1,720,955 research outputs found
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Get PDFWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
L’adoption de l’industrie 4.0 dans le secteur textile : Cartographie des dynamiques scientifiques mondiales (2013–2025)
No full textIn a context of rapid industrial transformation and growing sustainability demands, Industry 4.0 has emerged as a key technological paradigm for the textile sector, historically characterized by labor intensity and low digitalization. Despite its potential for automation, flexibility, and traceability, adoption remains partial and uneven. This study addresses a major gap in the literature by providing a systematic and longitudinal mapping of the barriers to Industry 4.0 adoption in the global textile industry.
Using a quantitative bibliometric approach, 150 Scopus-indexed articles (2013–2025) were analyzed with Bibliometrix (R), Biblioshiny, and VOSviewer. The study combines performance analyses (output, citations, H-index) with structural analyses (co-occurrence, co-citation, and bibliographic coupling) to identify the field’s main themes, key contributors, and persistent barriers.
The results indicate an average annual growth rate of 24.6% and reveal four thematic clusters: (1) intelligent production technologies, (2) sustainability and circularity, (3) organizational adoption models, and (4) innovations in smart and functional textiles. The main obstacles are interconnected: high investment costs, lack of data science skills, limited interoperability, cybersecurity risks, and socio-technical resistance. The analysis also highlights geographic asymmetries, as Southern countries often produce knowledge that remains under-cited. Artificial intelligence emerges as a transversal enabler applied to predictive maintenance, simulation, automation, and adaptive management.
Overall, this study calls for a systemic reassessment of the barriers to adoption, integrating human, technical, and institutional dimensions. It offers a structured framework to guide the textile industry’s transition toward a smarter, more sustainable, and resilient model.
Classification JEL : O33, L67, M11, Q56
Paper type : Theoretical ResearchDans un contexte de transformation industrielle rapide et de quête de durabilité, l’Industrie 4.0 s’impose comme un paradigme technologique clé pour le secteur textile, historiquement marqué par une forte intensité de main-d’œuvre et une faible digitalisation. Malgré ses atouts en automatisation, flexibilité et traçabilité, son adoption demeure partielle et inégale. Cette recherche comble une lacune de la littérature en proposant une cartographie systématique et longitudinale des barrières à l’adoption des technologies 4.0 dans l’industrie textile mondiale.
En mobilisant une approche bibliométrique quantitative, 150 articles indexés dans Scopus (2013–2025) ont été analysés à l’aide des outils Bibliometrix (R), Biblioshiny et VOSviewer. L’étude combine des analyses de performance (production, citations, H-index) et de structure (co-occurrence, co-citation, couplage bibliographique) afin d’identifier les principaux thématiques, acteurs et freins du champ.
Les résultats révèlent une croissance annuelle moyenne de 24,6 % et une structuration en quatre clusters : (1) technologies de production intelligentes, (2) durabilité et circularité, (3) modèles organisationnels d’adoption et (4) innovations textiles et e-textiles. Les freins principaux apparaissent interconnectés : coûts d’investissement élevés, déficit de compétences en data science, interopérabilité limitée, cybersécurité et résistances sociotechniques. L’étude montre aussi une concentration géographique inégale, les pays du Sud produisant des connaissances souvent sous-citées. L’intelligence artificielle émerge comme un axe transversal appliqué à la maintenance prédictive, la simulation, l’automatisation et la gestion adaptative.
En conclusion, cette étude propose une lecture systémique des barrières et offre un cadre structurant pour une transition vers un modèle textile plus intelligent, durable et résilient.
JEL Classification : O33, L67, M11, Q56
Type du papier : Recherche Théoriqu
L’adoption de l’industrie 4.0 dans le secteur textile : Cartographie des dynamiques scientifiques mondiales (2013–2025)
No full textIn a context of rapid industrial transformation and growing sustainability demands, Industry 4.0 has emerged as a key technological paradigm for the textile sector, historically characterized by labor intensity and low digitalization. Despite its potential for automation, flexibility, and traceability, adoption remains partial and uneven. This study addresses a major gap in the literature by providing a systematic and longitudinal mapping of the barriers to Industry 4.0 adoption in the global textile industry.
Using a quantitative bibliometric approach, 150 Scopus-indexed articles (2013–2025) were analyzed with Bibliometrix (R), Biblioshiny, and VOSviewer. The study combines performance analyses (output, citations, H-index) with structural analyses (co-occurrence, co-citation, and bibliographic coupling) to identify the field’s main themes, key contributors, and persistent barriers.
The results indicate an average annual growth rate of 24.6% and reveal four thematic clusters: (1) intelligent production technologies, (2) sustainability and circularity, (3) organizational adoption models, and (4) innovations in smart and functional textiles. The main obstacles are interconnected: high investment costs, lack of data science skills, limited interoperability, cybersecurity risks, and socio-technical resistance. The analysis also highlights geographic asymmetries, as Southern countries often produce knowledge that remains under-cited. Artificial intelligence emerges as a transversal enabler applied to predictive maintenance, simulation, automation, and adaptive management.
Overall, this study calls for a systemic reassessment of the barriers to adoption, integrating human, technical, and institutional dimensions. It offers a structured framework to guide the textile industry’s transition toward a smarter, more sustainable, and resilient model.
Classification JEL : O33, L67, M11, Q56
Paper type : Theoretical ResearchDans un contexte de transformation industrielle rapide et de quête de durabilité, l’Industrie 4.0 s’impose comme un paradigme technologique clé pour le secteur textile, historiquement marqué par une forte intensité de main-d’œuvre et une faible digitalisation. Malgré ses atouts en automatisation, flexibilité et traçabilité, son adoption demeure partielle et inégale. Cette recherche comble une lacune de la littérature en proposant une cartographie systématique et longitudinale des barrières à l’adoption des technologies 4.0 dans l’industrie textile mondiale.
En mobilisant une approche bibliométrique quantitative, 150 articles indexés dans Scopus (2013–2025) ont été analysés à l’aide des outils Bibliometrix (R), Biblioshiny et VOSviewer. L’étude combine des analyses de performance (production, citations, H-index) et de structure (co-occurrence, co-citation, couplage bibliographique) afin d’identifier les principaux thématiques, acteurs et freins du champ.
Les résultats révèlent une croissance annuelle moyenne de 24,6 % et une structuration en quatre clusters : (1) technologies de production intelligentes, (2) durabilité et circularité, (3) modèles organisationnels d’adoption et (4) innovations textiles et e-textiles. Les freins principaux apparaissent interconnectés : coûts d’investissement élevés, déficit de compétences en data science, interopérabilité limitée, cybersécurité et résistances sociotechniques. L’étude montre aussi une concentration géographique inégale, les pays du Sud produisant des connaissances souvent sous-citées. L’intelligence artificielle émerge comme un axe transversal appliqué à la maintenance prédictive, la simulation, l’automatisation et la gestion adaptative.
En conclusion, cette étude propose une lecture systémique des barrières et offre un cadre structurant pour une transition vers un modèle textile plus intelligent, durable et résilient.
JEL Classification : O33, L67, M11, Q56
Type du papier : Recherche Théoriqu
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
Author-wise bibliometric analysis based on entropy.
No full textAuthor-wise bibliometric analysis based on entropy.</p
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