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An Agent-Based Simulation of Corporate Gender Biases

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Proceedings of the Future Technologies Conference (FTC) 2019 (FTC 2019)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1069))

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Abstract

Diversity & Inclusion (D&I) is a topic of increasing relevance across virtually all sectors of our society, with the potential for significant impact on corporations and more broadly on our economy and our society. In spite of the value of human capital, Human Resources in general and D&I in particular are dominated by qualitative approaches. We introduce an agent-based simulation that can quantify the impact of D&I on corporate performance. We show that the simulation provides a compelling explanation of the impact of hiring and promotion biases on corporate gender balance, and it replicates the patterns of gender imbalance found in various industry sectors. These results suggest that agent-based simulations are a promising approach to managing the complexity of D&I in corporate settings.

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Notes

  1. 1.

    The promotion-bias parameter can be positive or negative to simulate biases that favor men or women, respectively.

  2. 2.

    Smaller pool sizes coupled with non-zero promotion biases tend to create cyclical behaviors which do not influence the overall results but create some unnatural dynamics.

  3. 3.

    To ensure reproducibility, we have the ability to select the seed for the random number generator.

References

  1. Hunt, V., Yee, L., Prince, S., Dixon-Fyle, S.: Delivering through diversity (2018). https://www.mckinsey.com/business-functions/organization/our-insights/delivering-through-diversity. Accessed 17 Feb 2019

  2. Flabbi, L., Macis, M., Moro, A., Schivardi, F.: Do female executives make a difference? The impact of female leadership on gender gaps and firm performance. IZA Discussion Paper No. 8602 (2014). SSRN: https://ssrn.com/abstract=2520777

  3. Dezsö, C.L., Ross, D.G.: Does female representation in top management improve firm performance? A panel data investigation. Strateg. Manag. J. 33(9), 1072–1089 (2012)

    Article  Google Scholar 

  4. Blau, F.D., Kahn, L.M.: The gender pay gap: have women gone as far as they can? Acad. Manag. Perspect. 21(1), 7–23 (2007)

    Article  Google Scholar 

  5. Biagetti, M., Scicchitano, S.: A note on the gender wage gap among managerial positions using a counterfactual decomposition approach: sticky floor or glass ceiling? Appl. Econ. Lett. 18(10), 939–943 (2011)

    Article  Google Scholar 

  6. Becker-Blease, J., Elkinawy, S., Hoag, C., Stater, M.: The effects of executive, firm, and board characteristics on executive exit. Financ. Rev. 51(4), 527–557 (2016)

    Article  Google Scholar 

  7. Shaffer, M.A., Joplin, J.R., Bell, M.P., Lau, T., Oguz, C.: Gender discrimination and job-related outcomes: a cross-cultural comparison of working women in the United States and China. J. Vocat. Behav. 57(3), 395–427 (2000)

    Article  Google Scholar 

  8. Hirsh, E., Cha, Y.: For law and markets: employment discrimination lawsuits, market performance, and managerial diversity. Am. J. Sociol. 123(4), 1117–1160 (2018)

    Article  Google Scholar 

  9. Murphy, T.: Morgan stanley settles sex-discrimination suit, 12 July 2004. https://www.forbes.com/2004/07/12/cx_tm_0712video3.html

  10. Jokinen, J., Pehkonen, J.: Promotions and earnings – gender or merit? Evidence from longitudinal personnel data. J. Labor Res. 38(3), 306–334 (2017)

    Article  Google Scholar 

  11. Bain, O., Cummings, W.: Academes glass ceiling: societal, professional-organizational, and institutional barriers to the career advancement of academic women. Comp. Educ. Rev. 44(4), 493–514 (2000)

    Article  Google Scholar 

  12. Catalyst, Pyramid: Women in S&P 500 Companies, 1 January 2019. https://www.catalyst.org/knowledge/women-sp-500-companies. Accessed 3 Mar 2019

  13. Bielby, W.T., Baron, J.N.: Men and women at work: sex segregation and statistical discrimination. Am. J. Sociol. 91, 759–799 (1986)

    Article  Google Scholar 

  14. Matsa, D.A., Miller, A.R.: Chipping away at the glass ceiling: gender spillovers in corporate leadership. Am. Econ. Assoc. 101(3), 635–639 (2011). 0002-8282

    Google Scholar 

  15. Olsen, C., Becker, B.E.: Sex discrimination in the promotion process. Ind. Labor Relat. Rev. 36, 624–641 (1983)

    Article  Google Scholar 

  16. Kossek, E.E., Su, R., Wu, L.: “Opting Out” or “Pushed Out”? Integrating perspectives on women’s career equality for gender inclusion and interventions. J. Manag. 43(1), 228–254 (2016)

    Google Scholar 

  17. Niederle, M., Vesterlund, L.: Do women shy away from competition? Do men compete too much? Quart. J. Econ. 122(3), 1067–1101 (2007)

    Article  Google Scholar 

  18. Gjerde, K.A.: The existence of gender-specific promotion standards in the U.S. Manag. Decis. Econ. 23(8), 447–459 (2002)

    Article  Google Scholar 

  19. Lyness, K.S., Heilman, M.E.: When fit is fundamental: performance evaluations and promotions of upper-level female and male managers. J. Appl. Psychol. 91(4), 777–785 (2006)

    Article  Google Scholar 

  20. Vinkenburg, C.J., Engen, M.L., Eagly, A.H., Johannesen-Schmidt, M.C.: An exploration of stereotypical beliefs about leadership styles: is transformational leadership a route to women’s promotion? Leadersh. Quart. 22(1), 10–21 (2011)

    Article  Google Scholar 

  21. McKinsey & Company: Women in the workplace (2015)

    Google Scholar 

  22. Schelling, T.: Models of segregation. Am. Econ. Rev. 59(2), 488–493 (1969)

    Google Scholar 

  23. Waldrop, M.M.: Complexity: The Emerging Science at the Edge of Order and Chaos. Simon and Schuster, New York (1992)

    Google Scholar 

  24. Bonabeau, E.: Agent-based modeling: methods and techniques for simulating human systems. Proc. Natl. Acad. Sci. 99, 7280–7287 (2002)

    Article  Google Scholar 

  25. Gaudiano, P.: Understanding attribution from the inside out (2016). https://www.exchangewire.com/blog/2016/05/16/understanding-attribution-from-the-inside-out/. Accessed 5 Apr 2018

  26. Duzevik, D., Anev, A., Funes, P., Gaudiano, P.: The effects of word-of-mouth: an agent-based simulation of interpersonal influence in social networks. In: 2007 Word of Mouth Research Symposium. Word of Mouth Marketing Association, Las Vegas (2007)

    Google Scholar 

  27. Gaudiano, P.: Agent-based simulation as a tool for the built environment. Ann. N. Y. Acad. Sci. 1295, 26–33 (2013)

    Article  Google Scholar 

  28. Garagic, D., Trifonov, I., Gaudiano, P., Dickason, D.: An agent-based modeling approach for studying manpower and personnel management behaviors. In: Proceedings of the 2007 Winter Simulation Conference, Washington (2007)

    Google Scholar 

  29. Gaudiano, P., Bandte, O., Duzevik, D., Anev, A.: How word-of-mouth impacts medicare product launch and product design. In: 2007 Word of Mouth Research Symposium. Word of Mouth Marketing Association, Las Vegas (2007)

    Google Scholar 

  30. Shargel, B., Bonabeau, E., Budynek, J., Buchsbaum, D., Gaudiano, P.: An evolutionary, agent-based model to aid in computer intrusion detection and prevention. In: Proceedings of the 10th International Command and Control Research and Technology Symposium, MacLean, VA (2005)

    Google Scholar 

  31. Page, S.E.: The Diversity Bonus. Princeton University Press, Princeton (2017)

    Book  Google Scholar 

  32. Bullinaria, J.: Agent-based models of gender inequalities in career progression. J. Artif. Soc. Soc. Simul. 21(3), 1–7 (2018)

    Article  Google Scholar 

  33. Takács, K., Squazzoni, F., Bravo, G.: The network antidote: an agent-based model of discrimination in labor markets. Presented at MKE 2012 Conference, Budapest, Hungary, 20–21 December 2012 (2012)

    Google Scholar 

  34. Robison-Cox, J.F., Martell, R.F., Emrich, C.G.: Simulating gender stratification. J. Artif. Soc. Soc. Simul. 10(3) (2007). http://jasss.soc.surrey.ac.uk/10/3/8.html

  35. Gaudiano, P., Hunt, E.: Equal opportunity or affirmative action? A computer program shows which is better for diversity (2016). Forbes.com. http://www.forbes.com/sites/gaudianohunt/2016/08/22/equal-opportunity-or-affirmative-action-a-computer-program-shows-which-is-better-for-diversity/

  36. Kalev, A., Dobbin, F., Kelly, E.: Best practices or best guesses? Assessing the efficacy of corporate affirmative action and diversity policies. Am. Sociol. Rev. 71(4), 589–617 (2006)

    Article  Google Scholar 

  37. Wilensky, U.: An Introduction to Agent-Based Modeling: Modeling Natural, Social, and Engineered Complex Systems with NetLogo. MIT Press, Cambridge (2015)

    Google Scholar 

  38. North American Employee Turnover: Trends and Effects. https://www.imercer.com/ecommerce/articleinsights/North-American-Employee-Turnover-Trends-and-Effects. Accessed 20 Mar 2019

  39. Naghdi Tam, A.: Agent-based simulation as a tool for examining the impact of a company’s reputation on attracting diverse talent. Unpublished Master’s thesis, City College of New York (2017)

    Google Scholar 

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Author information

Authors and Affiliations

  1. Aleria PBC, New York, USA

    Chibin Zhang & Paolo Gaudiano

  2. Quantitative Studies of Diversity and Inclusion, City College of New York, New York, USA

    Paolo Gaudiano

Authors
  1. Chibin Zhang
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  2. Paolo Gaudiano
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Corresponding author

Correspondence to Paolo Gaudiano .

Editor information

Editors and Affiliations

  1. Faculty of Science and Engineering, Saga University, Saga, Japan

    Kohei Arai

  2. The Science and Information (SAI) Organization, Bradford, West Yorkshire, UK

    Rahul Bhatia

  3. The Science and Information (SAI) Organization, Bradford, West Yorkshire, UK

    Supriya Kapoor

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Zhang, C., Gaudiano, P. (2020). An Agent-Based Simulation of Corporate Gender Biases. In: Arai, K., Bhatia, R., Kapoor, S. (eds) Proceedings of the Future Technologies Conference (FTC) 2019. FTC 2019. Advances in Intelligent Systems and Computing, vol 1069. Springer, Cham. https://doi.org/10.1007/978-3-030-32520-6_9

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