Does the gender of your co-worker matter? Evidence from call centres in India

Gender integration in the workplace may have negative effects on employee productivity (Akerlof and Kranton 2000, Bertrand et al. 2015). This could decrease employee productivity if employees of different genders are (1) uncomfortable or distracted by each other’s presence (Kandel and Lazear 1992), (2) face communication barriers while interacting (Hamilton et al. 2012), (3) socialise and date more within the organisation due to lack of alternate avenues to meet new people. On the other hand, there could be mutual learning and knowledge spillovers (Hamilton et al. 2012).

Does the gender of one's co-worker matter? The question is especially pertinent in a traditional-country setting where gender roles are more rigid. Often in such traditional settings, prolonged interactions with members of a different gender as equals and outside of family, happens in the workplace. I conduct an experiment in call centres located in five Indian (four small cities and one metropolitan city) cities (Batheja 2020).[1] Using matched pair randomisation[2] on past productivity, I randomise call centre employees or customer sales representatives into mixed gender (30-50% females) and same gender teams. A total of 765 employees (297 male employees in mixed-gender teams, 320 in all-male teams; 67 female employees in mixed-gender teams, and 81 in all-female teams) were seated with their new teams for a median of 12 weeks.[3] Male and female co-workers in mixed-gender teams were mapped to sit on alternate seats to intensify exposure to different gender.

There are many advantages to choosing call centres to conduct this experiment about the impact of gender composition of team members on employee performance. First, despite being male-dominated, the call centres or the Business Process Outsourcing (BPO) sector employs large number of female employees at the agent level (entry-level jobs involving making calls as customer support representatives) due to their comparative advantage in interpersonal skills (Jensen 2012). The second reason for choosing this setting is that these are entry-level jobs and employ young people with low prior exposure to different gender. The average age of an agent is around 21 years in my sample. A third reason is that there are uniform and consistent measures of productivity for all workers in this setting, which may not be the case for some other work settings.

I have detailed and complete daily-level measures of individual productivity, which is internally collected using technology-based automatic data collection in the call centres. The top three productivity indicators are chosen depending on the nature of the businesses/processes after discussion and consensus with the call centre’s senior management. These include average call handling time, number of calls answered, sales made, and so on. After combining these three productivity indicators, the aggregate productivity is ‘standardised’[4] within each process. This makes the productivity indicator comparable across all processes. At the extensive margin, I look at share of days worked during the course of the study period from the day of appearing in the study. This is an unconditional measure based on showing up to work so there are no selection concerns.[5]

Does team matter in call centres?

A team is an important entity in call centres. In a typical call centre, customer support employees or agents are grouped to form teams, and agents interact with their team members on a daily basis in team meetings. As it is standard practice in call centres for teams to be seated together, changing the gender composition of teams leads to a change in the gender composition of peers seated around a worker.[6] Workers interact with agents sitting next to them if they get stuck on a call and the team leader or manager is not around. Approximately, 66% of the respondents in the baseline survey agree that they learnt something from the agents sitting next to them. When asked about whose help they seek when stuck on a call, a vast majority of agents responded that they took help from the team leader (67%), followed by agents seated nearby (27%), and then others (6%). The importance of peer effect in this setting is supported by evidence from the economics literature that low-skilled or routine tasks have significant and larger peer effects than high-skilled jobs (Cornelissen et al. 2017, Ichino and Falk 2005, Bandiera et al. 2010).

Main finding: Not costly for firms to integrate women into all-male workplaces

• Do different gender peers decrease male productivity? There is no negative impact on either productivity or share of days worked during the study period, of being assigned to a mixed gender team for male employees. In general, there is evidence of gender discrimination in hiring practices in India, which is a potential cause of low female labour force participation rates of women (Chowdury et al. 2018). Additionally, the fastest growing sectors such as telecom and banking are dominated by men. Most of these firms have not undertaken any hiring initiatives to improve the situation (India Skills Report, 2017). These male-dominated sectors might be sceptical about hiring women, and the low representation of females in the senior management might be further increasing the entry barriers for women in these workplaces (Goldin 2014, Chowdhury et al. 2018). Given that I find precisely estimated zero effects on productivity, these are important findings providing supportive evidence for integrating women into workplace, without any additional costs to the firms.
• Are these results similar across all kinds of male employees? I find that conditional on being assigned to mixed-gender teams, male employees with progressive gender attitudes have significantly higher productivity than those with regressive gender attitudes.[7] This finding is consistent with theories on social identity and taste-based employee discrimination.

• Was there any knowledge spillover or learning from different gender peers at all? There is a 0.3 standard deviation[8] increase in knowledge sharing for male employees, which is a survey response for if the employee benefitted from agents sitting nearby on work-related issues. I do not find any evidence of knowledge spillover for women. This could be because, on average, women were more productive than men at the baseline.

• What about incidence of dating among these young workers? The male employees assigned to mixed-gender teams report 19 percentage points higher incidence of dating than those in all-male teams at the endline. Around 54% of the male employees assigned to all-male teams report to be dating, but not married, at the endline. So, there was an increase of 35% in dating for male employees assigned to mixed-gender teams compared to those in the control teams. In India, family elders arrange more than 90% of the marriages, and most of these are intra-caste (Centre for Monitoring Indian Economy, 2018). The increase in dating for men in mixed-gender teams in the setting of small-town India, is therefore an important finding. Interestingly, the result on dating is driven by relatively progressive men in the mixed-gender teams.

• Was gender integration in the workplace useful for female employees? Here also, I find that there is no overall impact on either productivity or share of days worked during the study period of being assigned to a mixed-gender team for female employees. However, these are less precisely estimated results, as there are fewer women in the sample because these workplaces are male-dominated. The next concern was whether these women are comfortable working in these male-dominated workplaces. For female employees, there is an increase in peer monitoring and comfort for those assigned to mixed-gender teams. The female workers in mixed teams received 0.2 standard deviations more peer monitoring and support relative to those in all-female teams. 

Implications for policy and research

These findings are important for both researchers and policymakers. They provide evidence in the under-studied subject of taste-based employee discrimination. Additionally, research on productivity improvements in this high-growth, largest private-sector employer is crucial for sustainable job creation for many young workers, particularly women. Policymakers in India are interested in further expanding these call centres to smaller cities and villages and are providing special incentives to firms to hire women. Some of the call centres, which are a part of the study, receive a subsidy from the central government (India BPO Promotion Scheme (IBPS)) for hiring female employees. The findings provide supportive evidence to strengthen the objective of the policymakers to boost female labour supply and empowerment in the country, by showing that integrating women in the workplace does not lead to an overall loss in productivity. It could in fact lead to increases in productivity if the male employees have progressive gender attitudes.

Editor’s note: This article was published in collaboration with Ideas for India and is based on this IGC project.

[1] The field experiment took place in two Indian call centre companies: Call-2-Connect India Pvt. Ltd., and Five Splash Infotech Pvt. Ltd. Call2Connect India Pvt. Ltd. has centres in the states of Bihar (Patna), Uttar Pradesh (Noida), and Maharashtra (Mumbai). Five Splash Infotech Pvt. Ltd. has centres in the states of Rajasthan (Udaipur) and Karnataka (Hubli). All of these five cities/locations are a part of the study. Out of the chosen locations, Mumbai is the most developed and is categorised as a metropolitan and Tier-1 city. Hubli, Noida, and Patna are less urbanised and are in the Tier-2 category. Udaipur is in the Tier-3 category. The call centres in this study serve domestic customers and therefore, employees have to speak in the local language.

[2] In matched pair randomisation method, two units are matched on a list of important characteristics and then, one of them is randomly assigned to ‘treatment’ (subjected to intervention) and the other to ‘control’ (not subjected to intervention). In this study, I match employees on the basis of gender and past productivity (using 3-4 weeks of pre-study administrative data) and then randomly assign one of them to mixed gender team and the other to control.

[3] In centres where 25-30% of the employees were women, only mixed gender teams and all male teams were formed. The women who were part of those mixed gender teams did not have relevant control group of all-female teams. Therefore, these women are not included in the study. In the centres where women constituted 45% of the employees, all the three groups of mixed teams, all male and all female teams could be formed. In these cases, both male and female employees were a part of the study. The study has a higher number of male employees due to low proportion of female employees in the sample (even though this is a sector that hires more women in general, as mentioned above). This is because the female labour force participation rate is low in India so there are fewer women in the workplace relative to men.

[4] Since I use an index of three top variables for the productivity outcome, standardisation is a method that I use to bring the productivity variables to the same scale. This makes the productivity index comparable across centres, and easily interpretable as deviations from the control group’s average.

[5] Share of days worked is the proportion of days worked in the study period (from the employee's job starting date) out of the total number of days of the study. This is a measure of attendance, which is regardless of the work status and is therefore called an unconditional measure of attendance (also includes the measure of retention). If we were to study attendance from the study start-date or job-start date to the employee’s last day of work, then such a conditional measure of attendance will fail to account for attrition. So, there could arise selection concerns/biases if a large number of employees in the treatment or control group show up to work despite being unhappy but then suddenly quit. The conditional measure of attendance will not be able to capture this effect but the unconditional measure combining both attendance and attrition, will be able to successfully capture this.

[6] There was no fixed method of forming teams in these call centres. but shuffling and rebuilding of teams was common. In many centres, fixed seating was not practiced. So, employees would need to find vacant seats to work from, every morning.

[7] To assess gender attitudes of the males in the study, a broad set of questions were posed to them, based on the current literature on measuring women’s empowerment and gender attitudes (Dhar et al. 2018, Glennerster et al. 2018). The questions broadly pertain to gender attitudes with respect to education, employment, fertility, and traditional gender roles. For example: “Should the wife be less educated than her husband?”

[8] Standard deviation is a measure that is used to quantify the amount of variation or dispersion of a set of values from the mean value (average) of that set.