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  • 标题:What Determines the Entrepreneurial Intentions of Highly-Skilled Women with Refugee Experience? An Empirical Analysis in the Context of Sweden
  • 本地全文:下载
  • 作者:Nina Lazarczyk-Bilal ; Beata Glinka
  • 期刊名称:Administrative Sciences
  • 电子版ISSN:2076-3387
  • 出版年度:2021
  • 卷号:11
  • 期号:1
  • 页码:2
  • DOI:10.3390/admsci11010002
  • 出版社:MDPI Publishing
  • 摘要:One of the main challenges faced by refugee hosting states is the labour market integration of newcomers, which can be achieved to some extent through the creation of small businesses. This paper analyses the individual level determinants of the entrepreneurial intentions of highly-skilled women with refugee experience. The study adds a new perspective to the conversation about highly-skilled migrant women analysed so far, mostly as family reunion migrants joining economic migrants. It also contributes to the relatively new research on refugee entrepreneurship by adopting an unusual perspective for looking at highly skilled women. The empirical analysis embedded in the context of Sweden is two-fold. First, it is done in SPSS on the sample (N = 98) drawn from the 2017 Swedish Invandrarindex data set with the use of binary logistic regression. Second, the findings from the quantitative analysis are nuanced with the analysis of two case studies based on SSI with Syrian women having refugee experience. The results show that the gender variable does not predict the effect on entrepreneurial intentions. The findings confirm the importance of previous self-employment and leadership experience and indicate the potential importance of entrepreneurial role models, the cultural aspect of entrepreneurial intentions and the role of an encouraging environment in the host country.
  • 关键词:highly-skilled migrant women; gender; refugee experience; entrepreneurial intentions; refugee entrepreneurship; Syria; Sweden; logistic regression; case study highly-skilled migrant women ; gender ; refugee experience ; entrepreneurial intentions ; refugee entrepreneurship ; Syria ; Sweden ; logistic regression ; case study
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