Journal of Leadership &
Organizational Studies
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Gender Diversity, Business-Unit Engagement, and Performance
Sangeeta Badal and James K. Harter
Journal of Leadership & Organizational Studies 2014 21: 354 originally published online 23 September 2013
DOI: 10.1177/1548051813504460
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JLOXXX10.1177/1548051813504460Journal of Leadership & Organizational StudiesBadal and Harter
research-article2013
Article
Gender Diversity, Business-Unit
Engagement, and Performance
Journal of Leadership &
Organizational Studies
2014, Vol. 21(4) 354–365
© The Authors 2013
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DOI: 10.1177/1548051813504460
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Sangeeta Badal1 and James K. Harter1
Abstract
This study investigates the relationship between gender diversity and financial performance at the business-unit level and
whether employee engagement moderates this relationship. Using more than 800 business units from two companies
belonging to two different industries, we found that employee engagement and gender diversity independently predict
financial performance at the business-unit level. One implication is that making diversity an organizational priority and
creating an engaged culture for the workforce may result in cumulative financial benefits.
Keywords
gender diversity, employee engagement, business-unit performance
Over the past 25 years, the percentage of women in the U.S.
workforce has steadily increased. Today women are almost
on par with men in the workforce (53.4% men and 46.6%
women; U.S. Department of Labor, 2011a). This demographic shift, prompted by the civil rights movement and
promoted by government legislation, has led to an increased
interest among businesses in managing diversity issues
effectively (Kochan et al., 2003; Mannix & Neale, 2005).
Private businesses quickly realized that fulfilling the legal
mandates is not enough, and the diversity movement shifted
from “valuing diversity” to a much more focused approach
emphasizing the “business utility” for supporting diversity
(Mannix & Neale, 2005). The business utility approach
states that a more diverse workforce promotes innovation
and creativity and allows the organization to be competitive
in the global marketplace (Jehn & Bezrukova, 2004;
Myaskovsky, Unikel, & Dew, 2005).
The research exploring linkages between diversity and
performance has shown contradictory results. One view of
diversity states that team-heterogeneity creates value and
has a positive impact on business-unit processes due to the
unique cognitive resources that team members bring to the
team (Cox & Blake, 1991; Easley, 2001; Frink et al., 2003;
Hambrick, Cho, & Chen, 1996; Horwitz, 2005; Kochan et
al., 2003; Mannix & Neale, 2005). Another view of diversity states that homogenous groups generate better communication, are more cohesive, have less conflict, and are more
productive (Ancona & Caldwell, 1992; Böhren & Ström,
2005; Campbell & Mínguez-Vera, 2008; Gallego-Alvarez
et al., 2009; Jimeno & Redondo, 2007; Konrad, Winter, &
Gutek, 1992; Milliken & Martins, 1996; O’Reilly, Caldwell,
& Barnett, 1989; Rose, 2007; Tsui, Egan, & O’Reilly, 1992;
Wharton & Baron, 1987, 1991; Williams & O’Reilly, 1998).
Some experts suggest that the relationship between diversity and performance is both theoretically and empirically
more complex than captured by any one perspective and
thus it is important to consider the effect of context, such as
interpersonal congruence, employee engagement levels,
and human resource practices on the diversity-performance
relationship (Carter, D’Souza, Simkins, & Simpson, 2007;
Horwitz, 2005; Kochan et al., 2003; Pelled, 1996; Pelled,
Eisenhardt, & Xin, 1999).
In this study, we seek to address two major research
goals: our main goal is to further our understanding of the
gender diversity–performance relationship by testing the
impact of gender diversity, a key surface-level observable
attribute, on the financial bottom-line of businesses. We specifically chose to focus just on gender diversity, as studies
have shown that it is better to treat each demographic diversity variable as a distinct theoretical construct. Combining
different diversity categories together may mask the real
impact of each on organizational outcomes (Herring, 2009;
Smith, DiTomaso, Farris, & Cordero, 2001; Zenger &
Lawrence, 1989). Moreover, a focus on gender diversity is
critical since studies (Heilman & Haynes, 2005; Heilman &
Okimoto, 2007) have found that women often suffer the consequences of gender stereotyping when they work in teams
with
men,
hindering
team
performance
and
1
Gallup, Omaha, NE, USA
Corresponding Author:
Sangeeta Badal, Gallup, 1001 Gallup Drive, P.O. Box 2277, Omaha, NE
68102, USA.
Email:
[email protected]
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Badal and Harter
overall organizational functioning. Our secondary goal is to
examine the role of employee engagement as a potential
moderator in the gender diversity–performance relationship.
Employee perception of their work environment depends on
their day-to-day interactions and relationships with their
coworkers (Harter, Schmidt, Asplund, Killham, & Agrawal,
2010). These interpersonal and intergroup relationships in
turn affect many important organizational outcomes such as
sales and profit. Thus, this study adds significantly to the
existing literature by providing a deeper look at the links
between gender diversity, interpersonal and intergroup relationships, and business performance. Furthermore, we
extend the literature by outlining the psychological underpinnings of the gender diversity–business performance linkage. This theory-based approach to understanding the gender
diversity–engagement–performance linkage provides the
practitioners with tools on how to manage gender diversity
to drive organizational performance. Furthermore, this is the
first study that links gender diversity to financial performance at the business-unit level. Studies at the firm level
ignore the variability of performance across business units
within firms. Prior studies (Harter, Schmidt, & Hayes, 2002;
Harter et al., 2010) show that engagement varies substantially across business units within firms and is a predictor of
business-unit outcomes. It is reasonable to postulate that
diversity also varies substantially across business units
within firms. In fact, the business units in the two organizations in this article vary widely in gender diversity. For
instance, in the retail organization, business-unit diversity
values range from .09 (9% of the team is one gender and
91% in the other gender) to .48 (48% of the team is one gender and 52% in the other gender) with the average diversity
of .24 (24% of the business unit is one gender and 76% in the
other gender). Studying the gender diversity–performance
linkage at the firm level may mask such variations. Harter
and Schmidt (2006) explain that unit-level studies provide a
more accurate view of the intergroup relations that affects
many of the ultimate outcomes the units are working to
achieve. Last, this is the first study that looks at objective
financial performance measures in real organizations. If we
are looking at the diversity–performance linkage from a
business utility perspective, then it is important to study the
impact of diversity on a business-unit’s financial bottomline in real organizations rather than testing gender diversity
effects in simulated environments.
Theoretical Foundation and Hypotheses
The literature includes a number of well-established theories that provide a conceptual framework to understand why
and how gender diversity affects performance: resourcedependence theory, resource-based view of the firm, and
psychological presence theory. These theories and the
hypotheses are discussed below.
Pfeffer and Salancik’s (1978) resource-dependency theory seeks to explain how organizations employ strategies to
manage complex business environments by accessing
scarce external resources. It proposes that diversity is a
vehicle for accessing critically valuable resources for the
firm’s success (Aldrich & Pfeffer, 1976; Pfeffer & Salancik,
1978).
A growing degree of uncertainty in world affairs—evidenced by recent economic downturn, market failures, and
dissatisfaction with local and national governance bodies—
makes it imperative for organizations to garner all resources
at their behest to stay competitive and viable. Hiring a
demographically diverse workforce is one such strategy to
get access to critical resources for firm survival and success
(Gallego-Alvarez,
Garcia-Sanchez,
&
RodriguezDominguez, 2009). For instance, Hillman, Shropshire, and
Cannella (2007) found that companies that are heavily
dependent on female employees or ones with ties to other
companies who have women as board members are likely to
strategically place women on their corporate boards to mirror the environment in which they operate. Other studies
(Dalton, Daily, Ellstrand, & Johnson, 1998; Siciliano, 1996)
have found that a diverse workforce is likely to establish
interactions and external links that may result in easier
access to resources such as diverse credit sources, multiple
information sources, wider knowledge of the industry, or a
bigger customer base. For instance, a diverse workforce
may benefit from interactions with an increasingly diverse
customer base (Carter, Simkins, & Simpson, 2003). In addition, gender diversity in the employee base also enables
companies to attract and retain talent from a wider pool of
human capital (Gallego-Alvarez et al., 2009; Jimeno &
Redondo, 2008).
These studies suggest that hiring female employees can
provide a strategic advantage to these companies, affecting
their performance positively. Currently, there are 71 million
women in U.S. workforce, and the Bureau of Labor
Statistics forecasts indicate that in the next decade women’s
labor force growth will continue to be greater than men’s—
a resource that companies cannot afford to ignore and may
be the source of power in interorganizational relations (U.S.
Department of Labor, 2011b).
The resource-based view (RBV) is a valuable conceptual
framework to understand the way firms manage their internal resources, in this case human resources, to achieve a
competitive advantage. The theory postulates that a firm
can gain a competitive advantage by using its valuable,
rare, inimitable, and nonsubstitutable resources (Barney,
1991). Levels of human capital available to management
can be a source of competitive advantage for a firm (Barney,
2001). Studies supporting this theory found that gender
diversity is one such resource with no strategically equivalent substitute and can be a source of competitive advantage
(Ali, Kulik, & Metz, 2009).
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Journal of Leadership & Organizational Studies 21(4)
Theoretical support for the positive link between gender
diversity and performance is based on the notion that men
and women bring different viewpoints, diversity in creativity and innovation, diverse market insights, and broader
repertoire of skills that enable superior problem solving and
decision making (Farrell & Hersch, 2001; Shrader,
Blackburn, & Iles, 1997; Smith, Smith, & Verner, 2006;
Watson, Kumar, & Michaelsen, 1993). Studies have found
that gender-diverse teams perform better than single-gender
teams (Kanter, 1977; Martin, 1985; Orlitzky & Benjamin,
2003). Similarly, Stewart (2006) found that heterogeneity is
desirable in teams consisting of knowledge workers who
are engaged in creative tasks. Wood (1987) conducted a
meta-analysis of the findings from past laboratory research
and concluded that mixed-sex groups slightly outperformed
same-sex groups. Similarly, a recent McKinsey study
(Desvaux, Devillard-Hoellinger, & Meaney, 2008) found
that senior management teams with a higher proportion of
women had better organizational performance. Similarly,
Catalyst (2004), Dezso and Ross (2008), and Krishnan and
Park (2005) found a strong positive correlation between
female participation in top management and financial indicators of performance.
Both resource-dependency theory and RBV assert that
hiring and managing a demographically diverse workforce
can be a source of competitive advantage to the firm. Hence,
we hypothesize that gender diversity at the business-unit
level will be positively associated with financial
performance.
Hypothesis 1: There is a positive relationship between
gender diversity and financial performance at the businessunit level.
Kahn’s (1990) psychological presence model proposes
that intergroup relations affect the psychological context at
work, thus influencing personal engagement of employees.
In his seminal work, Kahn (1990, 1992) defines engagement as an individual’s physical, cognitive, and emotional
presence at work influenced by individual, interpersonal,
group, intergroup, and organizational factors. According to
this framework, work contexts create conditions (meaningfulness, safety, and availability) that influence an individual’s engagement or disengagement. May, Gilson, and Harter
(2004) empirically tested Kahn’s model and found that role
fit and opportunities to grow in their jobs were positive predictors of meaningfulness (a sense of self-worth, being useful, and being valued); supportive relationships between
coworkers and between employees and supervisor predicted
safety (open, trusting relationships with coworkers, clear
expectations and control over their work, and supportive
managerial environments); and access to resources positively predicted psychological availability (having the
physical, emotional, or psychological resources to personally engage in the role). Studies supporting this theory
found that when employees feel adequately supported by
coworkers, it results in higher engagement with the job and
higher levels of job satisfaction (Dignam, Barrera, & West,
1986). Similarly, Polzer, Milton, and Swann (2002) found
that when demographically diverse groups have high levels
of interpersonal congruence (open, trusting, and supportive
relationships with coworkers and supervisors), conflict levels decrease, which in turn affects productivity positively.
Conversely, the authors found that diversity in workgroups
can lead to lowered productivity if group members categorize themselves into in-groups/out-groups and have lower
interpersonal congruence. In another study, Tougas, Rinfret,
Beaton, and de la Sablonniére (2005) found that women in
the police force who felt they experienced relative disadvantage compared to men (interpersonal incongruence)
psychologically disengaged from their work, possibly leading to inferior performance in the role. Jones and Harter
(2005) assessed the combined effects of employee engagement and racial composition of employee–supervisor dyad
on turnover intent. They found that at lower levels of
engagement, different-race dyads show higher turnover
intent, but at high levels of engagement, intent to stay with
the organization was higher for different-race dyads.
Similarly, Hobman, Bordia, and Gallois (2003) found that
perceived openness to diversity moderated the relationships
between diversity and workgroup conflict. In this investigation, we conceptualize engagement levels as a manifestation of intergroup relations at work and measure it using
Gallup’s Q12 (Harter, Schmidt, & Hayes, 2002).
Based on Kahn’s (1990, 1992) work, we propose that
high engagement levels at the business-unit level (indicative of positive intergroup relations) perpetuate a secure
psychological environment in which gender-diverse groups
may be able to achieve high levels of interpersonal congruence, thus reducing dysfunctional conflict and positively
affecting business outcomes. Conversely, low engagement
levels (indicative of negative intergroup relations) may trigger dysfunctional conflict among males and females, thus
affecting business outcomes negatively. Based on psychological presence theory and research, we hypothesize that
the gender diversity–performance link is moderated by
business-unit level engagement.
Hypothesis 2: Employee engagement moderates the
relationship between gender diversity and performance.
Method
Context and Data
We identified two different companies from two industries,
retail (Study 1) and hospitality (Study 2), to examine the
relationship between gender diversity and performance at
the business-unit level. The main reason for using this
approach is that the group processes and outcome variables
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Badal and Harter
for each company are unique to their industry type, thus
necessitating a detailed contextual analysis of the relationship between gender diversity and performance. For
instance, the average male–female ratio in a business unit in
the retail company is three males to one female, whereas the
average ratio in the hospitality company is 1.13 females to
1 male. The critical outcome variable for the retail company
is the year over year change in revenue, whereas for the
hospitality company it is the quarterly net profit for each
unit. Thus, each study draws on somewhat different kinds
of data to address the issue of gender diversity at the business-unit level and its impact on performance. The store
(retail organization) or restaurant (hospitality organization)
is considered as the unit of analysis since this is the organizational unit where management decisions are made, and
day-to-day interactions happen between coworkers. It is
also the unit at which financial data are available.
The retail organization provided data from 532 electronics retail stores in the United States. The stores range in size
from 64 to 220 full- and part-time employees (SD = 20.67),
4 to 5 assistant managers, and 1 general manager. The data
collection involved both an objective financial measure
(comparable revenue) at the store level and self-reported
data from the employee engagement survey conducted for
all employees in the company (92% response rate), which
then is aggregated to a store level to match the financial data.
The hospitality organization provided data from 284 restaurants in the United States. The restaurants range in size
from 26 to 106 employees with almost 90% of the restaurants having 50 or more employees. Due to slightly lower
overall response rates, only restaurants with over 50 employees and a response rate of 50% or above on the employee
engagement survey were included in this analysis (range
50-106 employees, SD = 11.03). The excluded smaller restaurants were not directly comparable to regular sized stores
since they were quick-service mall/in-line restaurants rather
than stand-alone restaurants. Each restaurant in the study has
one general manager. We collected an objective financial
measure (quarterly net profit) at the restaurant level and
employee engagement data at the individual employee level,
which was aggregated to the restaurant level.
Independent Variables
Proportional Diversity Index. The majority of the studies have
defined gender composition as the percentage of heterogeneity (heterogeneity index; Pelled, Eisenhardt, & Xin,
1999). The heterogeneity index is noninterval, that is, the
difference in index scores between a group with one woman
and a group with two women is larger than the difference in
index scores between a group with two women and a group
with three women (Williams & Mean, 2004), making it less
well suited for regression analyses. This weakening of
effect with distance from homogeneity also predetermines
nonlinearity in the representation of the diversity construct.
For our study, we have used the proportional diversity
index, which is the percentage of minority group members
present within each business unit. This is on an interval
scale and more appropriate since it does not predetermine
nonlinearity in the diversity construct. Conceptualized
within the diversity approach, the proportional diversity
measure assumes that gender diversity among group members is an important determinant of group functioning, not
the proportion of a particular gender (male or female; Williams & Mean, 2004). The index calculates the proportion
of minority members in each business unit and has values
ranging from 0 to 0.5, where 0.5 denotes a business unit
with an equal number of males and females, and 0 denotes
a group with just one gender (male or female). Studies indicate that business units with one gender (index value of 0)
lack the different viewpoints, diversity in creativity and
innovation, diverse market insights, and broader repertoire
of skills that the RBV of the firm postulates to be important
for firm growth (Ali et al., 2009). As the proportion of
males and females approaches parity the interaction
between male and female members produces the benefits
hypothesized by the RBV of the firm (Ali et al., 2009; Williams & Mean, 2004).
Demographic breakdown of the stores and restaurants
was obtained from company records at the time of each
employee engagement measurement. In both studies, we
use the proportional diversity approach to calculate the gender composition of business-units. For the retail study
(Study 1), the average proportional diversity index is .24.
This indicates that, on an average, one fourth of the team is
one gender while three fourths is the other gender. Values
range from 0.09 to 0.48.
For the hospitality study (Study 2), the average proportional diversity index is .43. This indicates that in this
study, on average, 43% of the team is one gender while
57% is the other gender. Values range from .22 to .50 (.50
denotes a business unit with an equal number of males and
females).
Employee Engagement. Both organizations (Study 1 and
Study 2) measured employee engagement using the Gallup
Q12 measure (Harter et al., 2002; Harter et al., 2010), which
is a 12-item measure of employee engagement workplace
conditions (clarity of expectations, interpersonal relationships between coworkers and with the supervisor, recognition for good work, opportunities to develop, connection to
the purpose of the organization, opportunities to learn and
grow, etc.), the composite of which is highly statistically
convergent with other direct measures of engagement cited
by Macey and Schneider (2008) in their review of the
employee engagement construct (Harter & Schmidt, 2006,
2008). Gallup’s instrument is a formative measure of
engagement that captures the psychological and contextual
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Journal of Leadership & Organizational Studies 21(4)
conditions that influence the state of engagement in the
workplace. Kahn’s “meaningfulness” is measured by items
like “received recognition for good work,” “opinions
count,” “mission of my company makes me feel my job is
important,” and “I have had opportunities to learn and
grow.” Kahn’s “safety” is measured by items like “I know
what is expected of me,” “I have a best friend at work,” “my
associates are committed to doing quality work,” “my
supervisor cares about me as a person,” “someone at work
has talked to me about my progress,” and “there is someone
at work who encourages my development.” Finally, “psychological availability” is measured by “I have the materials and equipment I need to do my work” and “at work, I
have the opportunity to do what I do best every day.” When
these psychological and contextual conditions are met, it
creates a secure psychological environment that facilitates
effective integration of divergent perspectives, increased
levels of communication between group members and
between employees and supervisors, and stronger interpersonal relationships, thus enhancing group functioning and
positively affecting organizational performance (Harter
et al., 2002; Harter, Schmidt, Killham, & Asplund, 2006;
Schaufeli & Bakker, 2004).
A particular strength of the Q12 is its prior meta-analytic
evidence of causal impact of employee perceptions on the
performance of the firm and high test–retest reliability
(Harter et al., 2010). Since our primary research questions
here involve the examination of the role of gender diversity
in business-unit level performance, it is important that we
include a measure that has prior empirical evidence of performance relatedness (particularly, known generalizable
correlations with financial measures). A second strength is
that the Q12 measure is a measure of psychological conditions at work that many organizations have found actionable. The Q12 is used in hundreds of organizations around
the world and has been administered to more than 22 million respondents. In addition to capturing variance in global
workplace attitudes (satisfaction, commitment, involvement, dedication, etc.), the instrument is a practical measure
that managers can use in understanding the perceptions of
their work teams with regard to Kahn’s hypothesized psychological conditions at work. In both studies the average
engagement score for the 12 items is used to assess the level
of engagement among business units. Employee engagement surveys were administered at the individual employee
level in both studies. The data were then aggregated into
business units at the direct manager level and subsequently
rolled-up up to the store and restaurant level in each company. This allows us to examine the predictive relationship
between employee engagement at point one and the financial performance at a subsequent time at the business-unit
level. Engagement data were aggregated up to the store and
restaurant level since this is the lowest unit at which financial data was available.
For the retail study (Study 1), the engagement survey
results were collected during the second quarter of 2004
with an average response rate of 92%.
For the hospitality study (Study 2), the employee engagement survey results were collected in March 2002 with an
average response rate of 72%.
Dependent Variable
For the retail study (Study 1), Comparable Revenue 2005
was obtained from company records for each store. The
comparable revenue is a key performance metric in the
organization and computed as percent change in revenue
from the previous year, 2004. Extreme values were removed
to make Comparable Revenue normally distributed. This
was then matched to Q12 measurement from the 2nd quarter of 2004.
For the hospitality study (Study 2), Net Profit after controllable expenses for the second quarter of 2002 was used
in this analysis. Natural Log of Net Profit was used to
achieve a normal distribution of the dependent variable. Net
Profit was matched to the Q12 measurement conducted in
March 2002. Both studies measured employee engagement
(Q12 measurement) and diversity at Time 1 and outcomes
at Time 2, making it a predictive study of business-unitlevel performance.
Analyses
We use the hierarchical multiple linear regression approach
to test our hypotheses. This approach is appropriate to test
how each new variable or block of variables add to the prediction produced by the previously entered variables. We
enter employee engagement first, since it has prior established meta-analytic evidence of relationship to financial
outcomes (Harter et al., 2002; Harter et al., 2010). Once
accounting for the variance captured by engagement, we
enter the gender diversity variable to assess its unique
prediction of financial performance, and finally the
engagement–gender diversity interaction term, to test for
significant moderation.
Results for Study 1: A Large Retailer
Table 1 presents the means, standard deviations, and correlations for all the variables in this study. The correlations
indicate that gender diversity and employee engagement are
positively related to Comparable Revenue (r = .100, p < .05,
95% confidence interval [CI] = .02, .18; r = .137, p < .01,
95% CI = .05, .22, respectively). The observed correlation
of engagement to Comparable Revenue is of similar magnitude as meta-analytic observed correlations reported in
Harter et al. (2002) and Harter et al. (2006). The correlation
between gender diversity and employee engagement,
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Badal and Harter
Table 1. Study 1: Summary Statistics and Intercorrelations.
Variable
Comparable Revenue
Employee Engagement
Gender Diversity
Mean
SD
4.91 [−13.53 to 21.24]
4.07 [3.36 to 4.90]
0.24 [0.09 to 0.48]
Comparable Revenue Employee Engagement
6.196
0.283
0.056
—
.137** (.05, .22)
.100* (.02, .18)
Gender Diversity
—
.006 (−.08, .09)
—
Note. N = 532. Range is given in brackets; 95% confidence interval is given in parenthesis.
*p < .05. **p < .01.
Table 2. Study 1: Results of Hierarchical Regression Analysis Predicting Comparable Revenue.
Model 1
Variable
Engagement
Gender Diversity
Interaction (EE * GB)
R
∆R
df
Model 2
Model 3
B
SE
B
SE
2.989** (1.14, 4.84)
0.940
2.975** (1.14, 4.81)
10.838* (1.67, 20.01)
0.936
4.668
.137 (.05, .22)
1,530
.169 (.09, .25)
.032*
1,529
B
1.926 (−6.26, 10.11)
−6.853 (−141.66, 127.95)
4.346 (−28.69, 37.39)
.170 (.09, .25)
.001
1,528
SE
4.164
68.620
16.819
Note. 95% confidence interval is in parenthesis.
*p < .05. **p < .01.
however, was nonsignificant (r = .006, 95% CI = −.08, .09),
suggesting that gender-diverse business units are not necessarily more engaged.
Hypothesis 1 predicted that there is a positive relationship between gender diversity and financial performance at
the business-unit level. Hierarchical regression was used to
test this hypothesis. We first entered the employee engagement score in Step 1 in Model 1 (controlling for store size
made no substantive changes in the results). As expected, it
positively predicts performance (B = 2.989, 95% CI = 1.14,
4.84; t(530) = 3.179, p ≤ .01) and explained significant variance (R = .137, 95% CI = .05, .22). In Model 2, we entered
gender diversity, which was a significant predictor of comparable revenue, B = 10.84, 95% CI = 1.67, 20.01; t(529) =
2.322, p = .02, and explained additional variance beyond
employee engagement (R = .169, 95% CI = .09, .25; ∆R =
.032, p ≤ .05; see Table 2). Next, we tested the moderating
effect of employee engagement on the relationship between
gender diversity and performance (Hypothesis 2). We computed the interaction term between gender diversity and
employee engagement by multiplying both the independent
variables (centering the variables yielded the same results).
According to Baron and Kenny (1986) and James and Brett
(1984), a moderation effect is present if the interaction term
is significant. In Model 3, we entered the interaction term.
It was not significantly related to Comparable Revenue, B =
4.346, 95% CI = −28.69, 37.39; t(528) = .258, p = .796, and
the F change statistic was not statistically significant (R =
.170, 95% CI = .09, .25; F(1, 528) = .067, p = .796). Hence,
Hypothesis 2, predicting that employee engagement moderates
the relationship between gender diversity and performance,
was not supported.
Engagement levels and gender diversity explain about
2% and 1% of the variance in comparable revenue, respectively. However, the practical meaning of percent variance
accounted for is not directly interpretable. To understand
the practical meaning of the effects detected here, we conducted utility analysis. We calculated the mean comparable
revenue for various combinations of high and low employee
engagement and gender diversity. Table 3 indicates that
engaged business units (above the median on employee
engagement) have average comparable revenue increase of
5.54%, and more diverse business units (above the median
on proportional diversity index) have average comparable
revenue increase of 5.24%. However, stores that are highly
engaged and diverse outperform others with comparable
revenue increase of 5.76%. This is indicative of the additive
effect of engagement and gender diversity on performance.
Results for Study 2: A Large
Hospitality Company
Table 4 presents the means, standard deviations, and correlations for all the variables in this study. The correlations
indicate that gender diversity and employee engagement are
positively related to Net Profit (r = .154, p < .01, 95% CI =
.04, .27; r = .168, p < .01, 95% CI = .05, .28, respectively).
The correlation between employee engagement and net
profit is of similar magnitude to prior meta-analyses (Harter
et al., 2002; Harter et al., 2006). As with Study 1, the
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Journal of Leadership & Organizational Studies 21(4)
Table 3. Study 1: Practical Implications of Engagement and Gender Diversity.
Average comparable revenue (%)
SD
N
4.91
5.24
4.58
5.54
4.31
5.76
3.95
6.20
6.55
5.81
6.45
5.88
7.27
6.08
532
266
266
262
270
137
141
Average for total sample
Above median on gender diversity
Below median on gender diversity
Above median on engagement
Below median on engagement
Above median on engagement and gender diversity
Below median on engagement and gender diversity
Table 4. Study 2: Summary Statistics and Intercorrelations.
Variable
M
SD
Net Profit
14944.32 [−16,700 to 71,418] 15928.28
Employee Engagement
3.94 [3.07 to 4.79]
0.281
Gender Diversity
0.43 [0.22 to 0.50]
0.052
Net Profit
Employee Engagement
Gender Diversity
—
.168** (.05, .28)
.154** (.04, .27)
—
.078 (−.04, .19)
—
Note. N = 284. Range is given in brackets; 95% confidence interval is given in parenthesis.
*p < .05. **p < .01.
correlation between gender diversity and employee engagement was nonsignificant (r = .078, 95% CI= −.04, .19).
Hypothesis 1 predicted that there is a positive relationship between gender diversity and financial performance at
the business-unit level (log transformation of Net Profit
used). To test this hypothesis, we first entered employee
engagement in Model 1. Employee engagement is positively related to log transformed Net Profit (B = 0.357, 95%
CI = .15, .57; t(282) = 3.365, p < .001) and explains sizeable
proportion of variance (R = .196, 95% CI = .08, .31). The
estimated regression coefficient of employee engagement is
β1 = 0.357. This indicates that an increase of one unit in
employee engagement will result in (eβ1 − 1) * 100 percentage change in Y, that is, approximately 35.7% increase in
Net Profit. In Model 2, we entered gender diversity, which,
as with Study 1, by itself is a significant predictor of Net
Profit, B = 1.453, 95% CI = .33, 2.57; t(281) = 2.551, p =
.01, and explained additional variance (R = .246, 95% CI =
.13, .35; ∆R = .05, p ≤ .01; see Table 5). Next, we tested the
moderating effects of employee engagement on the relationship between gender diversity and performance
(Hypothesis 2). As with Study 1, we computed the interaction term between gender diversity and employee engagement by multiplying both the independent variables. In
Model 3, we entered the interaction term. It was not significantly related to Net Profit, B = −2.245, 95% CI = −6.22,
1.73; t(280) = −1.112, p = .267, and the F change statistic
was nonsignificant (R = .254, 95% CI = .14, .36; F(1, 280)
= 1.237, p = .267). Hence, Hypothesis 2, predicting that
employee engagement moderates the relationship between
gender diversity and performance, was not supported. The
results of Study 2 are remarkably consistent with those from
Study 1.
In this study, engagement and gender diversity each
explain 3% to 4% of variance in Net Profit. Again, percent
variance accounted for has no direct practical meaning on
its own. As with Study 1, we conducted utility analysis, calculating the mean net profit for various combinations of
high/low employee engagement and gender diversity. Table 6
indicates that engaged business units have average quarterly net profit of $17,301.84, and gender-diverse business
units have average quarterly net profit of $16,296.06; however, stores that are highly engaged and have high gender
diversity outperform others, with net profit of $18,283.28.
This is again indicative of the additive effect of engagement
and gender diversity on performance.
Discussion
In this investigation, our goal was to determine if there is a
relationship between gender diversity and financial performance at the business-unit level and whether employee
engagement moderates this relationship. Previous studies of
diversity’s impact on performance have been inconsistent in
their findings, suggesting a need to use a more complex
theoretical framework. The present study draws on three
well-established theories (resource-based view of the firm,
resource dependency theory, and psychological presence
theory) to explain the gender diversity–performance linkage. Using a total of 816 business units from two studies
belonging to two different industries (retail and hospitality),
the results suggest that more gender-diverse business units
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Badal and Harter
Table 5. Study 2: Results of Hierarchical Regression Analysis Predicting Net Profit (Log Transformation of Net Profit Used).
Model 1
Variable
Engagement
Gender diversity
Interaction (EE * GB)
R
∆R
df
Model 2
B
SE
0.357** (0.15, 0.57)
0.106
B
SE
0.336** (0.13, 0.54)
1.453* (0.33, 2.57)
.196 (.08, .31)
1,282
Model 3
0.105
0.570
.246 (.13, .35)
.050*
1,281
B
SE
1.292 (−0.41, 2.99)
10.209 (−5.33, 25.75)
−2.245 (−6.22, 1.73)
.254 (.14, .36)
.01
1,280
0.865
7.893
2.018
Note. 95% confidence interval is in parenthesis.
*p < .05. **p < .01.
Table 6. Study 2: Practical Implications of Engagement and Gender Diversity.
Average for total sample
Above median on gender diversity
Below median on gender diversity
Above median on engagement
Below median on engagement
Above median on engagement and gender diversity
Below median on engagement and gender diversity
perform at higher levels, financially, than those that are less
gender-diverse. Most of the earlier studies are at the firmlevel or are based on research conducted on student groups
in laboratory settings (Myaskovsky et al., 2005; Wood,
1987). Moreover, using actual financial data for business
units and tying it to team composition makes this study a
valuable addition to the gender diversity literature. Most
studies use employee job satisfaction (Fields & Blum,
1997) or productivity measures such as tasks completed,
time of completion, errors committed, and so on
(Myaskovsky et al., 2005) or group effectiveness measures
such as self-efficacy, group efficacy, and group cohesion
(Lee & Farh, 2004). These results make a strong “business
case” for gender diversity extending the boundary of gender
diversity impact on financial performance. Furthermore,
these results explain differences between business units
within firms rather than across firms. These findings suggest that organizations looking to implement changes in
gender diversity might be well suited to target specific business units for improvement.
In both studies, we found that employee engagement and
gender diversity independently predicted financial performance at the store/restaurant level, and the additive effect of
both is larger than the independent effect of each on business-unit performance. A major implication of this finding
for managers is to both create an engaged workplace and to
try to attain gender diversity in business units to affect
Average quarterly net profit ($)
SD
N
14,944.32
16,296.06
13,702.18
17,301.84
12,553.36
18,283.28
11,562.57
15,928.28
15,875.95
15,928.60
15,689.17
15,866.81
17,593.22
17,647.38
284
136
148
143
141
75
80
performance positively. In Study 1, business units that were
above median on both engagement and gender diversity had
a 46% higher increase in Comparable Revenue (i.e.,
[5.76%-3.95%]/3.95%) than those below the median on
both. Similarly, in Study 2, business units above the median
on engagement and gender diversity had a 58% higher net
profit (i.e., [$18,283-$11,562]/$11,562) than those below
the median on both. The replication of the results in Study 2
increases our confidence in the generalizability of our findings. It is important to note that although the absolute effect
size may not appear large, the practical utility of having an
engaged environment as well as diverse business units is
evident in both studies (see Tables 3 and 6). Also, the effect
sizes reported here are observed effect sizes and have not
been corrected for criterion variable reliability or range
restriction. Therefore, they should be regarded as lower
bound estimates of the true relationship. Once corrected for
measurement error and range restriction, the practical utility
would be higher than estimated here.
These findings also support previous studies that found
gender diversity to have a stronger impact on performance
in service industry (Ali et al., 2009) compared to manufacturing environments where customer relationships and creativity are secondary to the technologically driven
manufacturing process (Bowen & Schneider, 1988;
Campbell & Mínguez-Vera, 2008; Jackson, Schuler, &
Rivero, 1989). Both our studies belong to sectors, Retail
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Journal of Leadership & Organizational Studies 21(4)
and Hospitality, that gain from diverse perspectives, have
more social interaction between team members, and higher
interaction between employees and customers. In such
environments, it is critical to capitalize on the benefits provided by a diverse workforce.
While we found a practically meaningful relationship
between gender diversity and performance, our findings
suggest that engagement levels in the business unit may not
be moderating this relationship. To our knowledge, this is
the first study that uses employee engagement as a measure
of intergroup relations at work and looks at its moderating
effect on the gender diversity–performance link. A possible
explanation for why engagement did not moderate the effect
of gender diversity on performance is that the group members in these business units (retail stores in Study 1 and restaurants in Study 2) spend a considerable amount of time
with each other, working collaboratively to achieve specific
goals. Hence, they have learned to anticipate and manage
different viewpoints that may exist along the social categories (Harrison, Price, Gavin, & Florey, 2002; Jehn &
Bezrukova, 2004; Pelled et al., 1999). Prior research indicates that in collectivistic organizational cultures, such as
retail or hospitality, the emphasis is on team performance
rather than individual achievement. Team members depend
on each other to achieve a common goal. In such cultures
the organizational membership is far more important than
membership based on demographic attributes (Chatman,
Polzer, Barsade, & Neale, 1998). Turner, Oakes, Haslam,
and McGarty (1994) term this “functional antagonism,”
where, as the salience of one type of social categorization
(organizational membership) increases, salience of the
other type (gender, age, or race differences) decreases. In
our study, the employees in a store or a restaurant work
together to serve the customers’ needs and preferences and
thus affect performance. There is a feeling of shared goals,
leading members to consider more of their coworkers as
members of the same group irrespective of their demographic differences. Hence, interaction among males and
females is likely to be much more harmonious in a collectivistic culture, reducing the role of engagement as a moderator. In individualistic work cultures like the manufacturing
environment, limited interaction between male and female
employees may lead to gender differences becoming more
pronounced and thus hindering effective working of the unit
(Ali et al., 2009). In such environments, the moderating
effect of engagement may become more salient in harmonizing the relationships between gender groups and to fully
leverage the benefits of gender diversity. Clearly, more
research is needed to establish the role of engagement and
gender diversity in different industry contexts.
Our study has several limitations that can be addressed
by future research. The cross-sectional nature of the data
makes it difficult to draw causal inferences from this
study—a limitation that can be avoided by designing a
longitudinal study. A longitudinal study will also be able to
capture how changes in gender diversity influence performance over time. Researchers should also explore the effect
of organizational diversity goals on self-perception of
women and its impact on intergroup relations, engagement,
and organizational performance. Intergroup relations may
be negatively affected if women feel they were hired to
improve diversity levels. More research is also needed to
uncover the mechanisms by which gender diversity drives
business performance. Whether it is facilitating interactions
with a diverse customer base or generating diverse market
insights or bringing in a broader repertoire of skills into the
workplace—understanding the means by which gender
diversity can be a competitive advantage will enable organizations to use gender diversity as a lever for business
growth. Future research should also look at the role of
engagement as a moderator in industries other than retail
and hospitality. It will be interesting to see the effect of
engagement as a moderator in firms where demographic
attributes may hinder business-unit performance. In addition, future research should be focused on testing additional
environmental and individual-level variables that could be
better moderators of gender diversity–performance linkage
in different industry settings. For instance, length of time
the teams have been together, pattern and frequency of
interaction among team members, and differential job types
could possibly be better predictors of impact of gender
diversity on business-unit performance. Arguably, the
financial outcomes we included in this article are downstream from potentially direct outcomes such as customer
perceptions of service quality and employee turnover.
Future research should focus on these direct outcomes and
also explore the gender diversity link to nonfinancial outcomes, such as problem solving and innovation.
Conclusion
The current study is specifically focused on gender diversity. Even though there is an increasing body of literature
assessing the relationship between different types of demographic diversity (age, race, or gender) and performance,
there are a limited number of empirical studies examining
the independent effect of each demographic characteristic
on performance—a fact pointed out by several researchers
who tried to conduct a meta-analysis for each category
(Horwitz & Horwitz, 2007). The results of this research
support the contention that gender diversity at the businessunit level positively affects financial performance, which
appears to have substantial practical implications. This
financial utility suggests that making diversity an organizational priority may realize financial benefits. We also
showed that employee engagement separately and independently contributes to the company’s bottom-line. But diversity and engagement do not appear to be an either-or
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proposition. They are relatively independent in their contribution to financial success, suggesting that organizations
should focus both on selecting a diverse workforce and creating an engaged culture.
Declaration of Conflicting Interests
The author(s) declared no potential conflicts of interest with respect
to the research, authorship, and/or publication of this article.
Funding
The author(s) received no financial support for the research,
authorship, and/or publication of this article.
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Author Biographies
Sangeeta Badal is the primary researcher for Gallup's entrepreneurship initiative and a Senior Consultant with the workplace
practice. She has been employed with Gallup since 1999.
James K. Harter is Chief Scientist for workplace and well-being
research at Gallup. He has been employed with Gallup since 1985.
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