Search results

Our study aims to focus on the application of knowledge mapping to provide pedagogically-structured learners' competences.

We conducted an experiment examined the associations between the pedagogical quality of students’ pedagogically-informed knowledge (PIK) maps, class assignment scores and perceptions of PIK mapping’s uses.

The results showed that higher assignment scores were significantly predicted by higher quality PIK maps, ratings for PIK mapping were significantly higher than other mappings, and the learners’ experience of PIK mapping led to a significant change of attitude towards mapping as a learning activity and to a positive opinion of the value of PIK mapping in particular. Interestingly, there was no significant relation between learners’ opinion ratings of the uses of PIK mapping in learning and their assignment scores.

Questions remain on the generalizability of the findings, and on the features of a PIK map which are particularly useful to a learner. This study investigated the value of PIK mapping in the context of a practical class on the building of simple DIY (do-it-yourself) holographic projectors; it may be thought that the applied nature of the topic was more suited to the PIK mapping of learner competences and intended learning outcomes than a more theoretic classroom topic on holography. A future study is planned to address this issue.

The identification of network user relationship in Fancircle contributes to quantifying the violence index of user text, mining the internal correlation of network behaviors among users, which provides necessary data support for the construction of knowledge graph.

A correlation identification method based on sentiment analysis (CRDM-SA) is put forward by extracting user semantic information, as well as introducing violent sentiment membership. To be specific, the topic of the implementation of topology mapping in the community can be obtained based on self-built field of violent sentiment dictionary (VSD) by extracting user text information. Afterward, the violence index of the user text is calculated to quantify the fuzzy sentiment representation between the user and the topic. Finally, the multi-granularity violence association rules mining of user text is realized by constructing violence fuzzy concept lattice.

It is helpful to reveal the internal relationship of online violence under complex network environment. In that case, the sentiment dependence of users can be characterized from a granular perspective.

The membership degree of violent sentiment into user relationship recognition in Fancircle community is introduced, and a text sentiment association recognition method based on VSD is proposed. By calculating the value of violent sentiment in the user text, the annotation of violent sentiment in the topic dimension of the text is achieved, and the partial order relation between fuzzy concepts of violence under the effective confidence threshold is utilized to obtain the association relation.

This paper aims to map the research on management accounting (MA), clarifying its current role and identifying gaps and opportunities for future research.

In this paper, 784 papers were reviewed for the 1958–2019 period, published in 220 scientific journals indexed on Clarivate Analytics’ Web of Science (Science Citation Index Expanded [SCI-EXPANDED] and Social Sciences Citation Index [SSCI]). In the process, content analysis, regression analysis and bibliometric analysis were used.

The most relevant journals, authors and topics in MA, along with trends and patterns in the literature, were identified. Seven clusters that represent the overall thematic research structure of the MA field were also identified. This study shows that MA is becoming a multidimensional management decision-support instrument covering all organizational dimensions. As such, the research on MA is following the recent concerns with the sustainable development and digitalization of business processes.

Based on the findings of this research study, theoretical and practical implications for MA researchers were provided. These findings could also be useful to industry practitioners to improve their knowledge of emerging trends in MA practices, strategies and concepts.

Based on bibliometric and content analysis, a framework that shows an organizational, market and social context for the evolution of MA over the past 60 years was provided. It highlights the dynamics of MA alignment with organizational and external environment changes. Future research opportunities and implications for researchers and practitioners were also identified.

The purpose of this article is to (1) map the most important topics in the domain of sustainable business practices for entrepreneurial firms in emerging countries, (2) identify important terms in the various dimensions of sustainability in business and (3) identify the important practices and prioritize the practices.

This study has adopted a unique methodology that combines state-of-art scientometric analysis with the fuzzy nominal group technique (NGT) and fuzzy decision-making trial and evaluation laboratory (DEMATEL). Results obtained from the co-occurrence analysis in scientometrics were further mapped through NGT to obtain the list of the most important topics in the domain. The factors affecting sustainable business practices obtained through topic mapping were analyzed through fuzzy DEMATEL to obtain the cause-and-effect relation of variables.

The scale of firms, leadership, uncertainty, gender, country/location, education and tourism were found to be the factors affecting the sustainable business practices of entrepreneurial firms. The sustainable business practices for entrepreneurial firms were (1) innovation, (2) resilience, (3) policy, (4) business ethics and virtue ethics, (5) business model, (6) upcycling and value creation, (7) collaboration and (8) triple bottom line.

Policymakers in entrepreneurial firms, as well as other organizations, can implement the identified sustainable business practices to obtain optimum results and smooth functioning of the companies. The research framework obtained can be tested using exploratory methods.

Very few researchers have used the technique of scientometric analysis to identify the sustainable business practices of entrepreneurial firms, and to the best of the knowledge of the authors, no earlier researcher has attempted to use the technique of topic mapping, fuzzy NGT and fuzzy DEMATEL in combination.

The increasing urgency to address climate change in construction has made green construction (GC) and sustainability critical topics for academia and industry professionals. However, the volume of literature in this field has made it impractical to rely solely on traditional systematic evidence mapping methodologies.

This study employs machine learning (ML) techniques to analyze the extensive evidence-base on GC. Using both supervised and unsupervised ML, 5,462 relevant papers were filtered from 10,739 studies published from 2010 to 2022, retrieved from the Scopus and Web of Science databases.

Key themes in GC encompass green building materials, construction techniques, assessment methodologies and management practices. GC assessment and techniques were prominent, while management requires more research. The results from prevalence of topics and heatmaps revealed important patterns and interconnections, emphasizing the prominent role of materials as major contributors to the construction sector. Consistency of the results with VOSviewer analysis further validated the findings, demonstrating the robustness of the review approach.

Unlike other reviews focusing only on specific aspects of GC, use of ML techniques to review a large pool of literature provided a holistic understanding of the research landscape. It sets a precedent by demonstrating the effectiveness of ML techniques in addressing the challenge of analyzing a large body of literature. By showcasing the connections between various facets of GC and identifying research gaps, this research aids in guiding future initiatives in the field.

The purpose of this study is to conduct a systematic content review and bibliometric analysis of the current research trends, core concepts and knowledge mapping on the topic Islamic Banking and Finance (IBF) during Covid-19. Apart from highlighting the contributions of prolific authors, prominent institutions and countries, a comprehensive review of a significant number of documents using co-citation and co-word analysis is carried out for the science mapping.

A data set of 125 papers was collected published in Scopus database during the period December, 2019 and January 5th, 2023. Yearly publications, most-cited papers and authors, active sources, affiliations and countries are highlighted with descriptive analysis. Knowledge structure of the topic was mapped with investigating the social, intellectual and conceptual structures of IBF research. Content analysis is carried out to uncover the underlying research clusters that shape the scientific knowledge structure of studies.

A diverse group of authors and institutions contribute to the growing body of knowledge on the topic. IBF is adopting new paradigms and frameworks to integrate FinTech, crowd funding and Islamic social finance to provide sustainable solutions in both crisis and normal periods. The research on IBF is classified in to three themes: “financial markets in Covid-19,” “modeling risk and market regimes” and “FinTech and Islamic social finance.”

This study collects data only from Scopus database. Future studies must include research articles from other databases such as, Web of Sciences.

This study highlights research gaps in the existing literature and provides directions for future research.

The present study is about generating metadata to enhance thematic transparency and facilitate research on interview collections at the Research Documentation Centre, Centre for Social Sciences (TK KDK) in Budapest. It explores the use of artificial intelligence (AI) in producing, managing and processing social science data and its potential to generate useful metadata to describe the contents of such archives on a large scale.

The authors combined manual and automated/semi-automated methods of metadata development and curation. The authors developed a suitable domain-oriented taxonomy to classify a large text corpus of semi-structured interviews. To this end, the authors adapted the European Language Social Science Thesaurus (ELSST) to produce a concise, hierarchical structure of topics relevant in social sciences. The authors identified and tested the most promising natural language processing (NLP) tools supporting the Hungarian language. The results of manual and machine coding will be presented in a user interface.

The study describes how an international social scientific taxonomy can be adapted to a specific local setting and tailored to be used by automated NLP tools. The authors show the potential and limitations of existing and new NLP methods for thematic assignment. The current possibilities of multi-label classification in social scientific metadata assignment are discussed, i.e. the problem of automated selection of relevant labels from a large pool.

Interview materials have not yet been used for building manually annotated training datasets for automated indexing of scientifically relevant topics in a data repository. Comparing various automated-indexing methods, this study shows a possible implementation of a researcher tool supporting custom visualizations and the faceted search of interview collections.

This systematic literature review aims to identify the main areas of study related to co-creation and innovation in Higher Education Institutions (HEIs), as well as the main external and internal stakeholders with whom co-creation is made.

The empirical approach is based on 258 articles selected from the Web of Science (WoS), Clarivate Analytics and Scopus, Elsevier databases, with analysis of titles, abstracts and keywords following a research protocol. VOS viewer and CitNetExplorer software were used, with the twin aim of identifying publications with a higher number of citations and designing maps of reference word co-occurrence.

The analysis led to three clusters being identified: Cluster 1. Management and transfer of knowledge from HEIs to companies; Cluster 2. Co-creation and innovation in HEIs through cooperation between universities and companies; and Cluster 3. Universities’ third mission and their role in developing entrepreneurship education. The results of the literature clusters analysis led to proposing a conceptual model of analysis.

Despite only employing two databases and the content analysis criteria, the three found clusters are linked, recognising the interplay between co-creation and innovation in HEIs, knowledge transfer to enterprises and the influence on HEIs' third goal.

This systematic literature review highlights and gives a picture of the state-of-the-art in co-creation and innovation in HEIs, as well as presenting a model of co-creation and innovation in HEIs that can contribute to reinforcing the University-Industry-Community ties.

This study can lead to a better knowledge of the issue of co-creation and innovation at HEIs, as well as a deeper analysis of the sorts of relationships between HEIs and their stakeholders, as well as its impact on surrounding areas and influence.

The research highlights the interaction between HEIs and their stakeholders on a basis of value co-creation and innovation, providing mutual benefits for all involved, as well as greater development and recognition of HEIs and their surrounding regions’ image andreputation. A future research agenda is also presented on the topic of co-creation and innovation in HEIs.

Due to the unknown location, size and timing of disasters, the rapid response required by humanitarian operations (HO) faces high uncertainty and limited time to raise funds. These harsh realities make HO challenging. This study aims to systematically capture the complex dynamic relationships between operations in humanitarian settings.

To achieve this goal, the authors undertook a systematic review of the extant academic literature linking HO to system dynamics (SD) simulation.

The research reviews 88 papers to propose a taxonomy of different topics covered in the literature; a framework represented through a causal loop diagram (CLD) to summarise the taxonomy, offering a view of operational activities and their linkages before and after disasters; and a research agenda for future research avenues.

As the authors provide an adequate representation of reality, the findings can help decision makers understand the problems faced in HO and make more effective decisions.

While other reviews on the application of SD in HO have focused on specific subjects, the current research presents a broad view, summarising the main results of a comprehensive CLD.

The purpose of this paper is to provide a comprehensive framework that identifies thematic clusters and their interconnections within Global Talent Management (GTM), global careers and talent management (TM).

In this paper, this study conducted a co-citation analysis using bibliographic data to unveil the intellectual connections and relationships among thematic articles related to GTM sourced from the Web of Science.

This review highlights three key research themes: experiences working abroad, TM approaches and the complex nature of GTM as a living system.

The main limitation of this research is the sample itself. Content analysis based on the co-citation method resulted in some more recent releases being omitted.

The practical implications of the paper include providing a structured framework for understanding the complexities of GTM.

Research into the academic literature in this area is divided into various clusters, empirically demonstrating how GTM and global mobility are intertwined, revealing the need for us to more thoroughly comprehend the social ramifications of GTM practices and activities and the need to further analyse the influencing social aspects in a GTM strategy, like diversity, increased mobility and virtual reality.

The analysis revealed the emergence of three distinct thematic groups: (1) global work experiences, (2) TM approaches and (3) GTM.