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Gender diversity issues in the IT industry: How can your sourcing group help?

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  • Atal, Nikita
  • Berenguer, Gemma
  • Borwankar, Sameer

Abstract

In the information technology (IT) industry, women constitute only 33% of employees at the entry level and 17% at the leadership level. In this article, we outline the status of women in the workforce and discuss issues that affect their participation, with a specific focus on the IT sector. We claim that U.S. corporations can influence gender diversity in the IT industry by leveraging their relationships with IT suppliers. To this end, we propose the application of Nudge Theory during the strategic sourcing of IT services. We begin our narrative by describing the current state of gender diversity initiatives. Then, we detail gender diversity initiatives in the sourcing process as revealed by a survey on the topic related to IT suppliers. We then briefly define Nudge Theory and provide examples of this theory as applied to an organization’s supplier base. Finally, we present the details of our recommendation, which suggests that sourcing groups should include questions regarding women’s participation in the IT supplier’s workplace during competitive market events. We conclude with a call to action and a call to research.

Suggested Citation

  • Atal, Nikita & Berenguer, Gemma & Borwankar, Sameer, 2019. "Gender diversity issues in the IT industry: How can your sourcing group help?," Business Horizons, Elsevier, vol. 62(5), pages 595-602.
    • Handle: RePEc:eee:bushor:v:62:y:2019:i:5:p:595-602
    DOI: 10.1016/j.bushor.2019.04.004
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    References listed on IDEAS

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    1. Kimberly Bayard & Judith Hellerstein & David Neumark & Kenneth Troske, 2003. "New Evidence on Sex Segregation and Sex Differences in Wages from Matched Employee-Employer Data," Journal of Labor Economics, University of Chicago Press, vol. 21(4), pages 887-922, October.
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    Cited by:

    1. Pooja Sengupta & Roma Puri, 2022. "Gender Pay Gap in India: A Reality and the Way Forward—An Empirical Approach Using Quantile Regression Technique," Studies in Microeconomics, , vol. 10(1), pages 50-81, June.

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