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Sharing information security best practices between experts via knowledge management systems is valuable for improving information security practices, exchanging expertise, mitigating security risks, spreading knowledge, reducing costs and saving efforts. The purpose of this paper is developing a conceptual model to enhance the transfer of information security best practices between professionals in virtual communities through a Web-based knowledge management system to exchange their successful experience in handling different information security situations.

The model is validated by surveying 17 experts’ reviews on the correctness of the model’s structure and its related components through applying deep rich peer debriefing to test suitability. Quantitative data has been collected to achieve confirmatory results.

The resulting model incorporates five main components that support the formal mechanism for the acquisition and dissemination of knowledge: identification, classification, storage, validation and sharing. The success of knowledge sharing is highly dependent on the active collaboration of community members and highly influenced by motivation. Validating transferred knowledge is vital for ensuring the credibility of the system.

To the best of the author’s knowledge, this paper is one of the first to highlight the role of integrating knowledge management to enhance the effective share and reuse of information security best practices knowledge. The research results can support researchers investigating the topic and generate trustworthy literature to guide information security virtual community developers.

This paper aims to develop a model for selecting project team members. In this model, while knowledge sharing among individuals is maximized, the project costs and the workload balance among employees are also optimized.

The problem of project team formation is formulated as a fuzzy multi-objective 0-1 integer programming model. Afterward, to deal with uncertainty in the decision-making on the candidates’ abilities and the project requirements, the fuzzy multi-objective chance-constrained programming approach is adopted. Finally, by combining the non-dominated sorting genetic algorithm II and the fuzzy simulation algorithms, a method is proposed to solve the problem.

The computational results of the proposed model in a case study of project team formation in a large Iranian company from the shipbuilding industry evidently demonstrated its effectiveness in providing Pareto-optimal solutions for the team composition.

Seemingly for the first time, this paper develops a model to optimize knowledge sharing and improve the project efficiency through the selection of appropriate project team members.

The topic of organizational learning is populated with many theories and models; many relate to the enduring organizational learning framework consisting of knowledge acquisition, knowledge dissemination, and knowledge use. However, most of the research either emphasizes structural knowledge acquisition and dissemination as a composite construct, or focuses solely on the structural aspect of knowledge acquisition and dissemination. The primary objective of this study is to develop and test a model of organizational learning that incorporates both structural and informal knowledge acquisition and dissemination and as separate processes. The predictors of these processes are also proposed

A model of organizational learning that incorporates both structural and informal knowledge acquisition and dissemination constructs, along with three predictors of these organizational learning constructs were developed and quantitatively tested.

An inference to the research questions and hypotheses suggests that informal knowledge acquisition and dissemination have significant paths to market knowledge use, whereas structural knowledge acquisition and dissemination have, at best, a weak association with market knowledge use. Although the results were based on exploratory analysis, they provide tentative quantitative evidence that informal knowledge processes are at least as important as structural knowledge processes in market‐based organizational learning.

While the hypothesized model did not satisfy the goodness‐of‐fit tests, data‐driven exploratory analysis helped to refine two separate structural and informal models for future testing. The statistical explanation provided and procedures used to remedy the non‐fit issues should help future researchers to deal with structural equation‐modeling issues when similar non‐fit problems arise.

As economies move into the information age and post‐industrial era, information and knowledge become important resources to organizations. The article sets out to discuss the role and contribution of business process modeling (BPM) in the knowledge management initiative and in the management of company‐specific knowledge.

The authors consider BPM as a tool for knowledge management that allows the transformation of informal knowledge into formal knowledge and facilitates its externalization and sharing. The article starts with the brief introduction of the theoretical background of business process modeling and its basic concepts, and also presents definitions and concepts of major knowledge categories, knowledge processes and knowledge resources, as have been given by different authors in the knowledge management (KM) domain. These definitions are used as a basis for the knowledge category model and knowledge process model proposed by the authors.

The article presents findings of the mapping process of the BPM concepts into the knowledge life‐cycle model, proposed by Nonaka and Takeuchi and knowledge categories defined by different authors. During mapping, the authors experienced a lack of explicit and widely accepted definitions of knowledge categories and knowledge processes in respect of all knowledge features.

The article emphasizes an important differentiation between various categories of knowledge, identified in the BPM process, as a basis for the business process‐related knowledge categorization and identification of key knowledge processes. The article also presents the theoretical framework, which gives an account of how and when business process models capture and allow the sharing of knowledge. The framework identifies key knowledge categories, stages in knowledge transformation, and activities in this process.

This study aims to focus on a particular type of intra-organizational knowledge sharing that is referred to as peer knowledge sharing. This paper examines how peer knowledge sharing impacts firms’ financial and innovation performance, and the mechanism through which such a relationship is realized. The study also evaluates the extent to which leadership support acts as a key antecedent to peer knowledge sharing.

Drawing on social capital theory and a knowledge-based view of firms, a theoretical model and related hypotheses are presented for testing. A survey design methodology is used to collect data and test the model. Structural equation modeling is used to test the hypothesized relationships based on data collected from 330 knowledge workers in various service-based organizations in Turkey.

The results indicate that the extent of employees’ engagement in knowledge sharing behavior with their peers and their managers’ leadership support exert a positive impact on organizations’ knowledge management success, which, in turn, can affect organizations’ innovation performance positively and, subsequently, their financial performance. Leadership support of the immediate manager is found to be an important factor that contributes to the respondent’s peer knowledge sharing behavior. The proposed model’s invariance testing between male and female respondents revealed that peer knowledge sharing’s contribution to knowledge management success may be different in the two groups.

This study contributes to extant research on knowledge sharing by specifically focusing on peer knowledge sharing and reinforcing leadership support’s importance on knowledge sharing. The study also highlights the importance of knowledge management success as an important mediator necessary for linking individual knowledge management behaviors, such as peer knowledge sharing, with organizational performance.

Knowledge sharing is a topic of continuing interest for organizational researchers, yet limited empirical research has been conducted that links individual-level, intra-organizational knowledge sharing to organizational performance. This study examines this linkage and provides empirical support for this relationship, while simultaneously pointing to an important type of knowledge sharing that occurs within organizations, referred to as peer knowledge sharing.

In the age of knowledge explosion, modern technology facilitates the acquisition, organization and effective dissemination of information to support academic research. To achieve long-term educational goals, integrating digital resources into a knowledge management model (KMM) has become a necessary prerequisite for university management. The proposed KMM aims to combine resources and technology to facilitate resource management, navigation and cross-database search for advanced research.

The published literature on digital resource integration was reviewed, and the status of resource organization was discussed with experts to compile research instruments together with the perspectives of serving professionals in universities. The data obtained was systematically processed to develop an integrated resource KMM. Data volume measurement was done with the SPSS software and AMOS was used for path analysis and modeling. After the conceptual model was developed, many assumptions were associated with it, and the software was run on the data set to validate the proposed theoretical model.

Library resources with four components (digital resources, information technology, financial planning and service promotion) have been successfully integrated into the knowledge management framework to organize resources and provide academic services for researchers. In addition to the organization of digital resources, the two components of knowledge management, such as the explicit knowledge of its technology-oriented nature and the tacit knowledge of its human-centered positions, remained useful to strengthen the integration process.

With the development of digital technology and the internet, information authentication, access and dissemination have become a complex task for information centers. As an integral part of modern digital libraries, the expansion of digital collections requires proper accessibility organization. Owing to the increasing number of digital resources, organization and management require thorough research and appropriate integration mechanisms. This integrated KMM helps to organize heterogeneous information resources and databases in libraries for long-term academic tasks.

Based on literature studies and discussions with academic experts, integration problems were identified, and raw data were obtained from the library management to find a solution. It is unique research owing to a lack of original work and extensive international literature on resource integration in connection with KMMs. This study has innovative findings that can add value to world literature.

This paper presents a new solution for conceptually modeling the training‐domain knowledge of intelligent computerassisted instructional (ICAI) systems. Various cognitive demands from learners impose various modalities of presenting and structuring the knowledge to be taught. This paper is presenting a theoretical framework allowing to develop coherent, flexible models for the training‐domain knowledge of an ICAI system. A case study and an authoring‐system are also presented, in order to describe the main features of the modeling methods. This new approach in ICAI systems’ domain‐knowledge structuring and representation can offer a solution to the problem of adapting the instructional system interaction to users with different learning styles and needs.

The purpose of this paper is to develop a model that can be used to assess the knowledge retention capabilities of an organisation, and suggest opportunities for improvement. A model to fulfil this aim is developed and validated on a construction engineering consultancy.

A knowledge retention model was developed drawing on a thorough review of the literature. The developed retention model was validated through a case of a construction engineering consultancy. Semi‐structured interviews were used to elicit relevant information during the case study.

A four‐stage knowledge retention process has been presented. These four steps are socialisation, codification, knowledge construction, and knowledge retrieval. The paper also describes four levels of maturity for the knowledge retention model. The first level demonstrated the extent of knowledge sharing in the organisation, the second level measured the extent of knowledge shared being documented, the third level measured the effectiveness of storage of documented knowledge, and the last level was a measure of ease of accessibility and retrieval of the knowledge. A four‐level indicator of maturity of the knowledge retention process has been documented. For the case study analysed in this research, the maturity of knowledge retention was noted as being between two and three.

The model developed only captures knowledge that can be converted into an explicit form. The authors accept that there would be some tacit knowledge that cannot be effectively codified in explicit form, and such knowledge might not be captured using the model.

The paper has developed a model that can be used to measure the knowledge retention in an organisation. Although the model has been applied to a construction industry, it can easily be modified vis‐à‐vis other sectors.

In recent years, knowledge graph completion has gained increasing research focus and shown significant improvements. However, most existing models only use the structures of knowledge graph triples when obtaining the entity and relationship representations. In contrast, the integration of the entity description and the knowledge graph network structure has been ignored. This paper aims to investigate how to leverage both the entity description and the network structure to enhance the knowledge graph completion with a high generalization ability among different datasets.

The authors propose an entity-description augmented knowledge graph completion model (EDA-KGC), which incorporates the entity description and network structure. It consists of three modules, i.e. representation initialization, deep interaction and reasoning. The representation initialization module utilizes entity descriptions to obtain the pre-trained representation of entities. The deep interaction module acquires the features of the deep interaction between entities and relationships. The reasoning component performs matrix manipulations with the deep interaction feature vector and entity representation matrix, thus obtaining the probability distribution of target entities. The authors conduct intensive experiments on the FB15K, WN18, FB15K-237 and WN18RR data sets to validate the effect of the proposed model.

The experiments demonstrate that the proposed model outperforms the traditional structure-based knowledge graph completion model and the entity-description-enhanced knowledge graph completion model. The experiments also suggest that the model has greater feasibility in different scenarios such as sparse data, dynamic entities and limited training epochs. The study shows that the integration of entity description and network structure can significantly increase the effect of the knowledge graph completion task.

The research has a significant reference for completing the missing information in the knowledge graph and improving the application effect of the knowledge graph in information retrieval, question answering and other fields.

This paper seeks to develop a model for risk management of knowledge loss in a project‐based organization in Iran.

This study uses a multi‐stage research approach. In the first stage, existing practices are examined to develop a model for risk management of knowledge loss. In the second stage, the model is evaluated by testing it in a case study. The methods integrated as the foundations of the Integrated KM and RM model are: the PMBOK risk management (RM) approach, the Fraunhofer IPK knowledge management (KM) model, and the TVA knowledge risk assessment framework.

The analytical approach includes a six‐step integrated model that manages the risk of critical knowledge in the case study. The results show that, after a year of implementing the model, the job positions facing knowledge loss were reduced by 88 percent.

The integrated KM and RM model can be used to assist the planning, establishment and evaluation of knowledge loss in projects. This helps to ensure that key issues regarding knowledge loss are covered during the planning and implementation phases of project management.

This study provides an integrated perspective of KM in project‐based organizations. It offers valuable guidelines that can help decision makers consider key issues during a risk assessment of knowledge factors in project management. Outputs of this model can prepare an extensive assessment report about the risk of knowledge loss in a project‐based organization with suggestions for preservation plans to mitigate its effects.