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This paper aims to propose a multiobjective branch and bound (MOBB) algorithm with a new criteria for the branching and discarding of nodes based on Pareto dominance and contribution metric.

A multiobjective branch and bound (MOBB) method is presented and applied to the bi-objective combinatorial optimization of a safety transformer. A comparison with exhaustive enumeration and non-dominated sorting genetic algorithm (NSGA2) confirms the solutions.

It appears that MOBB and NSGA2 are both sensitive to their control parameters. The parameters for the MOBB algorithm are the number of starting points and the number of solutions on the relaxed Pareto front. The parameters of NSGA2 are the population size and the number of generations.

The comparison with exhaustive enumeration confirms that the proposed algorithm is able to find the complete set of non-dominated solutions in about 235 times fewer evaluations. As this last method is exact, its confidence level is higher.

The COVID-19 pandemic created not only a public health crisis but also the largest disruption to the global economies. The purpose of the paper is to investigate the adverse impacts of the pandemic on self-employment including job loss, income reduction and cut back in work hours and how these impacts were related to the well-being the self-employed. The authors also examine how self-employers responded to adversity in different cultural settings.

The main sample was obtained the Gallup World Poll that covers more than 39,000 individuals across 55 countries over the period from October 2020 to June 2021. The ordinary least square was the main choice of methodology. The paper employs the Oaxaca-Blinder decomposition technique to quantify the gap in financial loss between self-employed and employed individuals. Finally, the moderated mediation analysis allows the authors to examine how financial loss mediates the reduction in well-being of self-employers.

The paper finds that self-employers were 29% more likely to lose their businesses than paid individuals to lose their jobs and perhaps as a result, they were 50% more likely to experience lower work hours and less income. The findings suggest that the impact of the COVID-19 pandemic varied across countries. The financial gap between self-employment and full-time employment was narrower in countries with individualism, low uncertainty avoidance and propensity for long-term future. Finally, the paper shows that although financial loss associated with the coronavirus situation mediated the relationship between self-employment and reduced wellbeing, the positive relationship between self-employment and life satisfaction (wellbeing) held amid the pandemic. Despite all the pecuniary setbacks relative to full-time employment, self-employers report higher subjective wellbeing than regular wage earners during difficult times.

The earnings gap between self-employers and employees persists (and increase) during adverse conditions may cast into doubt the efficiency of the economic system that ensures no one is left behind. In addition, contextual factors such as cultural values should also be taken into consideration in reducing the earning gap between self-employment and regular employment. It is also implied that the self-employed choose to engage in self-employment due to psychological and emotion benefits rather than material achievements.

This study has quantified the income gap between self-employment and employed individuals in the context of adverse economic conditions. This study also highlights the fact that despite all the financial setbacks, self-employers are happier than employed individuals and they engage in self-employment as an important way to pursue happiness. This highlights well-being as the critical non-pecuniary benefits of the career choice of and transition into self-employment that have been confirmed in extant entrepreneurship literature.