The need for greater concern about job quality/satisfaction seems clear, due to its potential link with workers' productivity, to the extent it affects employees' quitting behaviour, absenteeism, turnover, and firms' productivity.
In order to guide managers and policy makers when making decisions related to future hiring of human resources, a multiobjective interval programming model, based on the results of an econometric estimation, is suggested where different (and conflicting) aspects of job satisfaction are considered. The modelling framework thus obtained allows assessing the trade-offs among the different aspects of job satisfaction under different scenarios herein given within interval ranges. Data obtained from Spain are used to carry out the model's instantiation. Possibly efficient solutions are then generated with the help of scalarizing problems relying on reference point-based methods. The solution approach herein proposed allows computing with a lower computational effort the closest “possibly” efficient so- lutions attainable regarding their corresponding interval ideal solutions. Overall, the results obtained highlight the trade-off between earnings and quality of life, particularly under a pessimistic scenario, with the maximization of earnings leading to the lowest value of the working times. Conversely, the lowest value obtainable for earnings is reached with the consideration of both scenarios when the maximization of the satisfaction of the quality of life seekers is attained. Finally, the trade-off between less prone to risk workers and quality of life seekers is also revealed, with the lowest job security levels found in the solution that maximizes working times.
