LGBT Diversity and Inclusion, Community Characteristics, and Success

in Journal of Sport Management
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  • 1 Texas A&M University

Drawing from concepts in institutional theory, the purpose of this study was to examine how community measures intersect with lesbian, gay, bisexual, and transgender inclusiveness to predict organizational success. The authors collected publicly available data about National Collegiate Athletic Association departments (N = 65) and their communities. Moderated regression analyses demonstrated significant interactive effects, such that performance was highest when the department followed an inclusive strategy and (a) the lesbian, gay, and bisexual population density was high and (b) the state-level implicit bias toward sexual minorities was low. Importantly, there were no negative effects in following an inclusive strategy, even when institutional logics did not prescribe such an approach. The models explained 60–62% of the variance in performance. The authors discuss theoretical and practical implications.

In 2019, the Atlanta Hawks (of the National Basketball Association; NBA) hosted a “Love Wins” night, with a focus on the lesbian, gay, bisexual, and transgender (LGBT) community (Evans, 2019). Activities included lighting portions of the outside of the arena to create a rainbow effect. The Atlanta Gay Men’s Chorus sang the national anthem prior to the contest, and halftime performers sang about love. The team’s Chief Diversity and Inclusion Officer, Nzinga Shaw, commented that the event and others like it helped to reach new target markets, unify the fan base, and create social good in the community. She remarked: “We are uniquely positioned as a sports organization to create unifying moments . . . . Our role as a sports organization is to be a bridge-builder, finding that connective tissue and bring it all together.” Other teams and leagues have followed suit, focusing on LGBT inclusion to attract fans and grow the success of their enterprise (e.g., Ennis, 2019).

These examples are consistent with empirical research, showing the advantages of LGBT diversity and inclusion for athletes, coaches, teams, and organizations. We consider LGBT diversity to represent the heterogeneity of a unit (whether team, work group, or sport organization) along the diversity dimensions of sexual orientation, gender identity, and gender expression. Inclusion, on the other hand, represents “the degree to which employees are free to express their individual self and have a sense of workplace connectedness and belonging” (Cunningham, 2019a, p. 7).

Researchers have shown that LGBT diversity, LGBT inclusion, and the interaction of the two are all associated, with important outcomes for individuals, teams, and organizations. For example, in a qualitative study set in intercollegiate athletics, the participants noted that LGBT diversity among administrators and coaches allowed for (a) learning among the administrators from those who were different and (b) role modeling to student athletes (Cunningham, 2015). Focusing on LGBT-inclusive environments and their benefits, Anderson et al. have shown that inclusive team cultures link with greater bonding and connection to the team (Anderson, 2009; Anderson & McCormack, 2018). Furthermore, consumers and potential job applicants are attracted to sport organizations that signal their commitment to LGBT inclusiveness (Cunningham & Melton, 2014a; Melton & Cunningham, 2012). Inclusiveness is particularly important for LGBT individuals playing on teams or working in the sport. Inclusive leadership, for instance, is important to LGBT athletes during the sexual orientation disclosure process (Fink, Burton, Farrell, & Parker, 2012). Sexual minority athletes who feel psychologically safe on their teams are likely to have strong sexual orientation identities, especially relative to their peers who play in less welcoming environments (Cunningham, Pickett, Melton, Lee, & Miner, 2014). Furthermore, LGBT employees have reported being able to be more authentic in inclusive workspaces (Cunningham, 2015). Finally, other researchers have examined how group diversity and inclusiveness work in concert to influence positive group outcomes. At the organizational level, groups that couple high LGBT diversity with an inclusive environment are also likely to realize greater creativity, organizational attractiveness, and performance (Cunningham, 2011a, 2011b).

Thus, both LGBT diversity and LGBT-inclusive spaces appear to offer a bevy of benefits for sport organizations and their members. Recognizing these advantages, Cunningham (2015) conducted an in-depth qualitative study to understand how sport organizations created and sustained such environments. Most of the findings pointed to individual, leader, and organizational influences. Cunningham also noted, however, that the external environment was influential, as it helped to shape the activities within the workplace. Others outside of sport have theorized as much, suggesting that community or even regional characteristics might influence diversity activities in the workplace (Ferdman, 2014; Florida, 2012). Such theorizing is consistent with multilevel thinking about organizations and inclusion (Cunningham, 2019a; Ferdman, 2014).

Other than the qualitative and theoretical analyses, an empirical examination of how the external environments influence LGBT diversity efforts and outcomes remains unexplored. This is a meaningful omission because it creates a void in understanding how and to what extent environmental factors relate to the LGBT inclusion—organizational performance relationship. The purpose of this study was to fill this gap. We included two measures to assess the influence of community: LGBT population density, or the relative number of sexual minorities in the state, and the state-level implicit bias expressed toward LGBT individuals. Thus, we focused on a factor that might facilitate inclusiveness and another that potentially detracts from such efforts. Drawing from concepts in institutional theory (Greenwood, Oliver, Sahlin, & Suddaby, 2008), we suspected that the community measures would intersect with LGBT inclusiveness to predict organizational success, as measured by the performance of the athletic teams, and we tested these ideas in the context of intercollegiate athletics in the United States.

Theoretical Framework

We have drawn upon the conceptual foundations of institutional theory to examine the impact of local communities on organizational effectiveness. Consistent with Greenwood et al. (2008), we considered institutions as “more or less taken for granted repetitive social behavior that is underpinned by normative systems and cognitive understandings that give meaning to social exchange and thus enable self-reproducing social order” (p. 4, 5). Institutions exist at multiple levels, including the societal, organizational, and individual levels (Greenwood et al., 2008). Thus, scholars have noted the importance of examining sport organizations from a multilevel perspective (Nite, Hutchinson, & Bouchet, 2019), particularly when studying issues of underrepresentation and inclusion (Burton, 2015; Cunningham, 2010; Melton & Cunningham, 2014).

With this research, we were particularly attuned to the community and organizational levels of analysis. Recently, communities have garnered attention from institutional scholars who have recognized that local institutional contexts influence the evaluation of organizations (Almandoz, Marquis, & Cheely, 2017; Marquis & Battilana, 2009). Communities, whether geographically or affiliation based, tend to have embedded logics that affect expectations of proper behavior (i.e., legitimacy) of organizations (Almandoz et al., 2017; Thornton, Ocasio, & Lounsbury, 2012). Organizations are expected to conform to local normative expectations, especially when local values and customs are highly salient (Marquis & Battilana, 2009). Almandoz (2012) suggested that alignment with local community logics provided higher levels of local support and contributed to the success of newly established organizations.

It should not be surprising that alignment with local logics impacts organizational success. Indeed, communities often share common identities and values that make members more inclined to support those within their community boundaries (Almandoz et al., 2017; Baumeister & Leary, 1995; Bruhn, 2011). Other community factors influence organizational processes and success. Marquis and Battilana (2009) noted that histories and traditions, along with demographic differences, are important for understanding organizational behavior. They suggested that communities embody different sociopolitical ideologies that impact community members’ expectations of local organizations.

The communities within which organizations are embedded have a profound effect on perceptions of legitimacy. Legitimacy represents “a generalized perception or assumption that the actions of an entity are desirable, proper, or appropriate within some socially constructed system of norms, values, beliefs, and definitions” (Suchman, 1995, p. 574). It is important for organizations to be perceived as legitimate, as necessary resources for success and survival tend to be more obtainable for legitimate organizations (Deephouse, Bundy, Tost, & Suchman, 2017; Meyer & Rowan, 1977). Empirically, legitimacy has been linked with different forms of organizational success. Arnold, Handelman, and Tigert (1996), for example, found that being perceived as legitimate within a community impacted store choice and the perceptions of prices and value of products. Others have found that being perceived as legitimate indeed provided greater access to resources (Díez-Martín, Prado-Roman, & Blanco-González, 2013). Assenova and Sorenson (2017) found that conformity with local formalities generally resulted in higher sales and employment rates.

Legitimacy, LGBT Inclusiveness, and Success

Organizational legitimacy is usually evaluated within four general criteria: regulatory, or the degree to which the organization complies with legal mandates and regulations; pragmatic, which reflects the manner in which the organization meets stakeholders’ desired ends; moral, or the extent to which the organization operates within accepted mores; and cultural-cognitive, which reflects how well the organization aligns with engrained normative understandings and processes (Bitektine, 2011; Deephouse et al., 2017). All these mechanisms suggest that, within a given community, there are expectations placed on organizations to engage in certain activities. In the absence of this congruence, organizations are likely to experience performance shortcomings, both in terms of internal processes and desired organizational outcomes.

Applied to the current context of LGBT inclusiveness, this theoretical work might also inform the conditions under which LGBT inclusiveness is related to improved performance. In communities with a high number of LGBT individuals or where inclusiveness is the norm, people might come to expect organizations to also engage in inclusive actions. For example, in his collective case study of LGBT-inclusive athletic departments, Cunningham (2015) reported that administrators and coaches pointed to the influence of the broader community on organizational decisions. These factors included the laws and ordinances in the community, the history of inclusion in the broader university setting, and a broader focus on diversity of all kinds. One study participant, for example, noted that the university “was born out of the abolitionist movement. [The University] prides itself on including people of all types” (as cited in Cunningham, 2015, p. 436). These sentiments are consistent with Ferdman (2014), who theorized that community values and practices served to shape cultural practices and the decisions people made.

Current Study

In the current study, we examined the influence of community characteristics on LGBT inclusiveness and organizational success. We focused on two measures of community characteristics, the first of which is the proportion of LGBT people in the state. As communities become more diverse, the expectations for inclusive actions also increase (Cunningham, 2015). From one perspective, the labor pool in a workplace is likely to mirror that of the larger community in which the employees live. Indeed, Pugh, Dietz, Brief, and Wiley (2008) found that, as the racial diversity of the broader community increased, so did that of the workplaces in their study. Similarly, King et al. (2011), in their study of hospitals, observed that ethnic diversity was strongly related to heterogeneity in the community (see also Singh & Selvarajan, 2013). Such heterogeneity is important because expectations for inclusive and fair processes are likely to increase as organizational diversity does. From a different perspective, when a state is diverse, the constituents might expect services for the different constituent groups. For example, Martos, Wilson, and Meyer (2017) found that, as the proportion of LGBT individuals in an area increased, so did the services provided to that community, thereby meeting their needs and desires.

In the parlance of institutional theory, community diversity is likely to be associated with stakeholder expectations and cultural-cognitive forms of legitimacy (Bitektine, 2011; Deephouse et al., 2017). As previously noted, when organizations do not adhere to institutional norms, the legitimacy of their actions comes into question, and their performance will likely suffer. These dynamics suggest that the relationship between LGBT inclusiveness and organizational performance might vary based on community diversity. In the case of the current study, we captured community diversity with the LGBT population density of the state—that is, how many people within the state identified as a member of the LGBT community. Based on the preceding rationale, we developed the following research question:

Research Question 1: Does LGBT population density influence the relationship between LGBT-inclusive policies and organizational success?

We also examined a second measure of community characteristics: implicit bias toward LGBT individuals. People can express bias explicitly and implicitly. Explicit bias represents “a negative evaluation of a group or an individual on the basis of group membership” (Crandall, Eshleman, & O’Brien, 2002, p. 359). The bias is expressed deliberately and consciously maintained. Increasingly, though, people are unwilling to admit that they harbor explicitly negative attitudes toward others, and many seek to suppress such evaluations (Schuman, Steeh, Bobo, & Krysan, 1997). This is largely due to social norms (Crandall et al., 2002). Illustrative of this pattern, national polls in the United States show improved attitudes toward the LGBT community and associated rights over time (Fetner, 2016).

Despite these changes, other expressions of bias persist. Implicit bias refers to the unconscious bias maintained by people who might otherwise believe themselves to hold egalitarian views (Blair, Dasgupta, & Glaser, 2015). The bias manifests when there is a match between an external stimulus and a person’s internal association set, linking the stimulus with certain characteristics. Researchers have also shown that explicit and implicit forms of bias are weakly related to one another, if at all (Oswald, Mitchell, Blanton, Jaccard, & Tetlock, 2013). This is the case in sport, where for example, parents who purportedly support LGB coaches still exhibit LGB prejudice in subtle, biased ways (Cunningham & Melton, 2014b).

Generally, researchers have examined implicit bias at the individual level. More recently, however, Payne, Vuletich, and Lundberg (2017a, 2017b) persuasively argued that implicit bias takes on a shared property in different communities or regions, and thereby represents a bias of situations or context. They noted that

social interactions, media exposures, moods, memories, and trains of thought that form our more immediate contexts shift from one situation to the next. Individual implicit bias scores will be influenced by all of these factors and more. But like the wisdom of crowds, aggregate responses should converge on the most widely shared influences. Implicit bias can therefore be thought of as the bias of crowds. (p. 237)

A number of researchers have demonstrated the efficacy of considering bias at the aggregate level. Hehman, Flake, and Calanchini (2018), for example, showed that implicit racial attitudes were predictive of racial disparities in police shootings at the metropolitan level of analysis. Marini et al. (2013) showed that country-level implicit fat bias was associated with the obesity rates in the country. In the sport context, Watanabe and Cunningham (2020) showed that market-level implicit racial bias was predictive of attendance at National Football League games following the Black Lives Matter protests.
Collectively, this research suggests that implicit bias can take on a shared property at the community level. From an organizational legitimacy standpoint, implicit biases held by people within a given institutional environment are likely to shape their ideas about what organizational actions are legitimate or permissible (Greenwood et al., 2008). What’s more, implicit bias at the state level takes on institutionalized forms, as it reflects a shared understanding among people in that social setting. This perspective is consistent with Meyer and Rowan (1977), who argued that institutionalization occurs when a given activity or social norm takes on rulelike status. Given these patterns, we suspected that, in the context of the current study, in states with low implicit bias toward LGBT individuals, inclusive organizational activities are likely to be well-received and thus, contribute to organizational effectiveness. On the other hand, when bias within a community is high, LGBT-inclusive policies might be rejected or spur discord, either of which would detract from effectiveness pursuits. Given these possibilities, we developed our second research question:

Research Question 2: Does state-level LGBT implicit bias influence the relationship between LGBT-inclusive policies and organizational success?

Method

Data Collection

We examined our research questions within the context of intercollegiate athletics in the United States. We specifically examined the diversity strategy followed by major National Collegiate Athletic Association athletic departments, a context where LGBT diversity and inclusion has garnered considerable attention (Cunningham, 2019a, 2019b; Griffin, 2012; Klein, Paule-Koba, & Krane, 2019). The athletic departments (N = 65) included all departments in the Power 5 conferences of the Atlantic Coast Conference, Big Ten, Big 12, Southeastern Conference, and Pac 12. As outlined in more detail in the following sections, we gathered data from a variety of publicly available sources and offer an overview of the data in Table 1.

Table 1

Overview of Study Variables

VariableDescriptionMinimumMaximumMeanSD
BudgetAthletic department operating budget (in thousands)6,439.8519,676.9912,210.733,322.85
CoachesNumber of head coaches12.0035.0018.524.67
ConferenceAthletics Equality Index score for the entire athletic conference54.4079.7065.949.29
InclusivenessAthletics Equality Index score5.00100.0064.7417.26
PopDensityState’s population density0.030.050.040.01
ImplicitBiasLGBT IAT score for the state0.060.300.180.05
SuccessDirector’s Cup points153.501,517.50688.12296.16

Note. IAT = implicit association test; LGBT = lesbian, gay, bisexual, and transgender.

LGBT-inclusive strategy

We gathered data from the 2017 Athletics Equality Index (Athlete Ally, 2017) to assess the athletic department’s LGBT-inclusive strategy, Inclusiveness. This is a measure developed by the advocacy group Athlete Ally. After gathering feedback from scholars, coaches, administrators, and advocates in the field, the organization developed an index that assessed the multidimensional nature of organizational strategy. The Index assesses the presence of nondiscriminatory policies, advocates for LGBT equality, LGBT-specific resources, student–athlete-led groups that focus on diversity and inclusion, collaboration with other campus entities, pro-LGBT outreach and campaigns, explicit expectations for fan conduct, and a commitment to transgender inclusion on teams. For the current year, the scores ranged from 5 (on the low end) to 100 (on the high end).

Success

Though there are many ways to conceive of organizational effectiveness, one of the primary indicators at the National Collegiate Athletic Association level is the success of the department’s teams. Thus, we measured Success using points generated in the Learfield IMG Director’s Cup (Learfield/IMG, n.d.). This is an award given to athletic departments based on how well their women’s and men’s teams perform throughout the year. Previous researchers have adopted this approach to examine outcomes of employee behaviors (Rocha & Turner, 2008), department strategy (Cunningham, 2002), and diversity initiatives (Cunningham, 2009, 2011b).

Population density

We drew from the Movement Advancement Project website to gather data related to LGBT population density, PopDensity (LGBT Populations, n.d.). This value reflects the proportion of LGBT adults living in the state.

Implicit bias

We assessed ImplicitBias through the Implicit Association Test (IAT; Greenwald, McGhee, & Schwartz, 1998). As Greenwald, Poehlman, Uhmann, and Banaji (2009) explained, “The IAT assesses strengths of associations between concepts by observing response latencies in computer-administered categorization tasks” (p. 18). Researchers then calculated the response times between various associations to assess the preference for or against the specific target. Thus, as opposed to explicit measures of bias, where participants might respond to a questionnaire about their attitudes toward an LGBT individual, the IAT assesses associations that occur automatically (Devine, Plant, Amodio, Harmon-Jones, & Vance, 2002; Greenwald et al., 2002). Greenwald et al. (2009) overviewed considerable research showing the IAT’s internal consistency, test–retest reliability, and validity evidence.

Researchers at Harvard University have, for years, collected implicit bias data through Project Implicit. The data are publicly available through the Center for Open Science website (https://osf.io). For the current study, we used the public data from 2017 and aggregated the 346,024 responses to the state level to create an ImplicitBias score.

Controls

We also included two department-level controls in the analysis: the number of coaches in the department (Coaches) and the department’s operating budget for women’s and men’s teams (Budget). We included these measures given that organizational size can influence its operations, capacity, and overall ability to achieve desired performance outcomes (Richard, Murthi, & Ismail, 2007; Stanwick & Stanwick, 1998). The data were collected from the Equity in Athletics website, hosted by the U.S. Department of Education. We also controlled for the LGBT inclusiveness of the athletic conference with which the university was affiliated, Conference. We did so by using the conference score Athlete Ally provided in the 2017 Athletics Equality Index (as outlined in the previous sections). Employing this control helped isolate the unique effects of the state-level community factors.

Analyses

We computed the mean and standard deviation for all variables (see Table 1), as well as the correlations among them (see Table 2). We examined the research questions through separate moderated regression analyses, following Cohen, Cohen, West, and Aiken’s (2003) recommendations. Specifically, the three control variables were entered into the first step, followed by the standardized first-order effects, and finally, the interaction terms of interest. We examined the variance inflation factor (VIF) scores to test for multicollinearity, with scores lower than 10 demonstrating no cause for concern (Hair, Black, Babin, & Anderson, 2010). When the interactions were significant, we computed the simple slopes and plotted the nature of the interactions.

Table 2

Correlations Between Variables

Variable1234567
1. Budget---
2. Coaches.46***---
3. Conference−.07.36**---
4. Inclusiveness.02.21.37**---
5. PopDensity.12.35**.65***.38**---
6. ImplicitBias−.01−.27*−.57***−.41**−.70***---
7. Success.58***.54***−.01.27*.21−.11---

*p < .05. **p < .01. ***p < .001.

Results

Descriptive Statistics

As seen in Table 1, the average operating budget for women’s and men’s teams was $12.21 million (SD = 3.32), and the average department employed 18.52 (SD = 4.67) head coaches of women’s and men’s teams. LGBT individuals represented an average of 4% (SD = 0.01) of the state’s population among the states included. Finally, implicit bias ranged from 0.06 to 0.30, with a mean of 0.18 (SD = 0.05), suggesting considerable variability.

We present the bivariate correlations in Table 2. The department’s LGBT inclusiveness was significantly and positively associated with the inclusiveness of the larger athletic conference and the state’s LGBT population density and negatively associated with the LGBT implicit bias in the state. Success was positively associated with the two measures of department size (Budget and Coaches) and the department’s inclusiveness. That is, as inclusiveness increased, so did the Director’s Cup points earned.

Research Questions

The results of the regression analyses are presented in Table 3. The controls accounted for 44% (p < .001) of the variance in the Director’s Cup points earned (see Model 1).

Table 3

Results of Moderated Regression Analyses

Model 1Model 2Model 3Model 4Model 5
VariableBSEBSEBSEBSEBSE
Budget0.03**0.010.03**0.010.03**0.010.03**0.010.03**0.01
Coaches26.08**7.6324.31**7.3328.03***6.5224.50**7.3930.57***6.80
Conference−3.943.42−9.12**4.18−11.12**3.72−7.243.88−11.32**3.63
Inclusiveness------69.41*29.7650.5126.6472.46*30.4849.5227.93
PopDensity------39.0837.3221.6333.18------------
ImplicitBias------------------−12.1034.48−42.3931.84
Inclusiveness × PopDensity------------91.04***21.89------------
Inclusiveness × ImplicitBias------------------------−96.00***24.41
R2.44.51.62.50.60
ΔR2.44***.07*.11***.06*.10***

*p < .05. **p < .01. ***p < .001.

With our first research question, we examined the relationship between LGBT population density, LGBT-inclusive policies, and success. The first-order effects are presented in Model 2 and accounted for 6% (p = .03) unique variance beyond the controls. Inclusiveness was positively and significantly associated with Success (B = 69.41, SE = 29.76, p = .02). These direct effects were qualified by a significant Inclusiveness × PopDensity interaction (B = 91.04, SE = 21.89, p < .001; see Model 3). The nature of the interaction is presented in Figure 1. Simple slope analysis showed that the relationship between Inclusiveness and Success was positive and significant when PopDensity was high (B = 141.55, SE = 31.34, p < .001); however, when PopDensity was low, the aforementioned relationship was not significant (B = −40.53, SE = 37.00, p = .14). The total model explained 62% of the variance in Success.

Figure 1
Figure 1

Relationship between LGBT inclusiveness, LGBT population density, and success. LGBT = lesbian, gay, bisexual, and transgender.

Citation: Journal of Sport Management 2020; 10.1123/jsm.2019-0338

With our second research question, we examined the relationship between LGBT implicit bias, LGBT-inclusive policies, and success. As seen in Table 3 (Model 4), the first-order effects accounted for 6% (p = .04), but neither of the variables reached the level of significance. As with the other analyses, we did observe a significant Inclusiveness × ImplicitBias interaction (B = −96.00, SE = 24.41, p < .001; see Model 5), and inclusion of the interaction contributed 10% unique variance. We showed the interaction plot in Figure 2. Simple slope analysis showed that the relationship between Inclusiveness and Success was positive and significant when ImplicitBias was low (B = 145.52, SE = 33.04, p < .001), but the relationship was not significant when ImplicitBias was high (B = −46.48, SE = 40.75, p = .13). The model explained 60% of the variance in Success.

Figure 2
Figure 2

Relationship between LGBT inclusiveness, LGBT implicit bias, and effectiveness. LGBT = lesbian, gay, bisexual, and transgender.

Citation: Journal of Sport Management 2020; 10.1123/jsm.2019-0338

Discussion

Sport organizations are increasingly adopting strategies to recruit and attract LGBT fans, employees, and consumers (e.g., Ennis, 2019; Evans, 2019), and such efforts link with individual well-being, team outcomes, and various measures of effectiveness. Seeking to understand the factors that help facilitate diverse and inclusive workplaces, scholars have largely pointed to individual, leader-focused, and organizational influences. Importantly, Cunningham (2015) also noted the importance of societal factors, a position consistent with previous theorizing (Ferdman, 2014; Florida, 2012). The purpose of the current study was to extend and empirically test these potential connections. Drawing from institutional theory (Greenwood et al., 2008), we investigated how organizational inclusiveness efforts interacted with community norms of inclusion to predict success, as measured by the winning of the athletic teams. We found that success was the highest when there was alignment between community expectations and the inclusiveness of the sport organization; this pattern held for both of our community measures: LGB population density and LGBT implicit bias. In the space below, we highlighted the contributions to research and practice, highlighted limitations, and identified future directions.

Contributions

The study offers several contributions to the literature. First, from a diversity and inclusion perspective, we offer empirical support for the salience of the external environment. Consistent with the scholarship focusing on institutional logics (Almandoz, 2012), we show that alignment of LGBT-inclusive strategies with community norms benefited the organization. We suspect that, in areas with high LGBT populations and low-levels of implicit bias, inclusive and welcoming logics are salient, so alignment with those logics results in performance gains. Other sport management researchers focusing on external stakeholders and the prevailing institutional logics have offered similar conclusions (Huml, Hambrick, Hums, & Nite, 2018; Nite, Singer, & Cunningham, 2013). Our findings are also consistent with Nilsson’s (2015) work around positive institutional work, whereby adopting inclusive norms and practices helps facilitate greater organizational effectiveness.

Another important element of our work is what we did not find: namely, misalignment did not hurt performance, as the simple slope analyses were not statistically significant in these cases. The findings are consistent with a growing body of research showing that inclusiveness does not imperil performance, even among people who might not value it. For example, Melton and Cunningham (2012) experimentally examined the influence of inclusiveness on organizational attractiveness. For people with egalitarian values, LGBT inclusiveness was positively associated with attractiveness ratings, but for people who did not share such values, inclusiveness did not affect their perceptions of the workplace. Cunningham and Melton (2014a) observed a near identical pattern of findings in their experimental study of LGBT-inclusive fitness clubs. When coupled with the results from the current study, the collective evidence suggests that LGBT inclusiveness can serve to attract the employees or customers for whom fairness is important, and it is associated with performance gains when institutional logics are such that inclusion is salient; however, even when these conditions are absent, such as when fairness and equity are not an individual priority, when the LGB population is low, or the LGBT implicit bias is high, LGBT diversity and inclusion are not detrimental to workplace outcomes. Thus, excuses about environmental constraints prohibiting sport organization leaders from pursuing inclusive work environments ring hollow and do not appear to be evidence based.

From an institutional theory perspective, our findings further point to the importance of multilevel institutional analyses (see also Nite, Hutchinson, & Bouchet, 2019). Interestingly, we found that potential misalignment with individual-level logics did not impede impact organizational success, as measured by team performance. Considering the well-established notion that institutional complexity (i.e., competing institutional logics; see Greenwood, Raynard, Kodeih, Micelotta, & Lounsbury, 2011) impacts various organizational elements, including performance, it is intriguing that incompatible logics were not detrimental in our setting. Similarly, Nite, Ige, and Washington (2019) found that incompatible institutional elements, particularly contestations from peripheral actors, can simply be ignored, as they are inconsequential to performance and survival. Perhaps our findings point to the utility of Besharov and Smith’s (2014) theorizing of logic centrality when considering issues of incompatibility. Future researchers should provide more nuanced, multilevel accounts as to how and why certain logics are nonimpactful in institutional settings, especially in regard to diversity and inclusion topics.

From a methodological perspective, our focus on moderating effects proved efficacious. Previous researchers have shown that (a) developing theoretically based examinations of moderating effects helps uncover when, why, and under what conditions various phenomena might occur (Aguinis, Edwards, & Bradley, 2017), but (b) few sport management scholars test for moderation—a pattern that has remained over time (Cunningham & Ahn, 2019). In our own research, we observed that inclusion of moderators added substantial explanatory power (10 or more percentage) and helped explain when inclusiveness is associated with improved organizational performance.

Implications, Limitations, and Future Directions

Our study also offers a number of implications for sport managers. First, the results show that aligning strategic actions with the prevailing institutional logics is linked with success. Thus, sport managers would do well to survey their institutional environment and key actors to understand the logics in place. We have used easily identifiable measures, density and bias, and sport managers can use similar surrogate measures to gain such an understanding. Others, such as Huml et al. (2018), have suggested targeting key stakeholders to understand their preferences, and diversity and inclusion researchers have also pointed to the salience of stakeholders in shaping organizational policy and action (e.g., Burton, 2015; Schull, Shaw, & Kihl, 2013).

In addition, though organizational inclusiveness–institutional logics fit is associated with performance gains, lack of fit does not appear to impede performance. Thus, we encourage sport managers to pursue the creation and maintenance of LGBT-inclusive workplaces. Even when success gains might prove elusive, the psychological and physical health gains for athletes, coaches, and administrators (see Cunningham, Buzuvis, & Mosier, 2018; Griffin, 2012) makes such endeavors worthwhile.

Furthermore, though our study makes many contributions, there are potential limitations. Primarily, our focus on intercollegiate athletics might have limited direct applicability to sport managers outside North America, where college athletics plays a less central role in the sport landscape. In addition, the Athletics Equity Index was only awarded in 2017 so far, and thus, we have just the one year of data. Finally, some authors have criticized the IAT, our measure of implicit bias (for an overview, see Jost, 2019); thus, some readers might question our use of it in the current study. However, Jost (2019) provided compelling counterarguments to the prevailing criticisms, and Payne et al. (2017a, 2017b) have shown that IAT scores are especially predictive in the aggregate. As we focused on state-level bias (an aggregate score), concerns about our use of the IAT are likely limited.

These limitations give rise to additional research opportunities. Specifically, future researchers should consider expanding our analyses into different sport contexts—ones outside the intercollegiate athletics arena and with additional years of data available. How, for example, do biases at the country or state levels impact sport and physical activity opportunities for different groups? Furthermore, we focused on organizational success, as measured by the performance of the athletic teams. But there are other measures of performance, including both on- and off-field performance (Cunningham, 2007), organizational inputs and throughputs (Chelladurai, 1987), and financial performance (Nowy, Wicker, Feiler, & Breuer, 2015), among others. Future researchers would benefit from examining the associations between diversity, inclusion, and various measures of sport organization performance. Given the increased focus on LGBT inclusion and outreach among sport organizations, and the noted benefits of doing so, such endeavors are likely to be advantageous.

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  • Cunningham, G.B., Pickett, A., Melton, E.N., Lee, W., & Miner, K. (2014). Free to be me: Psychological safety and the expression of sexual orientation and personal identity. In J. Hargreaves & E. Anderson (Eds.), Routledge handbook of sport gender and sexualities (pp. 406415). London, UK: Routledge.

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If the inline PDF is not rendering correctly, you can download the PDF file here.

The authors are with the Center for Sport Management Research and Education, Department of Health and Kinesiology, Texas A&M University, College Station, TX, USA.

Cunningham (gbcunningham@tamu.edu) is corresponding author.
  • View in gallery

    Relationship between LGBT inclusiveness, LGBT population density, and success. LGBT = lesbian, gay, bisexual, and transgender.

  • View in gallery

    Relationship between LGBT inclusiveness, LGBT implicit bias, and effectiveness. LGBT = lesbian, gay, bisexual, and transgender.

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  • Almandoz, J., Marquis, C., & Cheely, M. (2017). Drivers of community strength: An institutional logics perspective on geographical and affiliation-based communities. In R. Greenwood, C. Oliver, T.B. Lawrence, & R.E. Meyer (Eds.), The SAGE handbook of organizational institutionalism (2nd ed., pp. 190213). Thousand Oaks, CA: Sage.

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  • Anderson, E. (2009). Inclusive masculinity: The changing nature of masculinities. New York, NY: Routledge.

  • Anderson, E., & McCormack, M. (2018). Inclusive masculinity theory: Overview, reflection and refinement. Journal of Gender Studies, 27(5), 547561. doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Arnold, S.J., Handelman, J., & Tiger, D.J. (1996). Organizational legitimacy and retail store patronage. Journal of Business Research, 35(3), 229239. doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Assenova, V.A., & Sorenson, O. (2017). Legitimacy and the benefits of firm formalization. Organization Science, 28(5), 804818. doi:

  • Athlete Ally. (2017). Athletic Equality Index. Retrieved from http://www.athleteally.org/wp-content/uploads/2017/09/Athletic-Equality-Index-9_11.pdf

    • Search Google Scholar
    • Export Citation
  • Baumeister, R.F., & Leary, M.R. (1995). The need to belong: Desire for interpersonal attachments as fundamental human motivation. Psychological Bulletin, 117(3), 497529. PubMed ID: 7777651 doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Besharov, M., & Smith, W.K. (2014). Multiple institutional logics in organizations: Explaining their varied nature and implications. Academy of Management Review, 39(3), 364381. doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bitektine, A. (2011). Toward a theory of social judgments of organizations: The case of legitimacy, reputation, and status. Academy of Management Review, 36(1), 151179. doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Blair, I.V., Dasgupta, N., & Glaser, J. (2015). Implicit attitudes. In M. Mikulincer& P.R. Shaver (Eds.), APA handbook of personality and social psychology (pp. 665691). Washington, DC: American Psychological Association.

    • Search Google Scholar
    • Export Citation
  • Bruhn, J.G. (2011). The sociology of community connections. New York, NY: Springer Science and Business Media.

  • Burton, L.J. (2015). Underrepresentation of women in sport leadership: A review of research. Sport Management Review, 18(2), 155165. doi:

  • Chelladurai, P. (1987). Multidimensionality and multiple perspectives of organizational effectiveness. Journal of Sport Management, 1(1), 3747. doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Cohen, J., Cohen, P., West, S.G., & Aiken, L.S. (2003). Applied multiple regression/correlation analysis for the behavioural sciences (3rd ed.). Hillsdale, NJ: Erlbaum.

    • Search Google Scholar
    • Export Citation
  • Crandall, C.S., Eshleman, A., & O’Brien, L. (2002). Social norms and the expression and suppression of prejudice: The struggle for internalization. Journal of Personality and Social Psychology, 82(3), 359378. PubMed ID: 11902622 doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Cunningham, G.B. (2002). Examining the relationship among miles and snow’s strategic types and measures of organizational effectiveness in NCAA Division I athletic departments. International Review for the Sociology of Sport, 37(2), 159175. doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Cunningham, G.B. (2007). Opening the black box: The influence of perceived diversity and a common in-group identity in diverse groups. Journal of Sport Management, 21(1), 5878. doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Cunningham, G.B. (2009). The moderating effect of diversity strategy on the relationship between racial diversity and organizational performance. Journal of Applied Social Psychology, 39(6), 14451460. doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Cunningham, G.B. (2010). Understanding the under-representation of African American coaches: A multilevel perspective. Sport Management Review, 13(4), 395406. doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Cunningham, G.B. (2011a). Creative work environments in sport organizations: The influence of sexual orientation diversity and commitment to diversity. Journal of Homosexuality, 58, 10411057. doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Cunningham, G.B. (2011b). The LGBT advantage: Examining the relationship among sexual orientation diversity, diversity strategy, and performance. Sport Management Review, 14, 453461. doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Cunningham, G.B. (2015). Creating and sustaining workplace cultures supportive of LGBT employees in college athletics. Journal of Sport Management, 29, 426442. doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Cunningham, G.B. (2019a). Diversity and inclusion in sport organizations: A multilevel perspective (4th ed.). New York, NY: Routledge.

  • Cunningham, G.B. (2019b). Understanding the experiences of LGBT athletes in sport: A multilevel model. In M. Anshel (Ed.), APA handbook of sport and exercise psychology (Vol. 1, pp. 367383). Washington, DC: American Psychological Association.

    • Search Google Scholar
    • Export Citation
  • Cunningham, G.B., & Ahn, N.Y. (2019). Moderation in sport management research: Room for growth. Measurement in Physical Education and Exercise Science, 23(4), 301313. doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Cunningham, G.B., Buzuvis, E., & Mosier, C. (2018). Inclusive spaces and locker rooms for transgender athletes. Kinesiology Review, 7(4), 365374. doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Cunningham, G.B., & Melton, E.N. (2014a). Signals and cues: LGBT inclusive advertising and consumer attraction. Sport Marketing Quarterly, 23, 3746.

    • Search Google Scholar
    • Export Citation
  • Cunningham, G.B., & Melton, E.N. (2014b). Varying degrees of support: Understanding parents’ positive attitudes toward LGBT coaches. Journal of Sport Management, 28, 387398. doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Cunningham, G.B., Pickett, A., Melton, E.N., Lee, W., & Miner, K. (2014). Free to be me: Psychological safety and the expression of sexual orientation and personal identity. In J. Hargreaves & E. Anderson (Eds.), Routledge handbook of sport gender and sexualities (pp. 406415). London, UK: Routledge.

    • Search Google Scholar
    • Export Citation
  • Deephouse, D.L., Bundy, J., Tost, L.P., & Suchman, M.C. (2017). Organizational legitimacy: Six key questions. In R. Greenwood, C. Oliver, T.B. Lawrence, & R.E. Meyer (Eds.), The SAGE handbook of organizational institutionalism (2nd ed., pp. 2754). Thousand Oaks, CA: Sage.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Devine, P.G., Plant, E.A., Amodio, D.M., Harmon-Jones, E., & Vance, S.L. (2002). The regulation of explicit and implicit race bias: The role of motivations to respond without prejudice. Journal of Personality and Social Psychology, 82, 835848. PubMed ID: 12003481 doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Díez-Martín, F., Prado-Roman, C., & Blanco-González, A. (2013). Beyond legitimacy: Legitimacy types and organizational success. Management Decision, 51(10), 19541969. doi:

    • Crossref
    • Search Google Scholar
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