber resilience is defined as the ability to withstand external shocks caused by cyber risks, recover from them, and adapt to them. The importance of building a cyber resilience system in modern conditions is emphasized and examples of emergency situations of cyberattacks are given. The need to ensure cyber resilience at facilities and institutions is considered, different types of threats aimed at different systems, as well as the consequences of their negative impact are highlighted.
 It is noted that resilience and risk management, although interrelated, are still different. Risk management involves quantitative risk assessment, which forms a decision on the most appropriate strategy for responding to them. Resilience is important when risk is incalculable, when hazardous conditions are a complete surprise, or when analytical risk parameters have proven ineffective.
 It is emphasized that at a fundamental level, there are certain disagreements about the true meaning of resilience: for some, it implies the ability of a system to withstand a shock and return to its initial state, while for others it is an evolutionary process leading to adaptation and a new state of balance.
 Resilience has a long and rich history in various fields of scientific knowledge, including ecology, psychology, and disaster management. One of its main advantages is that it allows complex systems to prepare for adverse events and continue to operate under extraordinary conditions. It is concluded that the "prevent and protect” paradigm, which is still dominant today, is insufficient, and that risk management tools need to be developed in the direction of cyber resilience.