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This study examines the effect of work–family conflict (WFC) and work–family enhancement (WFE) on the wellbeing of the self-employed and their spouses. Adopting a dyadic perspective, our analysis focuses on three dimensions of wellbeing: physical health, mental health and life satisfaction. Using the Spillover and Crossover Model as theoretical framework and the Actor–Partner Interdependence Model as an estimation technique, we investigate how work–family conflict and enhancement among the self-employed and their spouses were associated to their individual and mutual wellbeing. The analysis revealed a strong actor and partner effect, such that one's own perception of WFC undermined the wellbeing for both the self-employed and their spouses. Further, WFE was associated with an improvement in wellbeing, mainly for the self-employed, and not their spouses. The results partially supported the 'crossover hypothesis', suggesting that launching a new business is a stressful endeavour at the dyadic level of the self-employed and their spouses. [ABSTRACT FROM AUTHOR]

This paper aimed to compare the multi-layer perceptron as an artificial neural network and the decision tree model for predicting OPEC crude oil production. Machine learning is about designing algorithms that automatically extract valuable information from data, and it has seen many success stories. The accuracy of these two models was assessed using symmetric mean absolute percentage errors, mean absolute scaled errors, and mean absolute percentage errors. Achieved were the OPEC crude oil production's maximum projected figures. The OPEC crude oil output was also represented by certain descriptive scales and graphs; A comparison was made between the results and the earlier results acquired by the others after the study of the association between the variables revealed statistical significance. [ABSTRACT FROM AUTHOR]