![]() ![]() In parallel, it is postulated that the levels of self-esteem in the university environment may be related to the strategies implemented to solve problems. Despite this, the educational field is still an environment that lacks a variety of studies that use this type of predictive tools. The theoretical and methodological implications are discussed.Īrtificial intelligence is a useful predictive tool for a wide variety of fields of knowledge. ![]() Second, an interaction effect between age of acquisition and abstractness was found to explain model performance. First, words with early maturation and subsequent semantic definition promoted emotional propagation. Moreover, different multiple linear regression and mixed-effect models revealed moderation effects for the performance of the longitudinal computational model. These findings highlight a potential mechanism for early verbal emotional anchoring. In this way, different propagative processes were observed in the adult semantic space. Results suggested that the emotional valence of words can be predicted from amodal vector representations even at the child stage, and accurate emotional propagation was found in the adult word vector representations. Samples of 12 words were used in the child and the adult semantic spaces, respectively. Then, the resulting neural network was tested with adult word representations using ratings from an adult data set. The neural network was trained and validated in the child semantic space. Some children's word representations were used to set a mapping function between amodal and emotional word representations with a neural network model using ratings from 9-year-old children. In this study, children's and adult word representations were generated using the latent semantic analysis (LSA) vector space model and Word Maturity methodology. We present a longitudinal computational study on the connection between emotional and amodal word representations from a developmental perspective. The theoretical and practical contributions of the study improve the understanding of the relationships raised, being a pioneering study due to its contextualization in the wine industry, as well as providing a series of guidelines for both environmental managers and winemakers to improve their GP. In addition, GI partially mediates the relationship between these two variables, playing a key role in the environmental management of wineries. ![]() The results of the research indicate that there is a positive and significant relationship between GIC and GP. In order to achieve the proposed objectives, data from a survey of 202 wineries in Spain were used and a quantitative approach was followed using Structural Equation Modeling. Third, GIC represents an incipient field of study that needs to be developed and established within the literature linked to Intellectual Capital. Second, to the best of our knowledge, there is no previous research that has contextualized the relationships raised in the wine industry, thus representing an advance in the comprehension of the constructs studied. First, there is little empirical evidence of the relationships proposed in this study. Therefore, the research questions to be answered by this study are as follows: Does GIC influence environmental performance? Does GI mediate the GIC-GP relationship? What actions can companies take to improve their GP? There are several reasons that have led us to carry out this research. Specifically, the study shows how GP is influenced by GIC through the mediating role of the Green Innovation variable. In this context, the present research focuses its interest on analyzing how the set of green intangibles possessed by organizations, i.e., Green Intellectual Capital, affects their Green Performance. In this context, companies play a decisive role in achieving environmental objectives through the ecological knowledge they can store and manage. Global environmental problems, such as global warming, pollution, or deforestation, are critical issues that require a rapid and common response.
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