Changes in knowledge coupling and innovation performance: the moderation effect of network cohesion

Purpose 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. Design/methodology/approach 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 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. Research limitations/implications 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. Practical implications 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. Originality/value 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.

Development and Validation of Oral Health Knowledge, Attitude and Behavior Questionnaire among Indian Adults

Background and objectives: The Indian population faces numerous challenges to attain better oral hygiene due to a lack of oral health literacy. For the past 10 years, the prevalence of dental-related conditions in India has become a considerable problem in every state of India. A health-education-based oral health promotion strategy will be an ideal choice for the Indian population instead of endorsing conventional oral health promotion. The use of unsuitable tools to measure may lead to misleading and vague findings that might result in a flawed plan for cessation programs and deceitful effectiveness. Therefore, the research aimed to develop and validate an instrument that can assess the oral health knowledge, attitude and behavior (KAB) of adults in India. Materials and Methods: This study was carried among adults in India, who live in Chennai, Tamil Nadu. A questionnaire was fabricated and then validated using content, face, as well as construct. The knowledge domain was validated using item response theory analysis (IRT), whereas exploratory factor analysis (EFA) was used to validate the behavior domain and attitude. Results: Four principal sections, i.e., knowledge, attitude, demography and behavior, were used to fabricate a questionnaire following validation. Following analysis of item response theory on the knowledge domain, all analyzed items in the domain were within the ideal range of difficulty and discrimination. The Kaiser–Meyer–Olkin measure of sampling adequacy was 0.65 for the attitude and 0.66 for the behavior domain. A Bartlett’s test of sphericity was conducted and demonstrated that outcomes for both domains were highly significant (p < 0.001). The factor analysis resulted in three factors with a total of eight items in the attitude domain and three factors with a total of seven items in the behavior domain depicting satisfactory factor loading (>0.3). Across the three factors, i.e., knowledge, attitude and behavior, internal consistency reliability was tested using Cronbach’s alpha, and the values obtained were 0.67, 0.87, 0.67, and 0.88, respectively. Conclusions: The findings of this study that assessed validity and reliability showed that the developed questionnaire had an acceptable psychometric property for measuring oral health KAB among adults in India.

Visualizing the Knowledge Domain of Academic Mobility Research from 2010 to 2020: A Bibliometric Analysis Using CiteSpace

Academic mobility, given its importance in the dissemination of knowledge and globalization of research collaboration, has received growing attention over the past decades. Based on a bibliometric analysis of the literature on academic mobility (119) from 343 journal articles in Web of Science over the period of 2010 to 2020 with the use of CiteSpace, this paper outlines the research intellectual map, such as the most active contemporary institutions, journals, and popular regions/countries; dissects the network of categories and summarizes the emerging trends and future research opportunities for academic mobility. The results of the study are: (1) England is the most productive region followed by China and Netherlands in terms of publication; (2) Utrecht University, The Polytechnic University of Valencia, and Russian Academy of Science are the most productive institutions; (3) The publications are mainly in the subject categories of Education, Business and Economics, and Geography; (4) Gender, scientific practice, brain drain are the main keywords for discussion; and (5) Louise Ackers is the most influential author in this field and International Migration Journal is the most frequently cited journal over the past decade. Our paper contributes to the relevant body of literature by systematizing the literature on academic mobilities through CiteSpace, a visualized analytical tool for undertaking bibliometric analysis, providing valuable references for researchers and practitioners who want to further explore this knowledge area.

Mapping knowledge structure of artificial intelligence research in Bangladesh based on co-word analysis

Purpose: This article aims to map the knowledge structure of artificial intelligence (AI) in Bangladesh through detecting the interdisciplinarity and topic hotspots in the light of co-word analysis. Methodology: This study adopted bibliometric analysis of publications collected from the Web of Science (WoS) database. The WoS database was searched and 1557 publications were found. 1359 papers were selected for final analysis after eliminating duplicates. Co-occurrence words matrix, keyword clusters, hot topics were mapped using co-word analysis. The results were mapped, clustered and presented by VOSviewer.Results: The result showed a rapidly increasing publication trajectory with 12 sub-domain cluster under the AI knowledge domain in Bangladesh. It also identified that AI, machine learning, classification, neural network, deep learning, artificial neural network, convolutional neural network, support vector machine and data mining are hot topics during the period of studied time. However, the findings also suggest that many research areas in the research domain of AI of Bangladesh is still nascent.Limitation: VOSviewer often avoid having overlapping terms when multiple terms are positioned very close to each other. So, the overlapping terms remain invisible sometimes.Practical implications: This study may have potential usefulness in uncovering the AI research fields’ intellectual structure within a discipline and also to anticipate future innovation pathways of AI field in Bangladesh.Originality: Bibliometric methods to explore the research trend and growth of AI research field as a ‘knowledge base’ in Bangladesh is one of the first attempts.

Tax literacy: what does it mean?

Purpose This paper aims to identify the competency domains to be included in a conceptual framework for tax literacy. Design/methodology/approach Using a qualitative approach, this study expands on the current understanding of the competency areas of tax literacy. A dual-purpose literature review was, therefore, conducted. The literature review first provided the body of knowledge that underpinned the study and second, the key data concepts for the draft competency structure to determine whether there is consensus on an international (supra) level. The literature review was supported by an interactive qualitative analysis to further present the concept of tax literacy from the perspectives of various national stakeholders in an emerging economy. Accounting and public finance educators from a higher education institution, as well as financial advisers as representatives of a profession with a direct interest in tax-related matters, were considered. Findings Although a discipline lens seems to strongly influence the previous authors’ view of what tax literacy means, it was possible to identify certain tax literacy competency domains that should be included in a taxpayer education curriculum. These content domains consist first of a knowledge domain which includes disciplinary, interdisciplinary, epistemic and procedural knowledge components. Second, the skills domain should include components of cognitive and meta-cognitive, social and emotional, as well as physical and practice skills. Third, personal and societal attitudes and values represent the third domain. Fourth, transformative competencies such as value creation, taking responsibility and reconciliation attributes are important. Finally, core foundational competencies, such as numeracy and literacy should be in place. Practical implications The draft conceptual framework for tax literacy could serve as the foundation for the further development of a tax literacy measurement instrument, as well as tax education courses. Originality/value A more holistic conceptual framework for tax literacy, portraying the multidimensional nature of taxation, is presented in contrast to the limited one-dimensional position presented up to now.

Software Knowledge Entity Relation Extraction with Entity-Aware and Syntactic Dependency Structure Information

Software knowledge community contains a large scale of software knowledge entities with complex structure and rich semantic relations. Semantic relation extraction of software knowledge entities is a critical task for software knowledge graph construction, which has an important impact on knowledge graph based tasks such as software document generation and software expert recommendation. Due to the problems of entity sparsity, relation ambiguity, and the lack of annotated dataset in user-generated content of software knowledge community, it is difficult to apply existing methods of relation extraction in the software knowledge domain. To address these issues, we propose a novel software knowledge entity relation extraction model which incorporates entity-aware information with syntactic dependency information. Bidirectional Gated Recurrent Unit (Bi-GRU) and Graph Convolutional Networks (GCN) are used to learn the features of contextual semantic representation and syntactic dependency representation, respectively. To obtain more syntactic dependency information, a weight graph convolutional network based on Newton’s cooling law is constructed by calculating a weight adjacency matrix. Specifically, an entity-aware attention mechanism is proposed to integrate the entity information and syntactic dependency information to improve the prediction performance of the model. Experiments are conducted on a dataset which is constructed based on texts of the StackOverflow and show that the proposed model has better performance than the benchmark models.

Knowledge, Attitude, and Practice of Intranasal Corticosteroid in Allergic Rhinitis Patients: Development of a New Questionnaire

Objectives: The knowledge gap and attitude of allergic rhinitis (AR) patients using intranasal corticosteroid (INCS) led to the poor outcome of their disease. We aimed to develop and validate a new questionnaire to assess the knowledge, attitude, and practice (KAP) of AR patients that can be used to assess and understand the factors affecting compliance of INCS. Methods: The questionnaire comprised development and validation stages. A self-administered questionnaire was developed after a comprehensive literature review. It was subjected to content and face validity before a revised final version was drafted. Exploratory factor analysis was used to assess the validity of the questionnaire. Cronbach’s alpha was used to verify internal consistency. Results: The development phase resulted in a questionnaire consisting of 14 items. Explanatory factor analysis revealed four factors associated with KAP. The four factors were extracted, and 12 items were kept. The factors were attitude domain with four items (factor 1), practice domain with four items (factor 2), and knowledge domain with four items (factor 3 has two items, and factor 4 has two items). The Cronbach’s alpha of the four factors ranged from 0.614 to 0.809. The final questionnaire consists of 3 domains with 12 items (the knowledge domain with four questions; the attitude domain with four questions; the practice domain with four questions) and was valid and reliable. Conclusions: The newly developed questionnaire has adequate validity and reliability. It is a useful tool to improve the treatment of AR patients by understanding the factors affecting their compliance.