Advertisement

Sex Roles

pp 1–13 | Cite as

Solidarity in STEM: How Gender Composition Affects Women’s Experience in Work Teams

  • Ashley A. NilerEmail author
  • Raquel Asencio
  • Leslie A. DeChurch
Original Article

Abstract

The relationships among the percentage of women in a team and women’s sense of team identification and collective efficacy as well as team performance was examined. We explored these relationships in a sample of student teams conducting a semester-long social science research project within the context of science and technology-focused university. Findings with 95 U.S. college students (43 women) show that women experience higher team identification and collective efficacy as the percent of women teammates increases. Additionally, women’s team identification and collective efficacy mediate the relationship between the percentage of women on the team and overall team performance. Interestingly, the number of men on the team did not influence men’s sense of team identification, collective efficacy, or team performance. This research has implications for team composition. Specifically, when navigating diversity in teams, managers and leaders should aim to build teams that are composed of multiple women versus an approach that divides women up among various teams. In doing so, managers can better secure conditions for the development of positive teamwork experiences and, ultimately, performance.

Keywords

Gender equality Identification Collective efficacy theory STEM Team composition 

Notes

Acknowledgements

The present material is based upon work supported by the National Science Foundation grant SBE-1063901, National Science Foundation grant SES-SBE 1219469, and the Army Research Office grant W911NF-14-10686, and in association with the Purdue Brock-Wilson Center for Women in Management.

Compliance with Ethical Standards

We would like to note that this is an original work, not published or submitted elsewhere, and there are no conflicts of interest (either financial or non-financial). This research was supported by the National Science Foundation grant SBE-1063901, National Science Foundation grant SES-SBE 1219469, and the Army Research Office grant W911NF-14-10686. Additionally, this work was presented at the 2016 Interdisciplinary Network for Group Research annual conference. This research involved human subjects, who consented to participation in this study.

References

  1. Acker, S., & Oatley, K. (1993). Gender issues in education for science and technology: Current situation and prospects for change. Canadian Journal of Education/Revue Canadienne de L’éducation, 18(3), 255–272.  https://doi.org/10.2307/1495386.Google Scholar
  2. Bandura, A. (1997). Self-efficacy: The exercise of control. New York: Freeman.Google Scholar
  3. Baugh, S. G., & Graen, G. B. (1997). Effects of team gender and racial composition on perceptions of team performance in cross-functional teams. Group & Organization Management, 22(3), 366–383.  https://doi.org/10.1177/1059601197223004.Google Scholar
  4. Bear, J. B., & Woolley, A. W. (2011). The role of gender in team collaboration and performance. Interdisciplinary Science Reviews, 36(2), 146–153.  https://doi.org/10.1179/030801811X13013181961473.Google Scholar
  5. Beede, D. N., Julian, T. A., Langdon, D., McKittrick, G., Khan, B., & Doms, M. E. (2011). Women in STEM: A gender gap to innovation. Economics and Statistics Administration Issue Brief, 4–11.  https://doi.org/10.2139/ssrn.1964782.
  6. Betz, N. E., & Hackett, G. (1997). Applications of self-efficacy theory to the career assessment of women. Journal of Career Assessment, 5(4), 383–402.  https://doi.org/10.1177/106907279700500402.Google Scholar
  7. Bezrukova, K., Jehn, K. A., Zanutto, E. L., & Thatcher, S. M. (2009). Do workgroup faultlines help or hurt? A moderated model of faultlines, team identification, and group performance. Organization Science, 20(1), 35–50.  https://doi.org/10.1287/orsc.1080.0379.Google Scholar
  8. Bliese, P. D. (1998). Group size, ICC values, and group-level correlations: A simulation. Organizational Research Methods, 1(4), 355–373.  https://doi.org/10.1177/109442819814001.Google Scholar
  9. Bowers, C. A., Pharmer, J. A., & Salas, E. (2000). When member homogeneity is needed in work teams a meta-analysis. Small Group Research, 31(3), 305–327.  https://doi.org/10.1177/104649640003100303.Google Scholar
  10. Burleigh, N. (2015). What Silicon Valley thinks of women. Retrieved October 19, 2018, from http://www.newsweek.com/2015/02/06/what-silicon-valley-thinks-women-302821.html.
  11. Catalyst. (2017, March 16). Women on corporate boards globally. Retrieved October 19, 2018, from http://www.catalyst.org/knowledge/women-corporate-boards-globally.
  12. Catsambis, S. (1995). Gender, race, ethnicity, and science education in the middle grades. Journal of Research in Science Teaching, 32(3), 243–257.  https://doi.org/10.1002/tea.3660320305.Google Scholar
  13. Chen, G., Gully, S., & Eden, D. (2001). Validation of a new general self-efficacy scale. Organizational Research Methods, 4(1), 62–83.  https://doi.org/10.1177/109442810141004.Google Scholar
  14. Cheryan, S., Ziegler, S. A., Montoya, A. K., & Jiang, L. (2017). Why are some STEM fields more gender balanced than others? Psychological Bulletin, 143(1), 1–35.  https://doi.org/10.1037/bul0000052.Google Scholar
  15. Cohen, L. L., & Swim, J. K. (1995). The differential impact of gender ratios on women and men: Tokenism, self-confidence, and expectations. Personality and Social Psychology Bulletin, 21(9), 876–876.  https://doi.org/10.1177/0146167295219001.Google Scholar
  16. Crenshaw, K. (1989). Demarginalizing the intersection of race and sex: A Black feminist critique of antidiscrimination doctrine, feminist theory and antiracist politics. University of Chicago Legal Forum, 139–167.Google Scholar
  17. Damore, J. (2017). Google’s ideological echo chamber: How bias clouds our thinking about diversity and inclusion. Retrieved on October 19, 2018 https://assets.documentcloud.org/documents/3914586/Googles-Ideological-Echo-Chamber.pdf.
  18. Dasgupta, N., Scircle, M. M., & Hunsinger, M. (2015). Female peers in small work groups enhance women’s motivation, verbal participation, and career aspirations in engineering. Proceedings of the National Academy of Sciences, 112(16), 4988–4993.  https://doi.org/10.1073/pnas.1422822112.Google Scholar
  19. Dolan, K. (1997). Gender differences in support for women candidates: Is there a glass ceiling in American politics? Women & Politics, 17(2), 27–41.  https://doi.org/10.1300/J014v17n02_02.Google Scholar
  20. Eagly, A. H. (1987). Reporting sex differences. American Psychologist, 42(7), 756–757.Google Scholar
  21. Eagly, A. H. (2007). Female leadership advantage and disadvantage: Resolving the contradictions. Psychology of Women Quarterly, 31(1), 1–12.  https://doi.org/10.1111/j.1471-6402.2007.00326.x.Google Scholar
  22. Eagly, A. H., & Carli, L. L. (2003). The female leadership advantage: An evaluation of the evidence. The Leadership Quarterly, 14(6), 807–834.  https://doi.org/10.1016/j.leaqua.2003.09.004.Google Scholar
  23. Eagly, A. H., & Johnson, B. T. (1990). Gender and leadership style: A meta-analysis. Psychological Bulletin, 108(2), 233–256.Google Scholar
  24. Eagly, A. H., & Karau, S. J. (1991). Gender and the emergence of leaders: A meta-analysis. Journal of Personality and Social Psychology, 60(5), 685–710.Google Scholar
  25. Eagly, A. H., Karau, S. J., & Makhijani, M. G. (1995). Gender and the effectiveness of leaders: A meta-analysis. Psychological Bulletin, 117(1), 125–145.Google Scholar
  26. Eagly, A. H., Eaton, A., Rose, S. M., Riger, S., & McHugh, M. C. (2012). Feminism and psychology: Analysis of a half-century of research on women and gender. American Psychologist, 67(3), 211–230.Google Scholar
  27. Earley, C. P., & Mosakowski, E. (2000). Creating hybrid team cultures: An empirical test of transnational team functioning. Academy of Management Journal, 43(1), 26–49.  https://doi.org/10.5465/1556384.Google Scholar
  28. Eckel, C. C., & Grossman, P. J. (2005). Managing diversity by creating team identity. Journal of Economic Behavior & Organization, 58(3), 371–392.  https://doi.org/10.1016/j.jebo.2004.01.003.Google Scholar
  29. Etzkowitz, H., Kemelgor, C., Neuschatz, M., Uzzi, B., & Alonzo, J. (1994). The paradox of critical mass for women in science. Science, 266(5182), 51–54.Google Scholar
  30. Fernández-Ballesteros, R., Díez Nicolás, J., Caprara, G. V., Barbaranelli, C., & Bandura, A. (2002). Determinants and structural relation of personal efficacy to collective efficacy. Applied Psychology, 51(1), 107–125.  https://doi.org/10.1111/1464-0597.00081.Google Scholar
  31. Greer, L., & Bendersky, C. (2013). Power and status in conflict and negotiation research: Introduction to the special issue. Negotiation and Conflict Management Research, 6(4), 239–252.  https://doi.org/10.1111/ncmr.12021.Google Scholar
  32. Hackett, G., & Betz, N. E. (1981). A self-efficacy approach to the career development of women. Journal of Vocational Behavior, 18(3), 326–339.  https://doi.org/10.1016/0001-8791(81)90019-1.Google Scholar
  33. Hackman, J. R. (1987). The design of work teams. In J. W. Lorsch (Ed.), Handbook of organizational behavior (pp. 315–342). Englewood Cliffs, NJ: Prentice Hall.Google Scholar
  34. Heilman, M. E. (2001). Description and prescription: How gender stereotypes prevent women’s ascent up the organizational ladder. Journal of Social Issues, 57(4), 657–674.Google Scholar
  35. Heilman, M. E., & Eagly, A. H. (2008). Gender stereotypes are alive, well, and busy producing workplace discrimination. Industrial and Organizational Psychology, 1(4), 393–398.  https://doi.org/10.1111/0022-4537.00234.Google Scholar
  36. Heilman, M. E., & Haynes, M. C. (2005). No credit where credit is due: Attributional rationalization of women's success in male-female teams. Journal of Applied Psychology, 90(5), 905–916.Google Scholar
  37. Hill, C., Corbett, C., & St Rose, A. (2010). Why so few? Women in science, technology, engineering, and mathematics. Washington, DC: American Association of University Women. https://www.aauw.org/files/2013/02/Why-So-Few-Women-in-Science-Technology-Engineering-and-Mathematics.pdf. Accessed 18 March 2019.
  38. Hinds, P. J., & Mortensen, M. (2005). Understanding conflict in geographically distributed teams: The moderating effects of shared identity, shared context, and spontaneous communication. Organization Science, 16(3), 290–307.  https://doi.org/10.1287/orsc.1050.0122.Google Scholar
  39. Hoogendoorn, S., Oosterbeek, H., & Van Praag, M. (2013). The impact of gender diversity on the performance of business teams: Evidence from a field experiment. Management Science, 59(7), 1514–1528.  https://doi.org/10.1287/mnsc.1120.1674.Google Scholar
  40. Hu, L. T., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6(1), 1–55.  https://doi.org/10.1080/10705519909540118.Google Scholar
  41. Huang, C. Y., Huang, J. C., & Chang, Y. (2017). Team goal orientation composition, team efficacy, and team performance: The separate roles of team leader and members. Journal of Management & Organization. Advance online publication.  https://doi.org/10.1017/jmo.2016.62.
  42. Hyde, J. S., Lindberg, S. M., Linn, M. C., Ellis, A. B., & Williams, C. C. (2008). Gender similarities characterize math performance. Science, 321(5888), 494–495.  https://doi.org/10.1126/science.1160364.Google Scholar
  43. James, L. R. (1982). Aggregation bias in estimates of perceptual agreement. Journal of Applied Psychology, 67(2), 212–229.Google Scholar
  44. James, L. R., Demaree, R. G., & Wolf, G. (1984). Estimating within-group interrater reliability with and without response bias. Journal of Applied Psychology, 69(1), 85–98.  https://doi.org/10.1037/0021-9010.69.1.85.Google Scholar
  45. James, L. R., Mulaik, S. A., & Brett, J. M. (2006). A tale of two methods. Organizational Research Methods, 9(2), 233–244.  https://doi.org/10.1177/1094428105285144.Google Scholar
  46. Johns, G. (2018). Advances in the treatment of context in organizational research. Annual Review of Organizational Psychology and Organizational Behavior, 5, 21–46.  https://doi.org/10.1146/annurev-orgpsych-032117-104406.Google Scholar
  47. Jones, B. F. (2009). The burden of knowledge and the “death of the renaissance man”: Is innovation getting harder? The Review of Economic Studies, 76(1), 283–317.  https://doi.org/10.1111/j.1467-937X.2008.00531.x.Google Scholar
  48. Joshi, A. (2014). By whom and when is women’s expertise recognized? The interactive effects of gender and education in science and engineering teams. Administrative Science Quarterly, 59(2), 202–239.  https://doi.org/10.1177/0001839214528331.Google Scholar
  49. Kenny, D. A., & La Voie, L. (1984). The social relations model. Advances in Experimental Social Psychology, 18, 141–182.  https://doi.org/10.1016/S0065-2601(08)60144-6.Google Scholar
  50. Konrad, A. M., Kramer, V., & Erkut, S. (2008). Critical mass: The impact of three or more women on corporate boards. Organizational Dynamics, 37(2), 145–164.  https://doi.org/10.1016/j.orgdyn.2008.02.005.Google Scholar
  51. Krishnan, H. A., & Park, D. (2005). A few good women—on top management teams. Journal of Business Research, 58(12), 1712–1720.  https://doi.org/10.1016/j.jbusres.2004.09.003.Google Scholar
  52. Lewin, A. Y., & Duchan, L. (1971). Women in academia. Science, 173(4000), 892–895.  https://doi.org/10.1126/science.173.4000.892.Google Scholar
  53. Lindsley, D. H., Brass, D. J., & Thomas, J. B. (1995). Efficacy-performing spirals: A multilevel perspective. Academy of Management Review, 20(3), 645–678.  https://doi.org/10.5465/AMR.1995.9508080333.Google Scholar
  54. Little, B. L., & Madigan, R. M. (1997). The relationship between collective efficacy and performance in manufacturing work teams. Small Group Research, 28(4), 517–534.  https://doi.org/10.1177/1046496497284003.Google Scholar
  55. Lungeanu, A., Huang, Y., & Contractor, N. S. (2014). Understanding the assembly of interdisciplinary teams and its impact on performance. Journal of Informetrics, 8(1), 59–70.  https://doi.org/10.1016/j.joi.2013.10.006.Google Scholar
  56. Mesmer-Magnus, J. R., Asencio, R., Seely, P. W., & DeChurch, L. A. (2015). How organizational identity affects team functioning: The identity instrumentality hypothesis. Journal of Management, 41(7), 1–21.  https://doi.org/10.1177/0149206315614370.Google Scholar
  57. Metcalfe, B., & Linstead, A. (2003). Gendering teamwork: Re-writing the feminine. Gender, Work and Organization, 10(1), 94–119.  https://doi.org/10.1111/1468-0432.00005.Google Scholar
  58. Moss-Racusin, C. A., Dovidio, J. F., Brescoll, V. L., Graham, M. J., & Handelsman, J. (2012). Science faculty’s subtle gender biases favor male students. Proceedings of the National Academy of Sciences, 109(41), 16474–16479.  https://doi.org/10.1073/pnas.1211286109.Google Scholar
  59. Murase, T., Carter, D. R., DeChurch, L. A., & Marks, M. A. (2014). Mind the gap: The role of leadership in multiteam system collective cognition. The Leadership Quarterly, 25(5), 972–986.  https://doi.org/10.1016/j.leaqua.2014.06.003.Google Scholar
  60. Nielsen, M. W., Alegria, S., Börjeson, L., Etzkowitz, H., Falk-Krzesinski, H. J., Joshi, A., ... Schiebinger, L. (2017). Opinion: Gender diversity leads to better science. Proceedings of the National Academy of Sciences, 114(8), 1740–1742.Google Scholar
  61. Oakes, P. J. (1987). The salience of social categories. In J. C. Turner (Ed.), Rediscovering the social group: A self-categorization theory (pp. 117–141). New York: Basil Blackwell.Google Scholar
  62. Piazza, A., & Castellucci, F. (2014). Status in organization and management theory. Journal of Management, 40(1), 287–315.  https://doi.org/10.1177/0149206313498904.Google Scholar
  63. Rosseel, Y. (2012). lavaan: An R package for structural equation modeling. Journal of Statistical Software, 48(2), 1–36.Google Scholar
  64. Settles, I. (2014, October). Women in STEM: Challenges and determinants of success and wellbeing. Psychological Science Agenda. Retrieved on October 19, 2018, from http://www.apa.org/science/about/psa/2014/10/women-stem.aspx.
  65. Shih, J. (2006). Circumventing discrimination gender and ethnic strategies in Silicon Valley. Gender & Society, 20(2), 177–206.  https://doi.org/10.1177/0891243205285474.Google Scholar
  66. Smith-Crowe, K., Burke, M. J., Cohen, A., & Doveh, E. (2014). Statistical significance criteria for the r WG and average deviation interrater agreement indices. Journal of Applied Psychology, 99(2), 239–261.  https://doi.org/10.1037/a0034556.Google Scholar
  67. Stajkovic, A. D., Lee, D., & Nyberg, A. J. (2009). Collective efficacy, group potency, and group performance: Meta-analyses of their relationships, and test of a mediation model. Journal of Applied Psychology, 94(3), 814–828.  https://doi.org/10.1037/a0015659.Google Scholar
  68. Steele, C. M. (1997). A threat in the air: How stereotypes shape intellectual identity and performance. American Psychologist, 52(6), 613–629.Google Scholar
  69. Tajfel, H. (1978). Social categorization, social identity and social comparison. In H. Tajfel (Ed.), Differentiation between social groups: Studies in the social psychology of intergroup relations (pp. 61–76). London: Academic Press.Google Scholar
  70. Tajfel, J., & Turner, J. C. (1986). The social identity theory of intergroup behavior. In S. Worchel & G. Austin (Eds.), Psychology of intergroup relations (pp. 7–24). Chicago: Nelson-Hall.Google Scholar
  71. Tasa, K., Taggar, S., & Seijts, G. H. (2007). The development of collective efficacy in teams: A multilevel and longitudinal perspective. Journal of Applied Psychology, 92(1), 17–27.  https://doi.org/10.1037/0021-9010.92.1.17.Google Scholar
  72. van Knippenberg, D. (2000). Work motivation and performance: A social identity perspective. Applied Psychology, 49(3), 357–371.  https://doi.org/10.1111/1464-0597.00020.Google Scholar
  73. Wang, X. H. F., & Howell, J. M. (2012). A multilevel study of transformational leadership, identification, and follower outcomes. The Leadership Quarterly, 23(5), 775–790.  https://doi.org/10.1016/j.leaqua.2012.02.001.Google Scholar
  74. Wasserman, S., & Faust, K. (1994). Social network analysis: Methods and applications. Cambridge: Cambridge University Press.Google Scholar
  75. Woolley, A., & Malone, T. (2011). What makes a team smarter? More women. Harvard Business Review, 89(6), 32–33.Google Scholar
  76. Woolley, A. W., Chabris, C. F., Pentland, A., Hashmi, N., & Malone, T. W. (2010). Evidence for a collective intelligence factor in the performance of human groups. Science, 330(6004), 686–688.  https://doi.org/10.1126/science.1193147.Google Scholar
  77. Wright, D. B., Eaton, A. A., & Skagerberg, E. (2015). Occupational segregation and psychological gender differences: How empathizing and systemizing help explain the distribution of men and women into (some) occupations. Journal of Research in Personality, 54, 30–39.  https://doi.org/10.1016/j.jrp.2014.06.004.Google Scholar
  78. Wuchty, S., Jones, B. F., & Uzzi, B. (2007). The increasing dominance of teams in production of knowledge. Science, 316(5827), 1036–1039.  https://doi.org/10.1126/science.1136099.Google Scholar
  79. Zaccaro, S. J., Blair, V., Peterson, C., & Zazanis, M. (1995). Collective efficacy. In J. E. Maddux (Ed.), Self-efficacy, adaptation, and adjustment (pp. 305–328). New York: Plenum Press.Google Scholar
  80. Zeldin, A. L., & Pajares, F. (2000). Against the odds: Self-efficacy beliefs of women in mathematical, scientific, and technological careers. American Educational Research Journal, 37(1), 215–246.  https://doi.org/10.3102/00028312037001215.Google Scholar
  81. Zeldin, A. L., Britner, S. L., & Pajares, F. (2008). A comparative study of the self-efficacy beliefs of successful men and women in mathematics, science, and technology careers. Journal of Research in Science Teaching: The Official Journal of the National Association for Research in Science Teaching, 45(9), 1036–1058.  https://doi.org/10.1002/tea.20195.Google Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.The School of CommunicationNorthwestern UniversityEvanstonUSA
  2. 2.Krannert School of Management, Jane Brock-Wilson Women in Management CenterPurdue UniversityWest LafayetteUSA

Personalised recommendations