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Getting a balance in the life satisfaction determinants of full-time and part-time European workers

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  • Henriques, C.O.
  • Marcenaro-Gutierrez, O.D.
  • Lopez-Agudo, Luis Alejandro
Abstract
This paper explores the trade-offs between four different aspects of European workers’ life satisfaction (satisfaction with education, the present work, family life and social life), to reach balanced optimal levels across these features. This analysis was performed separately for different profiles of workers, i.e. full-time and part-time workers in 34 different European countries, differentiated by gender. The methodology employed for this purpose couples econometric and multiobjective interval programming approaches, enabling to assess the compromises of specific aspects of workers’ personal and working conditions.

Suggested Citation

  • Henriques, C.O. & Marcenaro-Gutierrez, O.D. & Lopez-Agudo, Luis Alejandro, 2020. "Getting a balance in the life satisfaction determinants of full-time and part-time European workers," Economic Analysis and Policy, Elsevier, vol. 67(C), pages 87-113.
    • Handle: RePEc:eee:ecanpo:v:67:y:2020:i:c:p:87-113
    DOI: 10.1016/j.eap.2020.07.002
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    References listed on IDEAS

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    Cited by:

    1. Prieto-Latorre, Claudia & Lopez-Agudo, Luis Alejandro & Luque, Mariano & Marcenaro-Gutierrez, Oscar David, 2022. "The ideal use of the internet and academic success: Finding a balance between competences and knowledge using interval multiobjective programming," Socio-Economic Planning Sciences, Elsevier, vol. 81(C).

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    More about this item

    Keywords

    Workers’ life satisfaction; Full-time workers; Part-time workers; Multiobjective interval programming; Econometric analysis;
    All these keywords.

    JEL classification:

    • J28 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Safety; Job Satisfaction; Related Public Policy
    • C54 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Quantitative Policy Modeling
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis

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