Effective Communication Methods for Diverse Teams Vary Depending on the Gender Makeup of Group Members

A new study led by a scholar at the University of Michigan finds the effectiveness of communication methods for diverse teams varies depending on the gender and racial/ethnic makeup of team members.

The researchers conducted a lab experiment with 46 teams performing a decision-making task. The teams were assigned to work on an admissions exercise to determine who should be admitted to a university. In the experiment, half of the teams used face-to-face communication and the other half used text.

Recent research has shown that text-messaging is the most effective communications method for racially diverse teams rather than face-to-face communications. This research confirmed that result. The authors state that texting can rid the environment of visual and vocal cues that can lead to stereotypes and other negative factors that get in the way. Race disappears somewhat online, which makes text messages work among racially diverse people.

However, the authors found that when it came to teams that were diverse along gender lines, using text messages had the opposite impact. Lionel Robert, associate professor at the University of Michigan’s School of Information and the lead author of the study, stated that the reason text doesn’t work across gender lines, is that the online environment historically has been a hostile one for women, and it can be even more so in the decision-making process, causing them to be less inclined to participate.

“What we began to see is natural tendency for men to be more aggressive,” Dr. Robert said. “Women are more polite than men online, so that impact is heightened in decision-making settings. Men are tone-deaf in general but are worse online. They become more aggressive, more rude.”

The full study “Differences are Different: Examining the Effects of Communication Media on the Impacts of Racial and Gender Diversity in Decision-Making Teams,” was published on the website of the journal Information Systems Research. It may be accessed here. Co-authors of the study are Alan Dennis of Indiana University and Manju Ahuja of the University of Louisville.