1,720,978 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
Final Energy Consumption—Growth Nexus in Romania Versus the European Union: A Sectoral Approach Using Neural Network
No full textThe energy crisis caused first by the COVID-19 pandemic and continued by the Russo-Ukrainian War has demonstrated that energy is a determining factor in the conduct of activities of any state. Several studies have examined the relationship between energy consumption and economic growth, developing various theories, but there is no consensus. This study investigates relationships by analyzing several regression models and choosing the fittest. Then, the verification of its validity is performed through the neural network, which gives greater credibility to the results obtained. Furthermore, using a structural analysis, the investigation is expanded to ranking the impact of sector-specific energy consumption on economic growth. The research includes data from 1995 to 2020 for the European Union (EU) and Romania. The results indicate that short-term energy consumption can have a positive or negative impact on economic growth, both in the EU and Romania. The structural analysis highlights the direct and indirect effects, with different intensities, of sector-specific energy consumption on economic growth. This study is interested primarily in the conditions of uncertainty caused by the COVID-19 pandemic and the Russo-Ukrainian War, to enable the EU and each member state to take effective energy policy measures to ensure their energy security
Approach to the Impact of Digital Technologies on Sustainability Reporting through Structural Equation Modeling and Artificial Neural Networks
No full textThe motivation for study derives from the requirements imposed by the European Union Corporate Sustainability Reporting Directive, which increases the sustainability reporting scope and the need for companies to use emerging digital technologies. The research aim is to evaluate the digital transformation impact of the European Union companies on sustainability reporting expressed through three sustainable performance indicators (economic, social, and ecological) based on a conceptual model. The data were collected from Eurostat for 2011–2021. The study proposes a framework for sustainable performance analysis through linear regression models and structural equations. Additionally, a hierarchy of digitization indicators is created by modeling structural equations, depending on their impact on sustainability performance indicators, which is validated using neural networks. The results indicate that the company’s digital transformation indicators positively influence economic and social performance and lead to an improved environmental protection (a decrease in pollution), proving the established hypotheses’ validity. The proposed model can be the basis for companies to create their dashboards for analyzing and monitoring sustainable performance. This research can be the basis of other studies, having a significant role in establishing economic and environmental strategies to stimulate an increase of companies that carry out sustainability reporting
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
A Hybrid SEM-Neural Network Modeling of Quality of M-Commerce Services under the Impact of the COVID-19 Pandemic
No full textThe research purpose is to contribute to the understanding of the COVID-19 pandemic impact on the intensification of commercial transactions on the mobile channel (m-commerce) and to identify the most significant factors that act on consumer behavior based on the development of a conceptual model to establish the influence of m-commerce service quality on customer satisfaction and loyalty. The data were collected through a survey addressed to customers who, during 2021–2022, made at least one purchase through m-commerce. The analysis was performed with SPSS Statistics and Amos software, using a hybrid approach: Structural Equation Modeling (SEM) and Artificial Neural Network (ANN). The research results confirm the hypotheses presented in this study. Both models identified the quality of services offered by m-commerce, satisfaction, and trust as determining factors for increasing consumer loyalty in virtual commerce. The novelty of this study consists of an interconnected analysis model of some variables specific to mobile commerce, which have not been used in this combination in the specialized literature. This research can be the basis of other research studies. In addition, it provides valuable results for the business environment (forecasts) and customers by obtaining improved, personalized, and secure commerce services
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
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