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Structural Hindrances or Less Driven Women? Managers’ Views on Corporate Quotas

Published online by Cambridge University Press:  01 April 2019

Þorgerður J. Einarsdóttir
Affiliation:
University of Iceland
Guðbjörg Linda Rafnsdóttir
Affiliation:
University of Iceland
Margrét Valdimarsdóttir
Affiliation:
University of Iceland
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Abstract

High levels of women in politics and paid work, together with the availability of paid parental leave and public child care, make the gender imbalance in business leadership in Iceland all the more confounding. This study analyzes business leaders’ attitudes toward gender and leadership positions after a gender quota law for company boards was implemented in 2013. We explore support for gender quotas and whether it is related to how respondents explain women's underrepresentation in leadership positions. A questionnaire was sent to 1,349 managers in the 250 largest companies in Iceland. Our findings indicate that women are more supportive of gender quotas than men. The way in which the respondents explain the underrepresentation of women as top managers is strongly related to their support for gender quotas. Those who believe that women are structurally disadvantaged are more likely to support gender quotas than those who adhere to individual explanations. Furthermore, male dominance at higher company levels is related to negative views on gender quotas, whereas this does not apply at lower levels. The research emphasizes the impact of business leaders on the recruitment of women to business leadership positions and, at the same time, has implications for policy interventions.

Information

Type
Research Article
Copyright
Copyright © The Women and Politics Research Section of the American Political Science Association 2019
Figure 0

Table 1. Gender division among CEOs and chairs of boards in companies to which quota laws apply (50+) and do not apply (1–49).

Figure 1

Figure 1. Hypothesized model.

Figure 2

Table 2. Descriptive statistics

Figure 3

Table 3. Attitudes toward gender quotas by gender

Figure 4

Table 4. Ordinary least squares regression estimates predicting support for gender quotas

Figure 5

Table 5. Ordinary least squares regression estimates predicting explanations for women's underrepresentation as managers

Figure 6

Table 6. Ordinary least squares regression estimates predicting support for gender quotas