Who Values Diversity? Comparing the Effect of Manager Gender Across the Public,Private,and Nonprofit Sectors

Abstract

Researchers have focused on the role of managerial gender on attitudes toward diversity issues mainly in either the public or private sector, but there is little research that compares managerial attitudes on diversity across the public, private, and nonprofit sectors. This article identifies important distinctions among the sectors that may influence gender differences in managerial priority placed on diversity. Using a national survey of nearly 1,000 top-level managers in public, private, and nonprofit hospitals in the United States, we analyze how managerial gender combined with cross-sector differences shape managerial priority on diversity. We find female managers place a higher priority on diversity than their male counterparts in nonprofit and private organizations compared with managers in public organizations. The differing effects of managerial gender on the priority placed on diversity are shaped by the organizational contexts of the three sectors. This research provides systematic evidence of sector differences in the patterns of managerial priorities regarding diversity.

Keywords

diversity gender cross-sector comparison American hospitals

Introduction

A growing body of research on diversity in the workplace has focused on the effect of workforce diversity and diversity management on the performance of public, private, and, to a lesser extent, nonprofit organizations (Choi, 2009; Choi & Rainey, 2009; Pitts & Wise, 2010). Although the impact of diversity and diversity management on performance is not always clear, managing for diversity is considered a best practice in public, nonprofit, and private organizations (Hyde & Hopkins, 2004; Mor Barak, 2000; Riccucci, 2002).

Managerial attention to diversity issues is often seen as the starting point of the promotion and implementation of diversity programs (Pitts, Hicklin, Hawes, & Melton, 2010; Soldan & Dickie, 2008; Soni, 2000). In this vein of research, a few researchers have started to explore how a manager’s social identities, such as gender, may affect the priority they place on diversity issues (Pitts & Jarry, 2007; Soldan & Dickie, 2008). Indeed, research finds that the gender of the manager influences managerial strategies and priorities, institutional culture, and networking behavior, which can affect policy and performance outcomes (Dolan, 2000; Jacobson, Palus, & Bowling, 2010; Johansen, 2007; Keiser, Wilkins, Meier, & Holland, 2002; Wilkins, 2007). More specifically, research finds gender differences in workers’ openness to diversity, valuing of diversity, inclusiveness, and support for diversity management programs (Mor Barak, Cherin, & Berkman, 1998; Soldan & Dickie, 2008; Soni, 2000).

Furthermore, it is possible that the type of sector in which the manager works may moderate the impact of gender on managerial practices regarding diversity as a result of differences in discretion and the instilling of organizational values and attitudes due to organizational socialization. For instance, research on representative bureaucracy finds that gender representation is influenced by discretion (Keiser et al., 2002; Wilkins & Keiser, 2006) and may be moderated by organizational socialization (Dolan, 2002).

In this article, we ask, how does gender influence the priority that managers place on diversity in their respective sectors of employment? First, we discuss the reasons for our expectations of gender and sector differences in the priority that managers place on diversity. We then explore why gender effects may vary across the public, private, and nonprofit sectors. Next, we describe the data and methods we use to test hypotheses using the empirical context of U.S. health care. In our “Results” section, we present our findings of significant differences in the priority male and female managers place on diversity in private and nonprofit organizations. We see the largest gender differences in the private sector. No differences exist between male and female managers’ priority on diversity in public organizations. Finally, we conclude by discussing how these findings highlight the importance of cross-sector differences and managerial gender for understanding managerial attitudes regarding diversity.

Gender Differences and Managerial Priority on Diversity

Research on gender and organizational behavior points us to two mechanisms for understanding gender differences in attitudes toward diversity. First, men and women may have different personal and workplace experiences, which may influence their attention to and attitudes toward diversity issues. For instance, female workers find more value in diversity programs than men in both private and public organizations (Dolan, 2000; Mor Barak et al., 1998; Soldan & Dickie, 2008; Soni, 2000). This is because, compared with men, “women perceive greater discrimination, experience less job satisfaction, report less satisfying team relationships, and perceive organizational culture to be less open, flexible, and supportive of diversity” (Soni, 2000, p. 406).

Moreover, according to research by Mor Barak (2013) about diversity attitudes in the private sector, female workers often feel that their organization “creates or tolerates barriers that prevent them from getting a promotion or from feeling included in the organization’s information, resource, or power networks” (p. 6). These gender differences in perceptions reveal an implicit or explicit exclusion of minority groups in the organization from “job opportunities, information networks, team membership, human resource investments, and the decision-making process because of their actual or employer-perceived membership in a minority or disfavored identify group” (Mor Barak, 2013, p. 6). There may also be gender differences because these barriers may be invisible to most men, as they are not exposed to, or do not participate in their creation (Mor Barak et al., 1998). Basically, women in the private sector are more supportive of diversity programs because they often feel excluded in the organization.

Second, gender differences in socialization and the obstacles one faces have been shown to result in gender differences in values and attitudes (Dolan, 2000, 2002; Hamidullah, Riccucci, & Pandey, 2015; Johansen, 2007; Nielsen, 2015), particularly on issues such as equal pay, equal employment opportunity, and workforce diversity. For instance, Nielsen (2015) finds in her study of Danish public administrators in six different occupations that female managers are more empathetic than male managers. Hamidullah et al. (2015) find that female senior local government managers place more emphasis on values related to diversity, such as equity, responsibility toward others, and representation compared with men. Dolan (2000, 2002) finds gender differences in spending priorities and support for policies related to affirmative action and pay equity. In terms of gender differences in behavior, research on representative bureaucracy finds that women are more likely to help other women inside the organization or the organization’s clients (Keiser et al., 2002; Wilkins, 2007; Wilkins & Keiser, 2006).

Moreover, female managers are often more inclusive. A key part of successful promotion of diversity in the organization is the acceptance or inclusion of all workers, but particularly of minority workers who often feel excluded. Inclusion occurs when workers have “access to information, connectedness to co-workers, and the ability to participate in and influence the decision making process” (Mor Barak, 2000, p. 341). Female managers are considered more inclusive because they are more likely to engage in managerial behaviors that make workers feel that they are a critical part of the organization—female managers are more likely to share information, power, and decision making with others (Rosener, 1990). Women are often more inclusive, so they may be more open to diversity in ideas and cultures, which is particularly important in service organizations.

Considering both the research on gender differences in workers’ openness to diversity programs and gender differences in managerial values, attitudes, and behavior, we expect that female and male managers will place different levels of priority on diversity.

Hypothesis 1: There are gender differences in managerial priority placed on diversity.

Sector Characteristics That Influence Priority on Diversity

Despite some significant differences in organizational and environmental factors across sectors (Nutt & Backoff, 1992), there has been little research that compares managerial practices regarding diversity across the sectors. Literature on cross-sector differences finds that managers in the three sectors embrace different organizational values and face different institutional constraints, which can affect managerial practice (Bullock, Stritch, & Rainey, 2015; Chen, 2012; Feeney & Rainey, 2010; Johansen & Zhu, 2014; Lee & Wilkins, 2011). Because institutional settings can affect behavior, the decision of managers to prioritize diversity may differ across sectors.

Two theories provide insight into why priority placed on diversity may vary across the three sectors: the theory of organizational socialization and resource-based theory. The theory of organizational socialization emphasizes the “normative contexts within which organizations exist” (Yang & Konrad, 2011). Institutional contexts, such as laws, regulations, goals, and professional norms, can limit and enable various behavior and actions (Peters, 1999; Scott, 2001). Individuals may enter organizations with different personal values and views, but because of their exposure to certain organizational values, over time “they become assimilated to the culture and values of the organization for which they work” (Dolan, 2002, p. 358). Therefore, it is conceivable that distinctive organizational contexts in different sectors may be tied to different managerial priorities regarding diversity.

An important institutional difference across sectors that can affect managerial priority on diversity is the formalization of organizational values. For example, managers in public organizations operate in a context with laws and regulations that require diversity policies and methods, and human resource management (HRM) in public organizations is more standardized and more formalized than in private sector organizations (Groeneveld & Verbeek, 2012). In other words, diversity programs and policies in public organizations are often more institutionalized than in private and nonprofit organizations, which could lead to different managerial priorities on diversity across the sectors.

In addition, public organizations are often supposed to serve as an example to private sector organizations with respect to enforcing nondiscrimination policies and equal employment opportunity laws (Boyne, Jenkins, & Poole, 1999; Groeneveld & Verbeek, 2012). Thus, there may be political pressure to improve the representation of minorities, which can feed into concerns about the legitimacy of the organization (Rangarajan & Black, 2007). This political pressure to improve an organization’s diversity could affect managerial priority on diversity. Indeed, research finds that public sector organizations have more diversity policies than private organizations (Groeneveld & Verbeek, 2012; Kelliher & Parry, 2011) and that the motivation for diversity policies in the public sector is linked to issues of legitimacy and democracy (Groeneveld & Van de Walle, 2010; Riccucci, Van Ryzin, & Lavena, 2014). Differences in legal requirements, political pressure, and concerns about legitimacy across the sectors may influence the priority managers place on diversity, and could result in sector differences in managerial priorities.

Organizational socialization theory, however, suggests that similarities in managers’ educational and professional experiences contribute to organizational isomorphism, where managers behave similar to one another no matter what sector they are in (DiMaggio & Powell, 1983). Thus, in an environment where public services are provided by organizations in all three sectors, it is possible that all managers in all three sectors will place a similar level of priority on diversity (Pitts et al., 2010).

The second theory that posits cross-sector differences in managers’ diversity on priority is resource-based theory, which states that the nature of the resources held by organizations determines their competitiveness and ultimately their success. This theory informs the “business case” for diversity, whereby managers prioritize diversity to be more competitive through finding the best talent, and enhancing market share by being able to deal with a diverse customer base and increasing innovation and creativity (Cox & Blake, 1991; Jayne & Dipboye, 2004; Yang & Konrad, 2011). The need to be competitive drives private managerial priorities on diversity.

Research finds that nonprofit organizations, and more recently public organizations, also pursue diversity for the business case although to a lesser extent than private organizations (Groeneveld & Van de Walle, 2010). Indeed, Nutt and Backoff (1992) note that the main goal for nonprofit organizations is both equity and efficiency, whereas for public organizations, the goal is equity, and for private organizations, the goal is efficiency. Kelliher and Parry (2011) find that many nonprofit organizations have changed their HRM practices to be more like public sector practices in response to government pressure through government contracts. Nonprofits are also concerned with diversity because it allows them to be more sensitive to the needs of their stakeholders and to better advocate for their clients (LeRoux, 2009).

Given that both the theory of organizational socialization and resource-based theory imply that there may be cross-sector differences in priority placed on diversity, we hypothesize the following:

Hypothesis 2: There are cross-sector differences in managerial priority placed on diversity.

A Moderating Effect of Sector on Gender Differences

The influence of gender on a manager’s priority on diversity may vary by sectors. Specifically, the impact of a manager’s personal characteristics on priorities can be moderated by the manager’s institutional context. Managerial priorities are conditioned by different types of informal and formal institutions, norms, and values that limit and enable actions in organizations (Nielsen, 2015; see also Dolan, 2000, 2002; Feeney & Rainey, 2010; Peters, 1999; Scott, 2001). In this article, we focus on two such conditioning factors: discretion and organizational socialization.

In regard to discretion, informal and formal institutions determine the level of discretion an employee has, and discretion affects the actions employees can take. For instance, research finds that a manager’s level of discretion affects managerial practices such as performance information use, strategic management, and representative behavior (Finkelstein & Hambrick, 1990; Moynihan & Pandey, 2010; Sowa & Selden, 2003).

Discretion also influences the impact of personal characteristics such as gender on attitudes and behavior (Keiser et al., 2002; Meier & Bohte, 2001; Sowa & Selden, 2003; Wilkins & Keiser, 2006). Indeed, Keiser et al. (2002) theorize that for personal characteristics to influence representative behavior, the person must have discretion. Research also shows that greater discretion leads to greater representative behavior by both racial minorities and women (Meier & Bohte, 2001; Sowa & Selden, 2003). Moreover, Nielsen (2015) finds that “when discretion is limited, so is the room for individual characteristics to affect behavior” even in nongendered policy areas (p. 1008). As such, we propose that differences in managerial discretion due to the sector the manager is in may moderate the influence of gender on the priority that managers place on diversity.

Another factor that may condition the influence of gender on managerial priority on diversity is organizational socialization. Specifically, the theory of organizational socialization argues that administrators are socialized by their organization to adopt and internalize the values of the organization they work in, thereby minimizing the influence of their own personal attitudes in the workplace (Dolan, 2002; Hamidullah et al., 2015; Thompson, 1976).

For example, Dolan (2002) finds evidence that organizational socialization affects spending priorities. She compared the spending priorities of male and female top public executives in the same agency and across agencies and found that spending priorities between women and men in the same agency were more similar than their same sex counterparts in other federal agencies. In other words, socialization occurred in that women and men in the same agency shared consistent priorities as compared with those outside the agency. However, she still found a gender gap in attitudes within agencies. She concluded that both gender and socialization shape priorities. This accords with Alexis and Wilson’s (1967) suggestion as summarized by Dolan (2002) that managers are “influenced by their own values, and some of these values, in turn, are shaped by their working environments” (p. 355). Thus, we posit that organizational socialization, and differences in managerial discretion, may moderate the effect of gender on the priority that managers’ place on diversity.

Hypothesis 3: Gender differences in managerial priority placed on diversity vary across sectors.

Data and Method

The American health care domain provides a suitable context to compare gender and sector differences in managerial priority on diversity, and how gender differences may vary by sectoral ownership of service organizations. The U.S. health care system is a regulated market system, involving hospitals from all three sectors that provide care services to a very diverse clientele. Public, nonprofit, and private hospitals in the United States share similar operational procedures and the training of personnel. However, hospitals across the three sectors differ in legal property ownership, their revenue streams, clientele characteristics, and the sale of their services. Thus, although managers in the three sectors have comparable training and backgrounds, they face different internal and external constraints due to sector differences that affect their managerial priorities.

Data on managerial practice were collected from an originally designed mail survey sponsored by the Project of Equality, Representation, and Governance at Texas A&M University. The survey used a convenient nonprobability sample of all 6,000+ registered American Hospital Association (AHA) member hospitals. Top-level managers (CEOs) of the sampled hospitals were the survey respondents. Survey questionaires were mailed between December 2010 and March 2011 to hospitals’ AHA registered mailing addresses. To improve the survey response rate, additional surveys were sent to the hospitals that did not respond to our initial inquiry. In total, we mailed out four waves of the survey questionnaire, which produced a representative sample of almost 1,000 valid responses and covers the full spectrum of hospitals’ service specializations (e.g., primary care, general surgery, heart, cancer, chronic disease, children’s hospital, psychiatric, etc.). The overall response rate is approximately 16%. Existing studies have proven that it is extremely difficult to engage top-level hospital managers in survey research and to obtain a representative sample covering managers from all the three sectors. For example, Brickley and van Horn (2002) study hospitals’ executive turnover with a large-n sample (more than 2,000 hospitals) but primarily focus on nonprofit hospitals. Goldstein and Naor (2005) survey 814 hospitals in three sectors about their operation management activities and obtained only 195 valid cases, which produced vary small samples for both public (six cases) and nonprofit hospitals (31 cases). Our survey produces a much larger sample than prior studies such as Goldstein and Naor’s sample. Our survey also proportionally covers hospitals in all three sectors, while existing studies have quite limited samples for both public and private for-profit hospitals. In addition, our survey yielded valid responses on hospitals in most of the states, while many previous studies draw from regional samples or focus on hospitals in one particular state (e.g., Ellis & McGuire, 1996; Grosskopf & Valdmanis, 1987).¹

The survey supplies self-reported measures of managerial priorities, managerial tenure, community conditions, and personal characteristics of top-level hospital managers. The AHA’s Annual Hospital Survey Database provides variables for hospital ownership, service types, and organizational characteristics such as hospital size and geographical location.

Dependent Variable: Managerial Priority on Diversity

Public management researchers often rely on surveys to collect data on organizational leaders’ attitudes, managerial behavior, and how they think about their organizations’ priorities (Zhu, 2015). Our research design uses the same strategy. In the literature, two main types of questions are used to ask about managerial priorities. The first type is to provide a list of organizational goals to respondents, and ask them to rate their priority for each goal based on importance scales (typically measured as an ordinal scale from a low to a high value). For example, using survey questions, Rutherford and Meier (2015) measure managerial priorities in higher education by asking university presidents to rank multiple organizational goals using low-to-high priority scales. For the second type, the respondent is provided with a statement that a specific goal (e.g., efficiency, diversity, personnel management, etc.) is an important priority. Then respondents are asked how much they agree or disagree with the statement. This is the design adopted by Pitts et al. (2010) in their study on Texas superintendents’ priorities on workforce diversity.

We use the first approach to design the survey question about hospital managers’ priority on diversity and cultural sensitivity. In our survey of hospital CEOs, managers were asked questions about the level of priority they placed on a variety of managerial topics. One topic is cultural sensitivity and diversity, which serves as a measure for managerial priority on diversity. Specifically, hospital CEOs were asked to “rank the following current priorities for your hospital” with one of the options being “cultural sensitivity and diversity.”² As managers operate within time and resource constraints, the reporting of a higher priority on cultural sensitivity and diversity indicates that diversity is a high managerial priority. Responses were collected based on a scale ranging from 1 (most important) to 10 (least important). To facilitate the substantive interpretation of the empirical models, we recode the responses into a 1 to 3 ordinal scale.³ We use 1 to denote a low priority on diversity, 2 to denote a medium level of priority on diversity, and 3 to denote a high priority on diversity. Table 1 presents descriptive statistics of all variables, and Table 2 presents additional summary statistics regarding managerial priority on diversity by gender and sector. As shown in Table 2, a very low percentage of respondents reported a low priority on diversity (8.35%), and the majority of managers (51.34%) report that they place a medium level of priority on diversity.

Table 1.

Descriptive Statistics of Variables (N = 898).

Variable	M	SD	Minimum	Maximum
Managerial priority on diversity	2.320	0.620	1	3
Female manager	0.222	0.415	0	1
Public hospital	0.340	0.474	0	1
Nonprofit hospital	0.480	0.500	0	1
Managerial tenure	12.139	9.125	0	49
Minority manager	0.061	0.240	0	1
Business school training	0.266	0.442	0	1
Medical school training	0.288	0.453	0	1
Number of full-time hospital employees	597.615	921.492	12	9,964
Low-income community	2.675	0.871	1	4
Community diversity match	−0.006	0.821	−2.883	1.375
Rural hospital	0.297	0.457	0	1
State diversity	0.457	0.151	0.108	0.712

Table 2.

Managerial Priority Placed on Diversity by Manager Gender and Sector.

	Low priorityDependent Variable = 1 (%)	Medium priorityDependent Variable = 2 (%)	High priorityDependent Variable = 3 (%)
Sample	Low priorityDependent Variable = 1 (%)	Medium priorityDependent Variable = 2 (%)	High priorityDependent Variable = 3 (%)	Sample size
All hospital managers	8.35	51.34	40.31	898
Female managers	5.53	43.72	50.75	199
Public managers	8.20	55.41	36.39	305
Nonprofit managers	9.05	56.61	34.34	431
Private managers	6.79	29.63	63.58	162

Independent Variables: Gender and Ownership

Managerial gender

We measure the managerial representation of women based on top-level hospital manager’s gender. Female manager is coded as 1 if a CEO is female. As shown in Table 2, 22.2% of the survey respondents were women. Nearly 43.72% of women place a medium priority on diversity, and 50.75% place a high priority on diversity. In contrast, 53.51% of male managers place a medium priority on diversity and 37.34% place a high priority on diversity.

Hospital ownership

Hospital ownership is defined and coded based on the AHA classification of hospitals, which places all registered hospitals into one of the three categories: public, private for-profit, and nonprofit. Public hospitals are hospitals that are owned by government, such as federal, state, county, city, or hospital districts. Nonprofit hospitals include church-operated hospitals and all other secular nonprofit hospitals. They qualify for federal tax exempt status under section 501c(3) of the Internal Revenue Code. Private for-profit hospitals include investor-owned for-profit hospitals, partnership and hospital corporations, and individual-owned hospitals. In our analysis, we use two dummy variables, one for public hospitals and one for nonprofit hospitals, leaving private hospitals as the base category. Our sample includes 305 government-owned hospitals (primarily nonfederal hospitals), 431 nonprofits, and 162 for-profits in 49 states and the District of Columbia.⁴

Table 2 reports managers’ priority on diversity based on the full sample and gender and sector subsamples. More than half of public hospital managers (55.41%) reported that they place a medium priority on diversity, and 36.39% said they place a high priority on diversity. The majority of private hospital managers (63.58%), however, report that they place a high priority on diversity, and 29.63% place a medium priority on diversity. More than 56% of nonprofit managers report that they place a medium priority on diversity, and 34.34% of nonprofit managers place a high priority on diversity.

In our sample, 20% of public managers are female, 20.88% of nonprofit managers are female, and 29.63% of private managers are female. The first row in Table 3 reports the percentages of respondents who placed a low, medium, and high priority on diversity by gender based on the full sample. Based on the full sample, we observe statistically different responses by female and male managers. Among all of the female managers, only 5.53% gave a low priority to diversity issues, 43.72% of them reported a medium priority, and 50.75% of female managers reported a high priority. But for male managers, the modal response was to give a medium priority to diversity (53%), while only 37.34% of male managers responded with a high priority. Further comparing female and male managers’ responses in each choice category (low, medium, and high) based on sector subsamples, we observe that in the public sector, the percentage of female managers who reported a high priority (45.90%) is slightly higher than that of male managers (34.02%). In the private sector, we observe the most salient gender differences in reporting a high priority—79.17% female private managers gave a high priority to diversity, but only 57% of male private managers reported a high priority on diversity.⁵

Table 3.

Comparing Female and Male Managers’ Priority on Diversity Within the Public, Nonprofit, and Private Sectors.

	Low priorityDependent Variable = 1		Medium priorityDependent Variable = 2		High priorityDependent Variable = 3
	Low priorityDependent Variable = 1		Medium priorityDependent Variable = 2		High priorityDependent Variable = 3
	Female	Male	Female	Male	Female	Male
All sectors (%)	5.53	9.16	43.72	53.51	50.75	37.34
Gender group size	199	699	199	699	199	699
χ²	2.664**		5.938**		11.585***
Public (%)	9.84	7.79	44.26	58.20	45.90	34.02
Gender group size	61	244	61	244	61	244
χ²	0.272		3.835**		2.978*
Nonprofit (%)	4.44	10.26	56.67	56.60	38.89	33.14
Gender group size	90	341	90	341	90	341
χ²	2.930*		0.0001		1.044
Private (%)	2.08	8.77	18.75	34.21	79.17	57.02
Gender group size	48	114	48	114	48	114
χ²	2.387		3.872**		7.156***

Note. Gender group size reflects the number of female and male managers based on each of the following samples: full sample (all sectors), public hospitals, nonprofit hospitals, and private hospitals. Percentage numbers reflect the percentages within each gender group, who report low, medium, and high priority on diversity. The χ² statistics are based on Pearson’s Chi-Squared Test to compare if the distributions of survey responses are different by gender within each choice category.

p < .10. **p < .05. ***p < .01.

Control Variables

We include three groups of variables to control for other factors that may affect managerial priority on diversity. We first control for managerial and organizational factors internal to a hospital, including managerial tenure, race, professional training and background, and hospital size. Following Finkelstein and Hambrick (1990), who find that top management tenure has a salient impact on both organizational outcomes and managerial decisions, we control for hospital CEO tenure. Managerial tenure is measured based on the number of years a hospital CEO has been in her or his position. Moreover, studies have shown that managers’ social traits such as race and gender can shape their attitudes toward diversity-related issues (Dolan, 2002). Therefore, we include the variable minority manager in our analysis. This variable is coded as a dummy variable, with 1 referring to non-White managers. As Table 1 shows, only 6% of the hospital managers are minority managers.

Furthermore, we control for hospital CEOs’ professional background. Researchers who study executive/bureaucratic identities have shown that leaders’ professional identities affect both organizational culture and their values about how to promote public values (Meyer, Egger-Peitler, Hollerer, & Hammerschmid, 2014). Professional career administrators also behave distinctively from professional public sector leaders (Aberbach, Putnam, & Rockman, 1981; Teodoro, 2014). Given that we include hospital managers from all three sectors, we control for their different professional backgrounds. Professional training and background is measured with dummy variables for managers with certain professional backgrounds. In the U.S. health care system, there are three major types of professional backgrounds for top-level hospital managers (CEOs): (a) professional managers who are trained by business schools, (b) professional health administrators who are trained by public health schools, and (c) managers who have a medicine or health-related science background. As managers with all three professional backgrounds can be found across the three sectors, none of the three sectors is uniquely linked to one professional tradition. We therefore include in the model a dummy variable for managers with a business school background, and a dummy variable for managers with a medical school background, leaving professional health administrators trained by public health schools as the reference category. In our sample (as shown in Table 1), 26.6% of hospital managers have a business school background and 28.8% of hospital managers have medical school training. In addition, we control for hospital size, which is measured with the number of full-time employees.

Beyond factors internal to organizations, Pitts et al. (2010) suggest that environmental contexts also affect managers’ attitudes toward diversity issues and their practice in managing diversity. Managers in uncertain and challenging environmental contexts might be constrained in promoting diversity, or may give a lower priority to diversity issues because they need to turn their attention to managing the external environment. We consider two environmental factors in our models: whether a hospital resides in a low-income community and whether a hospital is in a rural area. Hospitals serving rural and low-income communities face greater financial constraints than those serving high-income urban communities. It is conceivable that managers in these hospitals would face greater resource and environmental constraints and may not rate diversity as a very high priority in their organizations. The variable low-income community is measured based on managers’ descriptions of whether their hospital’s service area is in a low-income area.⁶ Rural hospital is a dummy variable, coded as 1 if a hospital is in a rural area, 0 otherwise. In our sample, 29.7% of the hospitals are identified as in a rural area. In addition, we control for three state-level context variables.

Finally, because hospitals are client-oriented service organizations, emphasizing workforce diversity may help to make a hospital culturally competent in providing care services, particularly if the hospital is in an area with diverse populations. Therefore, we include two variables to capture the hospital community’s demographic characteristics. At the hospital level, we control for how well the diversity of the hospital matches the diversity of the community it serves. Community diversity match is a factor index that measures managerial perceptions of the match between the diversity of hospital personnel and the diversity of the local community. In the hospital management survey, managers were asked whether they agree with the following three statements: (a) “The race/ethnicity of my hospital’s executive team reflects the diversity of our community,” (b) “The race/ethnicity of nonmanagement staff reflects the diversity of our community,” and (c) “The race/ethnicity of physicians and nurses reflects the diversity of our community.” Managerial responses to these three questions were coded based on a 1 to 4 ordinal scale, with 1 referring to strongly disagree and 4 referring to strongly agree. We combine responses to these three questions to create the factor index. A greater index score means a closer match between the race/ethnicity of hospital personnel and the diversity of the local community. For our second variable of community diversity, at the state level, we control for the ethnic diversity of state populations. State diversity is a Blau’s index of the racial/ethnic diversity of state populations. We use the 2010 U.S. Census Bureau population estimates to compute the state diversity index as the following: Diversity = 1 − Σp², whereby p refers to the proportion of state population for a racial/ethnic group.

Model Specification

Because we code managerial priority on diversity based on an ordinal scale, ordered logistic regression models were used to examine the effects of gender, sector, and other control variables on our dependent variable. American hospitals provide a wide range of health services ranging from general primary care services to services for very specialized health concerns, such as cancer, heart, acute long-term care, children’s hospitals, and so on. These different service specializations are likely to influence a hospital’s clientele characteristics and workforce composition. Top-level managers in hospitals with different service specialties may also perceive local market competition differently, which, in turn, affects managerial priority on diversity. To control for any unobserved influence of a hospital’s geographic location and service specialization, we cluster standard errors by service areas and service types.

Results

Table 4 presents our key empirical findings. Model 1 in Table 4 includes only the linear terms of all variables, showing the main effects of managerial gender and sectoral ownership. Model 2 in Table 4 adds interaction terms between female manager and public, and female manager and nonprofit, showing the combined effect of gender and sector.⁷

Table 4.

The Effects of Gender and Sector on Managerial Priority on Diversity.

Variable	Model 1	Model 2
Variable	Coefficient (clustered SE)	Coefficient (clustered SE)
Female manager	0.461*** (0.160)	1.136*** (0.417)
Public hospital	−0.677*** (0.228)	−0.637** (0.274)
Nonprofit hospital	−0.798*** (0.231)	−0.658** (0.271)
Female × Public Hospital	—	−0.862 (0.527)
Female × Nonprofit Hospital	—	−0.834* (0.481)
Controls
Managerial tenure	−0.008 (0.007)	−0.009 (0.007)
Minority manager	−0.023 (0.267)	−0.645 (0.586)
Minority × Public Hospital	—	1.690** (0.763)
Minority × Nonprofit Hospital	—	−0.066 (0.710)
Business school training	−0.334** (0.168)	−0.325* (0.167)
Medical school training	−0.290** (0.137)	−0.289** (0.137)
Number of hospital employees	0.00003 (0.00009)	0.00003 (0.00009)
Low-income community	0.059 (0.078)	0.060 (0.079)
Community diversity match	−0.112 (0.075)	−0.124 (0.079)
Rural hospital	−0.606*** (0.152)	−0.572*** (0.153)
State diversity	2.160*** (0.510)	2.114*** (0.517)
N	898	898
Log-likelihood	−771.567	−765.420
Pseudo R²	.062	.069
Wald χ²(12)	124.02***	137.77***

p < .10. **p < .05. ***p < .01.

Gender Differences in Priority on Diversity

Hypothesis 1 posits that there would be gender differences in managerial priority on diversity. Model 1 in Table 4 shows that the coefficient for female manager is positive and significant (b = .461, SE = 0.160), which means that, without considering cross-sector differences, female managers overall are more likely to place a higher priority on diversity than male managers. This finding provides some support for Hypothesis 1 that there are gender differences in managerial attention to diversity issues.

Cross-Sector Differences in Priority on Diversity

In Table 4, Model 1, we also find support for Hypothesis 2, as both the public and nonprofit variables are significantly associated with managerial priority on diversity. The coefficient for public is negative and statistically significant (b = −.677, SE = 0.228), meaning that public hospital managers place a lower managerial priority on diversity compared with private hospital managers. A slightly larger negative and statistically significant relationship occurs for nonprofit hospitals (b = −.798, SE = 0.231); nonprofit hospital managers place a lower priority on diversity compared with their private hospital counterparts. It is important to recall, however, in Table 2, that the majority of public and nonprofit managers still place a medium priority on diversity.

The Combined Effect of Gender and Sector

Although Model 1 presents evidence for both gender and cross-sector differences, it does not show the full picture about how these two factors affect managerial priority on diversity. Model 2 in Table 4 shows the model with added interaction terms between the gender of the manager and sector. In this model, the coefficient for female manager remains significant meaning that when public and nonprofit are equal to 0 (i.e., the manager is in the private sector); female managers place a significantly higher priority on diversity than male managers. We do not observe statistically significant differences between female and male managers in the public sector (i.e., insignificant interaction term). Both the nonprofit dummy and the interaction term Female × Nonprofit are significant, meaning that nonprofit managers overall are less likely to place a high priority on diversity compared with private managers, but within the nonprofit sector, we observe significant differences between female and male managers (i.e., significant interaction term). This finding suggests a significant interaction effect between female managers and sector. In other words, we find that female managers matter, but their influence is contingent on the sector their organization is in. This provides support for Hypothesis 3.

To further explore the relationship between gender and sector, we graph how managerial gender and sector interactively affect the predicted probability of managerial priority on diversity. Holding all other variables at their means, we use the Clarify program in STATA 12 (King, Tomz, & Wittenberg, 2000) to compute the mean predicted probability of ranking diversity as a high and moderate priority by managerial gender and sector. With these figures, we can compare these mean predicted probabilities with their corresponding 90% confidence intervals (CIs) to evaluate whether there are significant differences between female and male managers’ priority on diversity across the three sectors.

Figure 1 shows the comparison of female and male managers’ probability of placing a high priority on diversity in public, nonprofit, and private hospitals. We observe a significant interaction effect between gender and sector in Figure 1. In the public sector, both female and male managers are not likely to place a high managerial priority on diversity. For female managers in public hospitals, the mean predicted probability of prioritizing diversity is .364 (90% CI = [0.275, 0.456]), while that for male public hospital managers is .340 (90% CI = [0.297, 0.389]). In sum, we do not observe statistically significant differences in the predicted probabilities by gender in the public sector; gender does not seem to matter in the public sector.

Figure 1.

The predicted probability of ranking diversity as a high priority by manager gender and hospital ownership.

Female managers in the nonprofit and private sectors, however, are significantly more likely to rank diversity as a high management priority than their male peers in the same sector. For female nonprofit managers, the mean predicted probability of giving a high priority to diversity is .502, with the lower and higher bound of the 90% CIs being 0.449 and 0.559, respectively. For male nonprofit managers, the mean predicted probability of giving a high priority to diversity is .381 (90% CI = [0.348, 0.416]), which is significantly lower than that for their female peers.

The largest gender differences appear to be in private hospitals. For female private managers, the mean predicted probability of giving diversity a high priority is .642 (90% CI = [0.542, 0.734]), while that for male private managers is only .423 (90% CI = [0.356, 0.495]). In other words, more than two thirds of female managers in the private sector would give a high priority to diversity issues, while only about two fifths of private male managers highly value diversity. Female managers are more likely to place a high priority on diversity than male managers, but only in the nonprofit and private sectors.

Figure 2 presents the comparison of the probability that female and male managers will place a moderate priority on diversity in public, nonprofit, and private hospitals. As Figure 2 shows, both male and female managers in public hospitals are equally likely to place a moderate priority on diversity. Consistent with Figure 1, we observe the most salient gender differences in priority on diversity in private hospitals, and observe no differences between male and female managers in public hospitals. This interesting comparison merits further discussion. One explanation for the equal probability of female and male public hospital managers placing a moderate priority on diversity is that most government-owned hospitals already have institutionalized diversity management initiatives in their human resource departments. In such an organizational context, top-level managers may not need to pay special attention to diversity as the diversity consideration is part of the HRM routine. In sum, our findings provide support for Hypothesis 3—a manager’s gender affects the priority placed on diversity, but the impact of gender depends on sector.

Figure 2.

The predicted probability of ranking diversity as a moderate priority by manager gender and hospital ownership.

In terms of controls, we find that some managerial traits and environmental contexts matter for shaping managerial priority on diversity. Ethnic minority managers in the public sector are more likely to place a high priority on diversity compared with their White counterparts. Managers with business school and medical school backgrounds are much less likely to place a high priority on diversity than managers with public health degrees and other general degree backgrounds. This is similar to findings by Teodoro (2011), who finds that professional norms can explain different managerial behaviors in water utility districts. Managers in rural hospitals are less likely to give diversity a high priority compared with managers in nonrural hospitals. State population diversity has a significant and positive impact on managerial priority on diversity, which means that if a hospital is located in an area with diverse clients, the manager of that hospital is very likely to place a high priority on diversity.

Conclusions and Implications

In this study, we examine gender and sector differences in managerial priority on diversity, and how sectors may moderate gender differences in the priority that managers place on diversity. We find that there are gender and cross-sector differences in the priority that managers place on diversity, and that the importance of managerial gender to managerial priority on diversity differs depending on sector. Most notably, we find greater gender differences in nonprofit and private hospitals than public hospitals. By looking across sectors, we gain insight into the influence of organizational context on how gender influences managerial priorities.

These findings are in accordance with Nielsen (2015), who finds that gender matters in the right context (i.e., when there is discretion). As Nielsen finds, the more the manager’s task is institutionalized, the less effect gender has on behavior (i.e., smaller gender differences). Thus, it makes sense that there are no gender differences in managerial priority on diversity in public hospitals because diversity initiatives are often institutionalized in the public sector. These diversity initiatives grant managers limited discretion, and organizational socialization instills in both male and female public managers with similar organizational values. On the contrary, in contexts where managers have more discretion and less clear socialization of organizational values, such as private and nonprofit hospitals, there are greater gender differences (i.e., gender matters).

Moreover, we find managerial representation of women may increase managerial priority on diversity issues, but only within certain sectors. This more nuanced picture of how female managers prioritize diversity provides evidence about different motivations across the three sectors (Chen, 2012; Johansen & Zhu, 2014). Research finds that different motivations can lead to different types of diversity practices and policies (Groeneveld & Van de Walle, 2010), which can influence their effectiveness (Groeneveld & Verbeek, 2012; Wrench, 2007). Earlier, we proposed that organizational isomorphism may lead to similarities in managerial priorities across the sectors; however, we do not find evidence of this across the three sectors.

This study has a few limitations. First, our survey data only allow us to measure managers’ current priority on diversity. It is possible that some organizations may have already devoted great efforts to diversity, and therefore, their managers may place a moderate or low priority on diversity. Moreover, although managers’ priorities on diversity matter, a high managerial priority on diversity does not necessarily translate into the adoption of diversity programs. These considerations suggest the importance of further study of the implementation of various diversity programs in the three sectors to gain knowledge about how cross-sector differences regarding managers’ diversity attitudes and priorities may affect the practice of diversity management.

Second, in our empirical context, top-level hospital managers (CEOs) do not determine their managerial priorities based solely on their personal preferences. Their preferences are shaped by external influences from hospital boards, clients, and other stakeholders, and by internal influences from other hospital employees (e.g., middle-level managers, physicians, nurses, etc.). Hospital boards are often responsible for setting organizational goals and priorities. Thus, a natural extension of this study would be to explore how both external (hospital boards, clients, etc.) and internal (hospital employees) influences may shape managerial priority on diversity, and whether these influences differ across the three sectors.

Third, gender is not the only social identity that matters for diversity considerations. Due to data limitations, we cannot fully explore how a manager’s race may influence priority on diversity, and a very limited sample size for minority female managers in our data prevents us from further exploring the possible combined effect of a manager’s race and gender. This is unfortunate given that our survey prompt mentions both diversity and cultural sensitivity. However, research has found gender differences related to all aspects of diversity, not just gender diversity, which adds confidence to our measure and our findings. This research leads us to believe that there are broader benefits to be gained from female leaders beyond just having gender-balanced leadership. Because managerial priority on diversity is considered a critical factor in the implementation of various diversity programs, promoting female leaders in large service organizations may help the organization (a) formalize diversity programs more effectively, (b) eventually change the behaviors of male managers and employees by making them value workforce diversity and equal employment opportunity (Selden, Brudney, & Kellough, 1998), and (c) create a more inclusive organization for employees that are often excluded, which is a key component to effective diversity management (Mor Barak, 2013).

To conclude, this study finds that gender matters in shaping managerial priority on diversity issues, but so does the ownership context in which female managers operate. This is because the ownership context can condition managerial priorities due to differing levels of discretion and organizational values due to organizational socialization. If we do not consider cross-sector differences, we may oversimplify and underestimate how and why gender matters.

Although our empirical evidence is derived from the American health care context, our research design can be easily generalized into other service areas where effective diversity management is relevant to the provision of public services. This includes other social and human service areas where workforce diversity is critical to serve clients and/or where services are produced and delivered by organizations in different sectors. Specifically, our study can be generalized to schools and universities, long-term care organizations, job training programs, and other social services.

Footnotes

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.

Notes

Author Biographies

Morgen Johansen is an associate professor of public administration at the University of Hawaii. Her research interests include cross sector differences in managerial behavior, and topics related to diversity and social justice.

Ling Zhu is an assistant professor of political science at the University of Houston. Her research interests include the political economy of welfare policy, social inequality in health care and health outcomes, the management and governance of health service networks, and research methodology.

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