Work Life Balance up in the Air – Does Gender Make a Difference between Female and Male International Business Travelers?

Managing work-life balance (WLB) has become an issue for both employees and HR departments since WLB tensions may reduce performance, overall job satisfaction and finally, increase the fluctuation rate. Having a balance between job and non-work is a particular challenge for international business travelers, but research on this topic is still in its very infancy. The aim of this article and its underlying qualitative study was to discover factors that influence WLB of those employees, and to explore potential differences among male and female. The results clearly show a big difference in the perception of factors influencing WLB depending on the family situation. This highlights the need of HR departments to offer individually tailored support for the different groups of international business travelers.Das Managen der Work-Life Balance (WLB) ist für immer mehr Arbeitnehmerinnen und Arbeitnehmer als auch Personalabteilungen ein Thema geworden, da ein Ungleichgewicht zwischen Arbeit und 'Nicht-Arbeit' nicht nur Leistung sowie die allgemeine Jobzufriedenheit reduzieren, sondern letztendlich auch zu höheren Fluktuationsraten führen kann. Diese Balance zu halten, ist besonders für internationale Geschäftsreisende eine Herausforderung. Dennoch befindet sich die Forschung zu diesem Thema noch stark in den Kinderschuhen. Ziel dieses Artikels und der zugrundeliegenden qualitativen Studie ist es, die WLB dieser Gruppe von Arbeitnehmern sowie potenzielle Unterschiede zwischen weiblichen und männlichen Vielfliegern zu erörtern. Die Resultate zeigen, dass die Einflussfaktoren auf die WLB in Abhängigkeit von der Familiensituation unterschiedlich wahrgenommen werden. Diese Ergebnisse betonen den Bedarf nach Unterstützungsmaßnahmen seitens der Personalabteilungen, welche für die einzelnen Gruppen von internationalen Geschäftsreisenden maßgeschneidert sind

Measurement Invariance of the Satisfaction With Life Scale Across 26 Countries

The Satisfaction With Life Scale (SWLS) is a commonly used life satisfaction scale. Cross-cultural researchers use SWLS to compare mean scores of life satisfaction across countries. Despite the wide use of SWLS in cross-cultural studies, measurement invariance of SWLS has rarely been investigated, and previous studies showed inconsistent findings. Therefore, we examined the measurement invariance of SWLS with samples collected from 26 countries. To test measurement invariance, we utilized three measurement invariance techniques: (a) multigroup confirmatory factor analysis (MG-CFA), (b) multilevel confirmatory factor analysis (ML-CFA), and (c) alignment optimization methods. The three methods demonstrated that configural and metric invariances of life satisfaction held across 26 countries, whereas scalar invariance did not. With partial invariance testing, we identified that the intercepts of Items 2, 4, and 5 were noninvariant. Based on two invariant intercepts, factor means of countries were compared. Chile showed the highest factor mean; Spain and Bulgaria showed the lowest. The findings enhance our understanding of life satisfaction across countries, and they provide researchers and practitioners with practical guidance on how to conduct measurement invariance testing across countries. © 2017, © The Author(s) 2017

Measurement Invariance of the Satisfaction With Life Scale Across 26 Countries

The Satisfaction With Life Scale (SWLS) is a commonly used life satisfaction scale. Cross-cultural researchers use SWLS to compare mean scores of life satisfaction across countries. Despite the wide use of SWLS in cross-cultural studies, measurement invariance of SWLS has rarely been investigated, and previous studies showed inconsistent findings. Therefore, we examined the measurement invariance of SWLS with samples collected from 26 countries. To test measurement invariance, we utilized three measurement invariance techniques: (a) multigroup confirmatory factor analysis (MG-CFA), (b) multilevel confirmatory factor analysis (ML-CFA), and (c) alignment optimization methods. The three methods demonstrated that configural and metric invariances of life satisfaction held across 26 countries, whereas scalar invariance did not. With partial invariance testing, we identified that the intercepts of Items 2, 4, and 5 were noninvariant. Based on two invariant intercepts, factor means of countries were compared. Chile showed the highest factor mean; Spain and Bulgaria showed the lowest. The findings enhance our understanding of life satisfaction across countries, and they provide researchers and practitioners with practical guidance on how to conduct measurement invariance testing across countries