ECEO - Artigos de Revistas Internacionais com Arbitragem Científica

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    Assessing socioeconomic variables in HRM individual academic performance
    (Journal of Management Research and Practice, 2022) Santos, Miguel Baião; Coelho, Edviges; Duarte, Maria Isabel Alves; Chrzanowski, Maciej
    The present case study is focused on the analysis of some socioeconomic variables on the Higher Education accession path. The research tried to answer the question if there is any association between the accession path and the student’s performance. A sample of 1001 students from a HRM bachelor’s degree has been used. One of the main findings is that individual performance is independent of the accession path, but it is associated to other socioeconomic variables. Despite the uniqueness of the access path variable, it seems that it has no influence on student performance. Keywords: higher education, HRM, performance, socioeconomic variables, accession path
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    Work experience led programs and employment attainment
    (International Journal of Economics and Business Administration, 2021-03) Santos, Miguel Baião; Buligina, Ilze
    Purpose: This paper studied a ALMP to assess its effectiveness, the significance of public expenditure and the role of work experience on employment attainment. Design/Methodology/Approach: The existing literature has produced, so far, contradictory findings regarding work experience led programmes. The authors studied a Professional Traineeship Programme (PTP) outcome, using a descriptive statistic to verify the employment attainment rate and characteristics, over 13 years of the programme implementation. Findings: We found that the PTP has an employment attainment average rate of almost 3 out of 4 trainees. The regression analysis indicates clearly a strong positive linear relationship between the dependent and independent variables. The number of trainees has a keener contribution on the employment attainment figures but, apparently, the role of public expenditure is not decisive. Practical Implications: The findings clearly may help policy makers to take grounded decisions regarding this sort of programmes. Concerning the policy implications, the conclusions may lead to the fact that the PTP should continue to be provided to unemployed people (both youth and the adult population) bearing in mind the good results in employment attainment. Originality/Value: A scientific approach assessment of this PTP has never been done. It is clear research that may contribute to clear-cut the contradictory findings on this sort of ALMP. Keywords: Professional traineeships, active labour market policies, employment, unemployment.
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    Comparing decision tree-based ensemble machine learning models for covid-19 death probability profiling
    (Journal of Vaccines & Vaccination, 12: 441, 2021) Gonçalves, Carlos Pedro; Rouco, José
    Background: Age group, sex and underlying comorbidity or disease have been identified as major risk factors in COVID-19 severity and death risk. Aim: We compare the performance of major decision tree-based ensemble machine learning models on the task of COVID-19 death probability prediction, conditional on three risk factors: age group, sex and underlying comorbidity or disease, using the US Centers for Disease Control and Prevention (CDC)’s COVID-19 case surveillance dataset. Method: To evaluate the impact of the three risk factors on COVID-19 death probability, we extract and analyze the conditional probability profile produced by the best performing model. Result: The results show the presence of an exponential rise in death probability from COVID-19 with the age group, with males exhibiting a higher exponential growth rate than females, an effect that is stronger when an underlying comorbidity or disease is present, which also acts as an accelerator of COVID-19 death probability rise for both male and female subjects. These results are discussed in connection to healthcare and epidemiological concerns and in the degree to which they reinforce findings coming from other studies on COVID-19.