AcademicArticleSCO_85014466466
Academic Article in Scopus
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abstract
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© 2017, © Emerald Publishing Limited. Purpose: This paper aims to seek to provide a more comprehensive view of the determinants of experienced well-being by incorporating personal characteristics suggested to be significant predictors of global well-being, such as income, materialism, religiosity, community mindedness and sleep quality (Diener et al., 1999; Frey and Stutzer, 2002), as well as time-use activities (Kahneman and Krueger, 2006) and contextual elements, such as day of the week (Csikszentmihalyi and Hunter, 2003; Kahneman et al., 2004a) and the presence of companions, into a single model of predictive experienced well-being using the day reconstruction method (Kahneman et al., 2004a). Design/methodology/approach: The authors applied the day reconstruction method to a sample of 1,823 episodes from 104 undergraduate students at a private university in Mexico to determine time assignment and emotional experience. Data were analyzed using a panel data regression model. Findings: It is currently accepted that experienced well-being depends on how people assign their time; however, the results suggest marginal and interaction effects between time assignment and sharing activities with others. Individuals experience an increase in well-being when any activity is done with others, independent of the valence or the duration of the activity. Also, while money does not produce higher well-being, the share of the budget that is spent with others does cause people to experience more well-being. Finally, the results indicate that personal characteristics are equally important to experienced well-being. Research limitations/implications: The sample was restricted to students; thus, to achieve external validity, it is necessary to replicate this analysis within different populations as well as groups of different ages and occupations. Originality/value: The authors provided an integrative model of experienced well-being that combines personal characteristics, time assignment and contextual factors. In addition, this model provides a more accurate gauge of the impact of personal characteristics on well-being than previous studies by controlling for time assignment and by measuring the impact on experienced, rather than global, well-being.
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