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Research Interests:
En este trabajo se presentan los resultados de un estudio, el primero de estas características a nivel de la Comunidad de Castilla y León, cuyo objetivo es identificar los perfiles socioeconómicos de las mujeres salmantinas, en situación... more
En este trabajo se presentan los resultados de un estudio, el primero de estas características a nivel de la Comunidad de Castilla y León, cuyo objetivo es identificar los perfiles socioeconómicos de las mujeres salmantinas, en situación de irregularidad laboral, en comparación con las características de las mujeres que desarrollan su actividad en un marco laboral regular.<br /><br />The objective of this work is identifying the socio-economic profiles of women holding undeclared jobs as opposed to the profites of those holding declared jobs. This study is the first of its kind in the Castilla y León Community.
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In recent years, social responsibility has been revolutionizing sustainable development. After the development of new mathematical techniques, the improvement of computers’ processing capacity and the greater availability of possible... more
In recent years, social responsibility has been revolutionizing sustainable development. After the development of new mathematical techniques, the improvement of computers’ processing capacity and the greater availability of possible explanatory variables, the analysis of these topics is moving towards the use of different machine learning techniques. However, within the field of machine learning, the use of Biplot techniques is little known for these analyses. For this reason, in this paper we explore the performance of two of the most popular techniques in multivariate statistics: External Logistic Biplot and the HJ-Biplot, to analyse the data structure in social responsibility studies. The results obtained from the sample of companies representing the Fortune Global 500 list indicate that the most frequently reported indicators are related to the social aspects are labour practices and decent work and society. On the contrary, the disclosure of indicators is less frequently relat...
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The main objective of this research is to find the sustainability gradients of Global Fortune 500 companies and sort them as a function of economic, environmental, and social components using multivariate statistical methods to establish... more
The main objective of this research is to find the sustainability gradients of Global Fortune 500 companies and sort them as a function of economic, environmental, and social components using multivariate statistical methods to establish the foundations for better knowledge of the trends and sustainability reporting habits. A combined approach, comprising principal coordinates analysis (PCoA) and logistic regression model (LRM), is proposed to build an external logistics biplot (ELB). Moreover, HJ-Biplot and parallel coordinates are applied. This chapter helps to understand why many companies view their corporate social responsibility (CSR) reports as a way to guarantee the credibility of the published information. In particular, based on the Global Reporting Initiative, the sustainability gradients of the Global Fortune 500 companies are obtained and statistically exploited to analyze how the companies can make improvements in terms of sustainability.