1,720,993 research outputs found
Economic efficiency analysis of the Spanish olive industry
No full text[ES] El trabajo aborda una aproximación al análisis de la eficiencia económica de la industria oleícola española y los factores que pueden influir en ella. El análisis se ha realizado aplicando la metodología no paramétrica del Análisis Envolvente de Datos (DEA). La muestra está compuesta por un total de 429 empresas oleícolas que aparecen en la base de datos SABI en el año 2021. Los inputs utilizados han sido: Gastos en Personal, Aprovisionamientos e Inmovilizado, mientras que como output único se ha considerado las Ventas. El posterior recurso a pruebas estadísticas no paramétricas muestra diferencias significativas únicamente por tamaño empresarial. El trabajo aborda una aproximación al análisis de la eficiencia económica de la industria oleícola española, e intenta determinar los factores que pueden influir en ella. El análisis se ha realizado aplicando la metodología no paramétrica del Análisis Envolvente de Datos (DEA).[EN] The work addresses an economic efficiency analysis of the Spanish olive industry and the factors that can influence it. The analysis has been carried out applying the non-parametric methodology of Data Envelopment Analysis (DEA). The sample is made of a total of 429 olive oil companies that appear in the SABI database in 2021. The inputs used have been: Staff costs, Supplies and Fixed Assets, while Sales have been considered as the only output. The later non-parametric statistical tests has shown significant differences only by company size. The work addresses an economic efficiency analysis of the Spanish olive industry to determine the factors that can influence it. The analysis has been carried out applying the non-parametric methodology of Data Envelopment Analysis (DEA).Vidal, F.;Marques-Perez, Inmaculada;Ribal, Javier;Pastor, JT. (2025). Análisis de la eficiencia económica de la industria oleícola española. Economía Agraria y Recursos Naturales - Agricultural and Resource Economics. 25(1):163-177. https://doi.org/10.7201/earn.2025.01.07OJS16317725
Combination of ESG scores and prediction-based returns using long short-term memory neural networks to generate responsible portfolios
No full text[EN] The significance of the environmental, social, and governance (ESG) factors has risen substantially among investors in recent years. Similarly, machine learning techniques have allowed for improvements in the prediction of stock prices. Our research combines ESG factors and prediction-based returns using recurrent neural networks to create profitable-sustainable portfolios that can consistently beat the market index in return and ESG scores. Our analysis focuses on the components of the EURO STOXX 50 (R) Index during the year 2021 and the first half of 2022, allowing us to analyze two different market scenarios, continuous growth and bear market, respectively. This paper provides empirical evidence that combining machine learning with ESG scores and its application in portfolio optimization can achieve higher returns and higher ESG performance depending on the macroeconomic context and presents the trade-off between the Sharpe Ratio and the ESG score of the optimized portfolios for different scenarios.Jaume Jordan is supported by grant IJC2020-045683-I funded by MCIN/AEI/10.13039/501100011033 and by "European Union NextGenerationEU/PRTR".Martínez-Barbero, Xavier;Cervelló Royo, Roberto Elías;Jordán, Jaume;Ribal, Javier (2024). Combination of ESG scores and prediction-based returns using long short-term memory neural networks to generate responsible portfolios. Journal of Sustainable Finance & Investment. https://doi.org/10.1080/20430795.2024.2377551
Toward green finance: applying Bayesian machine learning in environmental portfolio management
No full text[EN] In recent years, the importance of climate change, environmental sustainability, and climate finance has witnessed a significant surge in recognition and relevance. The pressing global need to address environmental challenges and promote sustainable financial practices has become more pronounced than ever before. Traditional portfolio optimization often overlooks environmental considerations, resulting in sub-optimal investment decisions. In this paper, we propose the E-Sharpe Ratio, a metric tailored for evaluating environmental risk-adjusted returns. By combining this ratio with Bayesian machine learning, our methodology provides a comprehensive framework for assessing stocks and portfolios, accounting for both financial and environmental performance metrics. Our research contributes to the field of environmental and climate finance by bridging financial and environmental considerations, enabling investors to make environmentally-aware decisions, and enhancing the stock selection process underscoring the importance of integrating environmental criteria into modern investment strategies, paving the way for a more sustainable financial future.Open Access funding provided thanks to the CRUE-CSIC agreement with Springer Nature.Martínez-Barbero, Xavier;Cervelló Royo, Roberto Elías;Jordán, Jaume;Ribal, Javier (2025). Toward green finance: applying Bayesian machine learning in environmental portfolio management. International Journal of Data Science and Analytics. 20(7):6427-6440. https://doi.org/10.1007/s41060-025-00830-yS6427644020
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
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
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