Who they are, and what they do: perspectives on work–life balance among entrepreneurs and wage earners

Work–life balance (WLB) remains a pressing challenge in today’s fast-paced society. The current study addresses this prominent issue by examining whether employment type and individual characteristics shape perceptions of WLB among entrepreneurs and wage earners in Trinidad and Tobago. A structured survey was administered to a sample of entrepreneurs and wage earners and responses (n = 364) were statistically analysed to determine the main and interaction effects of employment type, age, ethnicity, relationship status, and sex on perceived WLB. Perceptions of WLB were lower among wage earners, though the observed differences were nonsignificant. Age and ethnicity emerged as significant main predictors of perceived WLB, with older persons and those of mixed ethnic backgrounds reporting higher levels of WLB. These main effects were moderated by the presence of a three-way interaction effect (sex × ethnicity × employment type) at p = 0.001. Our findings suggest that WLB is an intricate phenomenon that is not exclusively dependent on the occupational form, nor on an individual’s demographic composition but rather derived from the complex interactions between these two categories of variables. Thus, while entrepreneurship and wage employment both have the potential to improve standard of living, engaging in one type of employment versus the other may have an enhancing or diminishing effect on WLB based on life stages, ethnic affiliations and, possibly, other personal factors. This study’s findings also point to a need for more family-friendly policies and family-supportive working environments in Trinidad and Tobago. Though we move the field forward by addressing a critical gap in the literature, the explanatory variables tested in this study accounted for only 33.5% of the variance in the respondents’ WLB scores. We offer suggestions to overcome this limitation and others so that future studies can produce more nuanced and generalizable causal inferences.