Introduction

According to "The Equality Equation: Advancing the Participation of Women and Girls in STEM," a World Bank report that provides a comprehensive overview of global gender gaps in STEM education, only 18% of girls enrolled in tertiary education are pursuing STEM studies, compared to 35% of boys. Despite repeated global calls to increase women's representation in the STEM workforce, women account for only 33% of researchers, 22% of professionals working in artificial intelligence, and 28% of engineering students worldwide. In India, 43% of STEM graduates are women, but only 14% go on to become scientists, engineers, and technologists. Despite ranking second in the world's top 20 countries with the highest number of women tech CEOs, the share of women CEOs in tech companies in India is only 5%. Not giving women the space to invent and participate in STEM fields will result in a lack of diversity and innovation(AISHE 2020-21).

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Source: July 2021, Economic Times

This paper highlights the importance of increasing women's representation in innovation and STEM fields. Currently, women are underrepresented in these fields, which limits diversity and innovation. To address the underrepresentation of women in innovation and STEM fields, this paper argues that behavioural economics can be used to identify and address implicit biases and discrimination.

The Reasons behind Underrepresentation of Women in Innovation and STEM Fields

Women's underrepresentation in STEM fields can be attributed to a variety of factors at different stages. In higher education, societal and cultural factors, such as gender stereotypes, lack of female role models, and societal expectations, are the root causes of girls not choosing STEM fields(William & Mary, 2014). Expectancy-value theory suggests that students choose a subject based on its usefulness to personal goals, the extent to which it meets their life goals, and how much they enjoy the subject (intrinsic value), as well as the psychological, economic, and opportunity costs associated with the option(Ker & Tomei, 2013). However, this theory is not true across all subjects; a few subjects like biology and chemistry have a higher proportion of women than men. The association of certain fields as feminine or masculine and cleverness is attributed to this. Social norms influence our behaviour and perceptions, and we tend to follow others. The perception that women are not as good as men in STEM subjects, although false, affect their decisions. Additionally, women feel a low sense of belonging in the field(Wilson and VanAntwerp 2021).

Increasing Women in Innovation and STEM Fields

Behavioural economics can address these factors by shifting students' expectancy-value beliefs about STEM or self-reported motivation to participate in STEM(Rozek et al. 2017). Providing information about STEM's utility or making students aware of the relevance of STEM subjects to their lives can be helpful, as can exposure to successful women in STEM fields through mentorship, networking, and media(Stout et al. 2011; Elliott et al. 2020). With the prevalence of implicit biases in hiring and promotion, interventions such as blind resume reviews and structured interviews(Isaac et al. 2009).

To promote the value of a STEM career, the paper suggests developing a coherent strategy using the four P's: Product (a STEM job and its core value), Promotion (the main message suggested above), Price (financial or behavioural costs for the woman who performs the desired behaviour), and Place (the distribution of information or ideas about behavioural change)(Friedmann ).

Science communication can also play a crucial role in changing perceptions and stereotypes in STEM by socially engineering representations of scientists and engineers(Fogg-Rogers and Hobbs 2019). However, it is essential to evaluate the effectiveness and scalability of these interventions and ensure that they are inclusive and effective for all populations, including those from underrepresented groups.

Case Study of Successful Intervention

The 'Women Like Me' project provided public engagement and outreach training to 52 female engineers while also offering mentoring opportunities. They reached out to schools with higher than average numbers of students from lower socioeconomic backgrounds, targeting boys as well to challenge social norms about engineers. Questionnaires were completed by all 52 engineers, and junior engineers reported improved communication skills and networking opportunities. Mentoring pairs received training and met at least twice, and feedback indicated that junior engineers benefitted from meeting other engineers in the same position and learning about public engagement. Providing training and supporting opportunities for female scientists and engineers in education outreach is crucial to improve self-efficacy, enhancing capacity, and acting as positive role models for young girls. These social connections can boost the science capital of girls and other minorities in STEM, enabling them to pursue rewarding careers. Successful interventions can be scaled up by sharing best practices and collaborating with policymakers, educators, and employers(Fogg-Rogers and Hobbs 2019).

Conclusion

By studying how people make decisions and the factors that influence those decisions, behavioural economics interventions such as blind resume reviews, structured interviews, mentorship, networking, media exposure, and educational programs can be implemented to reduce implicit biases in hiring and promotion, increase exposure and access to successful women in STEM fields, and reduce the effects of gender stereotypes.

Increasing women's representation in innovation and STEM fields is significant because it can improve economic outcomes and address societal challenges. However, critics argue that behavioural economics interventions may not address the root causes of underrepresentation and may place the burden of change on individuals rather than institutions. Additionally, behavioural economics interventions may not be effective for all women and may not address other forms of diversity such as race and ethnicity. Thus, more research is needed to evaluate the effectiveness and scalability of behavioural economics interventions and to ensure that they are inclusive and effective for all populations. Future research should also focus on addressing other forms of diversity in innovation and STEM fields.

References
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