Modelling intellectual capital in the Covid-19 era

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Javier Carreon Guillen


In social sciences, the meta-analytical fixed effects models have gained special relevance due to their predictive capacity of a scenario, context and process, although they have focused on the estimation and prediction of simple variables, avoiding the effects of diffuse variables such as those emerging in processes Training and research. The objective of this work was to establish fixed effects models to explain the influence of diffuse variables in the formation of intellectual capital, considering contextual, educational, academic, and professional variables. A retrospective study was conducted with literature from 2014 to 2021, as well as an exploratory study with variables that have been conceptualized, but not empirically tested and correlational with an intentional selection of six studies that used diffuse variables to explain attrition. The results show that the model with the greatest adjustment is the one where the emergence of anti-plagiarism software and new editorial provisions explain the dropout, although the research design limited the results to the study scenario, suggesting its extension and sophistication with other statistical techniques.

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