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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.

Collaborative research and development have remained a pertinent mechanism for conducting technological innovations. With the lens of knowledge-based view (KBV), this study aims to examine the role of changes in knowledge couplings and network cohesion to elevate innovation performance.

Data analysis has been performed on 53,459 patents through regression analysis with random effects. These independent and joint patents are extracted from Derwent Innovation Database.

Findings explicate that change in external existing or existing and new knowledge couplings have inverted U-shaped effects on a firm’s innovation performance. Changes in internal existing or existing and new knowledge couplings have direct positive effects on firm’s innovation performance. The moderation effect of network cohesion flattens the inverted U-shaped effect of external new and existing knowledge coupling, whereas it has no significant effect on external existing knowledge coupling. Network cohesion further elevates the effects of internal knowledge couplings – existing or existing and new.

This study theoretically contributes to KBV and innovation management literature by highlighting the scope of changes in internal and external knowledge couplings and subsequent output. Network cohesion flattens the curviness of changes in external new and existing knowledge couplings, which is a contribution to strategic management literature.

Organizations need to carefully manage changes in knowledge couplings and ensure their benefits (obtain new knowledge domain or new combination) outweigh liabilities (damages to organizational routines or increase in collaboration costs). Managers must consider four kinds of knowledge coupling changes along with developing network cohesion as an R&D strategy.

This study is one of its types to flatten the curve through network cohesion. This study divided the changes in knowledge coupling into four types and two dimensions; external existing and new and existing knowledge couplings and internal existing and new and existing knowledge couplings.

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.

The purpose of this paper is to present various knowledge‐acquisition methods and to show how existing empirical research can be used for mapping between marketing problem domains and knowledge acquisition techniques. The key to doing this is to create a taxonomy of marketing problem domains.

This paper combines a thorough literature review with prima facie conceptualization to map a generic problem domain, and thereby provide guidance in the choice of knowledge‐acquisition technique for developers of expert systems in the field of marketing.

Recent empirical research in the field of expert systems shows that certain knowledge‐acquisition techniques are significantly more efficient than others for the extraction of certain types of knowledge within specific problem domains. It is found that protocol analysis, while fairly commonly used, is relatively inefficient for analytic problems. In the synthetic problem domain, interviewing proves to perform better for simple problems and worse for more difficult‐to‐model synthetic domains.

The findings suggest that it may be worth exploring some of the non‐traditional knowledge‐acquisition techniques when working on some types of applications. Further research could offer guidance in choosing the appropriate technique, with the aim of improving the quality, efficiency and development of the resulting system.

Designers of expert systems for marketing should consider interviewing and card sorting as the main means of knowledge acquisition for analytic problem domains, rather than protocol analysis as the main knowledge‐acquisition technique for analytic problem domains.

This paper is the first to suggest mapping between knowledge‐acquisition research and marketing problem domains.

The purpose of this paper is to shed light on the problematics of learning across knowledge boundaries in organizational settings. The paper specifically explores learning processes that emerge, when a new knowledge domain is introduced into an existing organizational practice with the aim of creating a new combined practice.

A case study was carried out as a “natural experiment” in an engineering consultancy, where emerging initiatives to integrate the newly acquired competencies into the existing practice were explored. A theoretical framework informed by selected perspectives on learning processes and boundary processes was applied on three illustrative vignettes to illuminate learning potentials and shortcomings in boundary processes.

In the engineering consultancy, it was found that while learning did occur in the consultancy organization, it remained discrete in ‘pockets’ of learning; mainly at an individual level, at project level or as domain-specific learning. Learning processes were intertwined with elements of domain-specific interests, power, managerial support, structural conditions, material and epistemic differences between knowledge domains.

The finding in this paper is based on a single case study: hence, the findings' generalizability may be limited.

The paper argues that learning across knowledge domains needs various forms of supporting initiatives and constant readiness to alter or counteract when an initiative's shortcomings appear or undesired learning loops arise.

The paper contributes to understanding the complexity of learning across knowledge boundaries in organizational settings.