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Business Structures, Stereotypes and Knowledge of Discrimination: Understanding Employers’ Support to Paid Family Leave in Hong Kong

Published online by Cambridge University Press:  24 March 2022

Haijing Dai
Affiliation:
Department of Social Work, Chinese University of Hong Kong, Hong Kong. E-mail: hjdai@cuhk.edu.hk
Nahri Jung
Affiliation:
Department of Social Work, Chinese University of Hong Kong, Hong Kong. E-mail: c362782@gmail.com
Nanxun Li
Affiliation:
Department of Social Work, Chinese University of Hong Kong, Hong Kong. E-mail: nxli@cuhk.edu.hk
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Abstract

Hong Kong society has put family-friendly workplace policies under serious discussion, but the investigation of the views of employers remains insufficient. Adopting the structure-agency paradigm, this study used survey data to examine how structural constraints in business and the subjective world of individual employers influence their support to paid family leave. We found that industry categories were significantly associated with employers’ support but not the size of their enterprises. Employers’ personal stereotypes of family caregivers and their awareness of relevant laws did not exert significant independent effects on their policy support, but the significant interaction of the two suggested that employers with knowledge of regulations were less likely to formulate attitudes towards paid family leave based on their own stereotypes. Policy practices therefore need to consider the rationality of employers in the local contexts of Hong Kong, and aim to integrate legal education with de-stigmatisation of family caregivers in advocacy programs.

Information

Type
Article
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
Copyright
© The Author(s), 2022. Published by Cambridge University Press
Figure 0

Table 1 Distribution of the sample (N=407)

Figure 1

Table 2 Descriptive of key variables (N=407)

Figure 2

Table 3 Results of SEM models (N=407)