Partial least squares regression and importance–satisfaction analyses of the strategic drivers of happiness: A quality of life survey in Seoul, Korea

Abstract

AbstractUsing survey data by the Seoul Metropolitan Government for 5 years (n = 228,103 individuals), this study analyzes the magnitudes of the impacts of major grouping variables on variations in the overall happiness through partial least squares regression analysis. This study then uses the importance–satisfaction analysis to explore how the between‐group variations can be reduced according to the current satisfaction as well as the ultimate importance of the five happiness components (health, finance, relationships with close relatives/friends, home life, and social life). The regression finds that self‐respect‐as‐a‐Seoul‐citizen, social class recognition, years (other than 2014), household income, and not being elderly have a positive difference in happiness. The importance of the social class recognition over the objective income suggests the validity of soft policies for increasing happiness as a subjective concept. The low happiness level in 2014 may reflect history effects or events that occurred in that year. The importance–satisfaction analysis presents customized strategies by group. Specifically, policies oriented to financial happiness are prioritized for groups with low values on self‐respect, class recognition, household income, and age while health‐ and home life‐related policies should be additionally arranged for the older population.