Observers have long noted that women are underrepresented in the young, fast-growing firms that dot Silicon Valley. Now, a six-year study of high-tech startups identifies factors that can predict how hospitable firms are to women and challenges the common assumption that access for women is uniformly low across technology firms.
While software and telecommunications companies are less inviting to women in scientific and technical roles than are biotech, medical device, and research firms, Business School Professor Michael Hannan and James Baron of the Yale University School of Management say that an even greater predictor of how women will fare may be how the founder decided to organize a firm early in its history.
In research conducted with Greta Hsu and Ozgecan Kocak, both graduates of the school's doctoral program, they discovered that the fewest scientific and technical women are found in those firms started along what the researchers call "the commitment model," in which employees are chosen based on their fit with the company's culture, motivated by their emotional attachment to the firm, and controlled by their peer group. Firms that value individual achievement and do not require an emotional attachment have more women. The evidence suggests that differences in hiring, rather than in attrition rates, account for women's underrepresentation in high-commitment firms. Baron says that it may not be high-commitment cultures in isolation that are adverse to women, but rather the particular types of commitments required by the high-tech Silicon Valley companies they studied.
The researchers also found that the largest numbers of women are employed in technical and scientific roles within companies that are larger, growing more rapidly, and competing primarily through technological innovation. These companies also tend to be post-IPO, which means they are offering less lucrative opportunities than ground-zero startups that often award stock options to employees before a public offering takes place. The companies with more women in scientific and technical roles also tended to have already gone public and had hired a full-time human resources employee or adopted an affirmative action plan. The results suggest that women are hired more rapidly into firms experiencing changes that require formal employment policies.
Baron, the Walter Kenneth Kilpatrick Professor of Organizational Behavior and Human Resources, and Hannan, the StrataCom Professor of Management and a professor of sociology in the School of Humanities and Sciences, based their study on data gathered through the Stanford Project on Emerging Companies (SPEC), which has studied the evolution of 167 high-tech startups since 1994. Overall, firms in the study had the greatest concentration of women in clerical positions (on average, 91 percent female), followed by administrators (54 percent), sales and marketing (28 percent), technical roles (17 percent), and senior management (14 percent).
The research by Baron and his collaborators also suggests that the effects of female leadership on the hiring of women into technical roles depend on where the women are located within senior management. Surprisingly, they found that women's overall presence in senior management has little effect on the number of women within the firm - possibly because across all the firms, senior women are concentrated in HR and administrative positions (33 percent), with very few overseeing engineering or R&D (4 percent). In fact, only one in ten of the firms had had a woman in the CEO, president, or founder slot. However, firms in which a woman had occupied one of those top positions - or had overseen the engineering or R&D function - were significantly more likely to employ women in scientific and technical positions.
Past research on the gender mix within organizations has suggested that women tend to fare better in firms in which their relative numbers are currently highest. The SPEC team's findings suggest, however, that decisions made early in the life of an organization are no less profound in predicting the current extent of gender inequality.