Page 101 - IJPS-11-1

International Journal of
Population Studies Malaysian women in logistics: Stay or switch?

Ngah et al., 2020). To enhance the model’s predictive power, the logistics industry, and the relationship between
the authors introduce work-life balance as a moderator intrinsic motivation and the intention to stay will be
within the research framework. Figure 1 illustrates the stronger when work-life balance is high.
research framework of the study with work-life balance as H5b: Work-life balance moderates the relationship
a moderator. Work-life balance refers to the degree with between extrinsic motivation and the intention to
which individuals manage diverse roles in their daily lives, stay in the logistics industry, and the relationship
such as job requirements, family’s responsibilities, and between extrinsic motivation and the intention to
any other roles to balance their professional requirements stay will be stronger when work-life balance is high.
and personnel responsibilities (Aloulou et al., 2023). For H5c: Work-life balance moderates the relationship
women, having a work-life balance is crucial to ensure they between job satisfaction and the intention to stay in
can meet the expectations of family members and work the logistic industry and the relationship between JS
requirements. Women want to perform at their offices and and the intention to stay will be stronger when work-
as mothers, wives, and daughters in their families. In the life balance is high.
Malaysia context, women play a leading role in ensuring H5d: Work-life balance moderates the relationship
that their families are in an ideal situation. However, between family-supportive supervisory behavior and
working in the logistics industry, which is known as a day- the intention to stay in the logistics industry, and the
and-night working environment, has the potential to strain relationship between family-supportive supervisory
the work-life balance, as more time is spent on professional behavior and the intention to stay will be stronger
requirements. Work-life balance leads not only to greater when work-life balance is high.
productivity but also improves company loyalty and reduces
the level of intent to leave the organization (Moore, 2007). 2. Data and methods
As mentioned by Dousin et al. (2021), work-life balance 2.1. Sampling method and data collection
improves employees’ emotional well-being and reduces
turnover intention. Moreover, Vo et al. (2023) suggest that A purposive sampling method was applied in this study
based on institutional logic, a good work-family balance as the authors focus on recruiting women in the logistics
helps to retain women talent. Hence, the authors believe industry. Moreover, besides the specific criteria of the
that work-life balance could increase the intention to respondents, unavailability of the sampling frame also
commit in the logistics industry among women. As such: forced the authors to employ this sampling technique
H5a: Work-life balance moderates the relationship between (Hassan et al., 2023; Rowley, 2014). An online survey
intrinsic motivation and the intention to stay in was used to collect the data in the present study. To
ensure sufficient sample size, the authors used numerous
channels to share a link to the questionnaire. In the
early stage, the link was shared through Facebook and
Instagram to seek women respondents from logistics
companies. Using personal contacts, the authors also
used WhatsApp to distribute the link to the questionnaire.
Last, the authors also contacted logistics companies by
approaching their human resource departments to share
the link with women in their organizations. From these
contacts, the authors managed to collect 280 completed
questionnaires. However, after screening, only 248
answers were valid and usable for the data analysis.
The reasons for discarding respondents included the
inclusion of men respondents, high missing values, and
respondents with the same score from the beginning till
the end (Ngah et al., 2023).

In determining the minimum sample size as suggested
by Albtoosh & Ngah (2022) and Hair et al. (2019), the
authors conducted power analysis. In the case for nine
Figure 1. Structural model predictors, 80% power, and a medium effect size as
Abbreviations: Ext: Extrinsic motivation; FSSB: Family supportive
supervisory behavior; Intention: Intention to stay; Instr: Intrinsic suggested by Gefen et al. (2011) and Ngah et al. (2021),
motivation; JS: Job satisfaction; WLB: Work-life balance. the minimum sample size of our research is 114. Since

Volume 11 Issue 1 (2025) 95 https://doi.org/10.36922/ijps.1700