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Previous studies have addressed the importance of knowledge base and its effect on innovation outputs. However, few studies have focused on the antecedents of dynamic changes of the organizational knowledge base. This study aims to shed light on the antecedents of dynamic change of the organizational knowledge base by examining how network centrality in an organization's collaboration network impacts this change and the moderating role of knowledge network cohesion.

The empirical setting of this study is the smartphone collaboration network. The authors selected patent data from the Derwent Innovation Database. A negative binomial model was used to test the hypotheses.

The results verified that network centrality has a positive effect on the change in coupling among existing knowledge domains and has an inverted U-shaped relationship with the coupling between new and existing knowledge domains. Furthermore, when local cohesion is high, network centrality has a stronger positive effect on the change in coupling among existing knowledge domains. Global cohesion moderates this process in such a way that when it is at a high level, the coupling between new and existing knowledge domains can benefit more from a moderate level of network centrality.

This study sheds light on the antecedents of dynamic change of the organizational knowledge base and links the literature on collaboration and knowledge networks by providing novel insights to match collaboration network centrality with knowledge network cohesion for successful improvement of the organizational knowledge base.

The purpose of this paper is to discuss and clarify a possible realist foundation of domain analysis and knowledge organization, and in this vein, investigate into how the concept of information is to be understood at a lower but necessary conceptual level in domain analysis.

The paper investigates into the foundation of domain analysis as formulated by Birger Hjørland, and develops a realist framework for domain analytical information and knowledge organization based on critical realism.

Information can meaningfully be considered as the prerequisite for domain analysis, and critical realism may provide for a realist ontological framework for domain analysis and knowledge organization.

The paper includes new insights into the foundation of information and domain analysis.

This study aims to illuminate the currently poorly understood inflow of knowledge originating from project managers across the value chain of construction projects. The primary purpose is to identify the domains of knowledge that project managers’ need to share in their management activities, the skills they need to develop in their sharing practices and how these relate to each other across different phases of a construction project.

Knowledge domains, skills and the relationships between them were identified following an inductive methodology, a combination of grounded theory and case study, and through the analysis of semi-structured interviews with 21 project managers and participants within a single construction project.

The outcome is a novel framework that theorizes the dynamic interplay between knowledge domains and the skills that facilitate knowledge sharing (KS) for successful project work throughout the construction project.

The combined effects of task heterogeneity, knowledge interdependencies and temporariness require paying increased attention to how knowledge domains and KS skills impact project performance. This paper addresses gaps in developing an integrative understanding of the nature of the domains of knowledge that need to be shared in a project context, the key skills contributing to KS and more importantly, how they evolve and are interpreted and reinterpreted throughout the project and assist KS practice in projects.

The conditions that domain analysis becomes an academic school of information science (IS) are mature. Domain analysis is one of the most important foundations of IS. The purpose of this paper is to analyze and discuss metatheoretical and theoretical issues in the domain analytic paradigm in IS.

This paper conducts a systematic review of representative publications of domain analysis. The analysis considered degree theses, journal articles, book chapters, conference papers and other materials.

Domain analysis maintains that community is the new focus of IS research. Although domain analysis centers on the domain and community, theoretical concerns on the social and individual dimensions of IS are inherent in it by its using sociology as its important approach and socio-cognitive viewpoint. For these reasons domain analysis can integrate social–community–individual levels of IS discipline as a whole. The role of subject knowledge in IS is discussed from the perspective of domain analysis. Realistic pragmatism that forms the philosophical foundation of domain analysis is argued and the implications of these theories to IS are presented.

The intellectual evolving landscape of domain analysis during a quarter century is comprehensively reviewed. Over the past twenty-five years, domain analysis has established its academic status in the international IS circle. Being an important metatheory, paradigm and methodology, domain analysis becomes the theoretical foundation of IS research. This paper assesses the current state of domain analysis and shows the contributions of domain analysis to IS. It also aims to inspire further exploration.

This paper aims to present a specific model and method for analyzing the knowledge domains and organization knowledge map. One of the functions of the organizational knowledge map is the possibility of extracting the risk of the organization's knowledge domains and thus the ability to define knowledge-based strategies in the organization. So far, various software tools have been designed to support the process of creating, analyzing knowledge domains and structure knowledge map. However, software companies have less detail and methodology of their software analysis and less research has been addressed.

This model calculates the risk of knowledge domains using the recursive algorithm approach, assuming there is one-way communication between the knowledge domains and using specific factors.

The prominence of this model is to calculate knowledge domains risk, dynamic updating of knowledge domains risk after any changes in knowledge domain risk in the organization's knowledge map. The model can also be used as a simulation model and prioritize corrective actions.

This is a recursive model that by assuming one-way relations among knowledge domain computes the risk of each domain knowledge by considering the risk of its related domains, relations among different domains and pre-requisites and post-requisites. This model has no limitation in determining the number of knots and communications. Despite of simplicity, it is too efficient and any organization can localize it based on its own needs.

The purpose of this paper is to present evidence of how different domains of knowledge (basic, experiential, emotional and innovative knowledge) relate to knowledge conversion processes (socialization, externalization, combination and internalization) in the firm.

Confirmatory principal component analyses were performed on knowledge domain and knowledge conversion variables. Path analyses, based on stepwise multiple regressions, were performed in order to determine the strength and directionality of the relationships between the four processes of knowledge conversion and the four knowledge domains.

The results indicate that knowledge based on experience impacts the conversion of tacit knowledge within an organization, leading to innovative knowledge and competitive advantage. Emotional knowledge impacts the knowledge conversion process similarly. Only basic knowledge impacts the explicit components of combination.

First, the results of this study are drawn from a fairly large sample in only one firm, and hence, one industry. Not all of the middle managers who participated in this study are equally familiar with knowledge creation and dissemination within their organization.

The results suggest that investing in basic training of employees and managers in order to reach a basal level of knowledge can act as a precursor to fuel other types of knowledge conversion as well as the innovative and experiential knowledge domains.

Past research has not examined how the domains of knowledge (the content) are related to the conversion of knowledge. In addition, little research in the area of knowledge conversion has taken place in a European setting. This paper addresses the deficits.

This study aims to discover the influence of researcher competence on University-Industry collaboration via researcher’s domain knowledge.

Quantitative data were collected via survey questionnaire by using purposive sampling technique from a total of 121 academicians from all five research universities in Malaysia. PLS-SEM is used to examine multiple structural relationships between the researcher competence, domain knowledge transfers and spillovers and university-industry collaboration.

Researcher’s competence serves as a success booster to initiate the collaborative endeavour, and the University-Industry collaboration is found to be substantially influenced by the domain knowledge transfers and spillovers.

The size of the sample in this study was however constrained by the characteristics and background of the targeted pool of respondents to be generalised to the population of all universities in Malaysia.

Researcher competence is found to be significant drive to the University-Industry collaboration formation through the development and deployment of domain knowledge transfers and spillovers. Thus, it requires the desire and need for continuous competence development for researchers, and a step change is called for individual principal investigators about extending their leadership across the field of studies and appearing as critical business partners in the University-Industry collaboration.

The paper contributes to the literature by empirically investigating the influence of researcher competence on the University-Industry collaboration via researcher’s domain knowledge. It attempts to show the researcher’s ability to leverage their competencies in increasing the collaborative endeavour in making out business opportunities, which will eventually influence the public university’s sustainability development. In addition, it proves the importance of researcher’s competence and domain knowledge within the entrepreneurial activities, which serves as the significant drivers to ensure successful University-Industry collaboration.

The purpose of this paper is to understand genomics scientists’ perceptions in data quality assurances based on their domain knowledge.

The study used a survey method to collect responses from 149 genomics scientists grouped by domain knowledge. They ranked the top-five quality criteria based on hypothetical curation scenarios. The results were compared using χ2 test.

Scientists with domain knowledge of biology, bioinformatics, and computational science did not reach a consensus in ranking data quality criteria. Findings showed that biologists cared more about curated data that can be concise and traceable. They were also concerned about skills dealing with information overloading. Computational scientists on the other hand value making curation understandable. They paid more attention to the specific skills for data wrangling.

This study takes a new approach in comparing the data quality perceptions for scientists across different domains of knowledge. Few studies have been able to synthesize models to interpret data quality perception across domains. The findings may help develop data quality assurance policies, training seminars, and maximize the efficiency of genome data management.

The purpose of this paper is to report on research that aims to make knowledge, and in particular know-how, more easily accessible to both academic and industrial communities, as well as to the general public. The paper proposes a novel approach to map out know-how information, so all knowledge stakeholders are able to contribute to the knowledge and expertise accumulation, as well as using that knowledge for research and applying expertise to address problems.

This research followed a design science approach in which mapping of the know-how information was done by the research team and then tested with graduate students. During this research, the mapping approach was continuously evaluated and refined, and mapping guidelines and a prototype tool were developed.

Following an evaluation with graduate students, it was found that the know-how maps produced were easy to follow, allowed continuous evolution, facilitated easy modification through provided modularity capabilities, further supported reasoning about know-how and overall provided adequate expressiveness. Furthermore, we applied the approach with various domains and found that it was a good fit for its purpose across different knowledge domains.

This paper argues that mapping out know-how within research and industry communities can further improve resource (knowledge) utilization, reduce the phenomena of “re-inventing the wheel” and further create linkage across communities.

With the qualities mentioned above, know-how maps can both ease and support the increase of access to expert knowledge to various communities, and thus, promote re-use and expansion of knowledge for various purposes. Having an explicit representation of know-how further encourages innovation, as knowledge from various domains can be mapped, searched and reasoned, and gaps can be identified and filled.

Strategy scholars have long argued that breakthrough innovation is generated by recombining knowledge from distant domains. Even if firms have the ability to access and absorb knowledge from distant domains, however, they may fail to pay attention to such knowledge because it is seemingly irrelevant to their tasks. We draw attention to this problem of knowledge relevance and develop a theoretical model to illuminate how ideas from seemingly irrelevant (i.e., peripheral) domains can generate breakthrough innovation through the cognitive process of analogical reasoning, as well as the conditions under which this is more likely to occur. We situate our theoretical model in the context of teams in order to develop insight into the microfoundations of knowledge recombination within firms. Our model reveals paradoxical requirements for teams that help to explain why breakthrough innovation is so difficult.