Nonprofit Board Governance Policy Adoption: Toward an Integrated Board Interlock Network and Institutional Perspectives

Abstract

Previous research lags behind in illuminating theoretical mechanisms that shape governance decision-making on board practices. Using an integrated theoretical approach, I examine how board interlock network and institutional factors are associated with board governance policy adoption in nonprofit organizations. A linear regression model is employed to investigate policies adopted by a panel of public charities in three cities in Upstate New York during 2008 and 2014. Results show that not only the presence of board interlock networks but also central network positions relate to extensive policy adoption. Results also reveal that the use of paid professionals in management relates to institutional isomorphism reflected by more extensive governance policy adoption. These results provide insights for nonprofit leaders seeking to facilitate good governance practices by paying attention to board members’ affiliations and institutional environment considerations.

Keywords

board governance board governance policy board interlock network institutional perspectives professionalization

Introduction

The establishment of accountable nonprofit governance is at the center of attention in both scholarly and public discussion. Scholars tend to agree that board governance practices are critical for their potential to shape board accountability (Nezhina & Brudney, 2010, 2012), board effectiveness (Bradshaw et al., 1992; Herman & Renz, 2000, 2004), board performance (W. A. Brown, 2005; Gazley & Nicholson-Crotty, 2018), and financial performance (Harris et al., 2015). To the extent that nonprofit operation relies on board governance practices, studying the decision-making on board governance policy adoption is an important agenda to ensure effective management aimed at promoting governance accountability. Despite the known significance of the use of board governance policy, however, theoretical account of why and when governance practices spread remains limited. As such, it is unclear how nonprofit boards decide what policy to adopt and how this decision is made.

Drawing from interorganizational network and institutional theory perspective, I provide theoretical accounts of governance policy adoption that explain how boards’ decision-making is influenced by its board linkages and institutional environments. In doing so, I attempt to respond to the call for research that uses a multi-theoretical approach to investigate a link between boards and organizational behavior (Guo & Acar, 2005; Miller-Millesen, 2003; Stone & Ostrower, 2007; Van Puyvelde et al., 2012).

Among a myriad of theoretical approaches used in nonprofit research, some scholars employ institutional theory to explain institutional pressures facilitating organizational homogeneity, including self-regulation and managerial practices (AbouAssi & Bies, 2018; Bromley & Orchard, 2016; Hersberger-Langloh et al., 2021), accountability and reporting standards (Benjamin, 2008; Verbruggen et al., 2011), and local funding practices (Paarlberg & Meinhold, 2012). From institutional theory perspective, the adoption of certain practices, such as board governance policy, can be considered as one example of institutional isomorphism.

Despite its significant contribution to explaining isomorphism, institutional perspectives offer insufficient attention to the behaviors of organizations embedded in broader social relations (Granovetter, 1985). Consequently, questions associated with interorganizational inter-connections and organizational behavior became central to the research agenda, which invigorated scholarly attention to network perspective. In particular, nonprofit board research has moved from the organization-level boards to interorganizational-level network structures that may influence processes and outcomes of board governance. As noted by scholars, however, current board research provides limited knowledge in elucidating how network relationships influence board governance (Cornforth, 2012; Renz & Andersson, 2013). This is surprising given the growing body of nonprofit research that uses network perspectives, including service provision networks (Van Puyvelde & Raeymaeckers, 2020), collaboration networks (Gazley & Guo, 2020; Guo & Acar, 2005; Ihm & Shumate, 2019), and partnership networks (Atouba & Shumate, 2020; O’Brien et al., 2019).

In this article, I bring attention to board interlock phenomena that occur when board member at one organization joins the board of another organization (Mizruchi, 1996). A board interlock creates interorganizational networks where overlapping board members constitute “ties” that link organizations. Board interlock literature is instructive because it views that actors such as organizations and individuals are socially constructed and embedded in a surrounding context. Board interlock study is a natural extension of board governance research given its theoretical reliance on the role of boards of directors (for synthesis of antecedents and consequences of nonprofit board interlock, see Yoon, 2021). Although scholars are increasingly paying more attention to investigating board interlock in recent nonprofit literature (Esparza & Jeon, 2013; Faulk et al., 2016, 2017; Moore et al., 2002; Paarlberg et al., 2020; Vidovich & Currie, 2012; Willems et al., 2015; Yoon, 2021), they do not explore the question regarding how board linkages such as interlocks shape governance decision-making on board practices (except for Bloch et al., 2020).

In effect, only a few studies look into board linkages (Guo & Acar, 2005; Ihm & Shumate, 2019) in current nonprofit literature, due to methodological issues such as data collection and refinement of network measures. Collecting and analyzing data on board linkages requires immense efforts to produce key measures of networked relationships based on the appointment status of board members. As a result, scholars have had little to say about examining such topics in board governance research. I address this limitation by building a unique longitudinal board interlock network data and empirically testing key network characteristics to extend our knowledge of interorganizational network connections through board linkages.

In this article, I develop a theoretical basis for a claim that board governance policy adoption is influenced by board linkages such as network presence and network position, and institutional forces such as external funding source and professionalization. While both institutional and network perspectives have made fruitful efforts to explain organizational behavior in a broader context, they have yet to be combined systematically. I build multi-theoretical explanations that account for complex interactions between board linkages, institutional pressures, and organizational decisions on governance policy adoption.

I use a hand-collected panel of 501(c)(3) public charities located in three cities in Upstate New York during 2008 and 2014. Results show that not only the presence of board interlock networks (i.e., having interlocking board members) but also central network positions conferred by influential status within networks (i.e., having board linkages connected to well-connected nonprofits) explain variations in policy adoption. Results also reveal that having paid professionals in management and operations contributes to institutional isomorphism reflected by more extensive use of governance policy. These findings lead me to conclude that network embeddedness established through interlocking board members and institutional pressures exerted from professional staffs and executives shape board governance decision-making in policy adoption. I use this knowledge to suggest action related to the promotion of governance practices by attending to board composition and the operating environment.

I begin with a discussion of relevant theory and illustrate how leading factors associate with board governance policy adoption. Sections “Data Collection and Sample” and “Methods” describe the study sample and methodology. Sections “Descriptive Statistics” and “Results” provide an analytic approach and present findings, respectively. Finally, I conclude with discussions and implications for research and practice.

Explanations for Board Governance Policy Adoption

Both network and institutional perspectives share the view that most organizations are inter-connected within an environment in which individual organizations interact in a structured context (Heugens & Lander, 2009; Westphal et al., 1997). Yet, these two perspectives hold different assumptions with respect to the mechanisms through which governance behaviors are shaped by contingent environments. In the absence of prior efforts to integrate these perspectives, I develop a set of arguments that explain how each perspective informs our understanding about the potential link between board linkages, institutional factors, and governance policy adoption.

Board Interlock Network Perspective of Board Governance Policy Adoption

Corporate board interlock literature has offered extensive evidence on the link between board interlock networks and management practices adoption. Here, scholars suggest that interlocking board members serve as network ties through which information and resources spread across the organizations (Davis, 1991; Krause et al., 2019). Specifically, scholarly work reveals that corporate board interlock networks relate to management practices adoption (Bouwman, 2011; Shropshire, 2010; Yoshikawa et al., 2020). These interlocking board members contribute to organizational learning because of their access to a variety of information from other organizations where they sit on boards (Beckman & Haunschild, 2002). Importantly, the presence of board interlock ties and network centrality (i.e., the level of inter-connectivity within networks) influences corporate practices adoption (Okhmatovskiy & David, 2012). Although much is known about how corporate board interlock shapes decision-making over policy adoption, little work has been conducted to delve into this topic in nonprofit organizations. Below, I focus on network presence and network position to describe how each attribute associates with governance policy adoption.

Network presence

Evidence suggests that interlocking board members influence corporate governance by exposing board members to various sources of information and channeling information to key decision-makers (Bouwman, 2011; Davis & Greve, 1997; Shropshire, 2010). Importantly, interlocking board members facilitate management practices adoption by ensuring upper managers about the benefits of using certain practices and policies (Carpenter & Westphal, 2001; Davis, 1991). Furthermore, these board members with multiple board affiliations and memberships help to increase the perceived legitimacy of new management practices such as formal governance policies (Connelly et al., 2010; Shipilov et al., 2010). Following this line of logic and extending to the nonprofit sector, I expect that the presence of a board interlock network (i.e., having at least one interlocking board member) is positively associated with board governance policy adoption.

Hypothesis 1 (network presence): Network presence is positively associated with board governance policies.

Network position

Not only the presence of board interlock networks but also the structure of networks influence board governance policy adoption. Structural characteristics such as network positions reflect the extent to which an organization is linked to other well-connected organizations in the networks. These attributes reveal a focal organization’s influence on the overall network. For example, organizations in central network positions reflect that they are linked to well-connected organizations through interlocking board members. Evidence shows a potential link between network position and organizational behavior, such as corporate philanthropic donations made to nonprofit organizations (Galaskiewicz & Burt, 1991). More relevant to this work, scholars suggest organizations with dense board linkages are better able to access and obtain more information such as management practices because of multiple board affiliations (Davis, 1991; Mizruchi, 1996). In particular, organizations in central network positions are exposed to more sources of information through diverse network ties than those in peripheral positions (Ahuja, 2000; Davis & Robbins, 2005). Thus, I expect the following:

Hypothesis 2 (network position): Network centrality is positively associated with board governance policies.

Institutional Perspective of Board Governance Policy Adoption

In contrast to network perspectives, the institutional theory does not necessarily assume the presence of direct ties to explain organizational behaviors. Rather, scholarly work drawn from institutional theory turns to a question of how organizations become increasingly similar to each other as a result of isomorphic responses to changes in the institutional environment in an attempt to gain legitimacy (DiMaggio & Powell, 1983; Galaskiewicz, 1985; Meyer & Rowan, 1977). A range of institutional forces has been known to stimulate homogeneity in organizational behaviors in response to expectations from government regulations, professional expectations, and collective norms (Heugens & Lander, 2009; Micelotta et al., 2017).

In particular, DiMaggio and Powell (1983) propose the idea that organizations become similar to one another as a result of the three isomorphic forces, including coercive, normative, and mimetic. Coercive isomorphism refers to the pressures arising from political and public agencies that create regulations, conduct oversight, and manage funding relations on which focal organizations are dependent. Normative isomorphism refers to the pressures deriving from professionalization, whereas mimetic isomorphism refers to the pressures stemming from a cognitive tendency to copy other organizations when the best course of action is uncertain (Haunschild & Miner, 1997). Regardless of the type of isomorphic process, institutional theory posits that organizations tend to adopt homogeneous behavioral patterns in response to environmental pressures.

In the context of this article, board governance policy adoption may represent institutional isomorphism in the nonprofit sector. Although many sources of institutional pressures exist that may induce the boards to adhere to written practices, I focus on two forces: coercive forces such as reliance on external funding from which nonprofits secure major source of revenue, and normative forces such as professionalization through which nonprofits are managed by paid professionals.

External funding

External funders such as governments, foundations, and the general public are a major source of coercive isomorphism in the nonprofit sector (DiMaggio & Powell, 1983; Frumkin & Galaskiewicz, 2004; Oliver, 1991; Pfeffer & Salancik, 1978).¹ These funders may exert coercive pressures for nonprofits to adopt certain practices and policies as a way to legitimize governance activities (Bromley & Orchard, 2016; Frumkin & Andre-Clark, 2000; Ostrower & Stone, 2010). For example, nonprofit organizations increasingly face higher levels of government pressure to demonstrate their commitment to effectiveness by establishing a set of standards that lend credibility to management activities (L. D. Brown & Moore, 2001; Frumkin & Galaskiewicz, 2004). Foundation grants may also require reporting on board governance policy designed to promote effective management. In effect, Hodge and Piccolo (2005) and Herman and Renz (2004) find that nonprofits relying on revenue derived from grants and donations report more use of governance practices compared with those that rely on commercial income such as fee for services. Although individual donors do not have a direct institutional influence on nonprofit organizations, they may indirectly influence governing activity by attaching conditions on the utilization of their donated funds (Hansmann, 1996). In particular, the influence of individual donors may be pronounced among nonprofits that depend heavily on charitable contributions (Frumkin & Galaskiewicz, 2004). Accordingly, I predict the following:

Hypothesis 3 (coercive pressures): Reliance on external funding is positively associated with board governance policies.

Professionalization

Board governance policy adoption may also emanate from normative pressures such as expectations from professional bodies (Meyer & Rowan, 1977). Scholars note increasing trends toward professionalization in the nonprofit sector reflected by extensive employment of paid professionals in management (Frumkin & Andre-Clark, 2000; Guo, 2007; Hwang & Powell, 2009). Evidence suggests that increased reliance on professionals in management and operations may influence nonprofit entities to develop and implement formal governance practices (Hersberger-Langloh et al., 2021; Hwang & Powell, 2009; Suárez, 2010). Professionals may serve an important role in policy adoption for two reasons. First, professionals are affiliated with many professional associations where new information is exchanged and promoted through social interactions (Bromley & Orchard, 2016; Ostrower & Stone, 2010). Personal networks created from interactions in those associations may expose professionals to social norms, such as the key benefits of formal rules and evaluation approaches for advanced governance activities (Galaskiewicz & Wasserman, 1989; Marshall & Suárez, 2014). Second, professionals in nonprofits may serve as “crucibles of expertise” (Abzug & Galaskiewicz, 2001) whose knowledge and experience help rationalize organizational decisions by affording legitimacy to organizations. Educational attainment and knowledge possessed by these professionals may encourage governance standards or best practices such as good governance practices (Meyer & Rowan, 1977). Based on findings from previous studies, I hypothesize the following:

Hypothesis 4 (normative pressures): The level of professionalization is positively associated with board governance policies.

Data Collection and Sample

I use two types of data sets: (a) organization-level data set compiled by the National Center for Charitable Statistics (NCCS) Core Files, and (b) board-level data set created from revised Internal Revenue Service (IRS) Form 990 filings. The organization-level data set consists of a wide range of information, including finances, size, and sub-sector classification. To construct board-level data, I use GuideStar to hand-collect the revised IRS Form 990 filings reported by 501(c)(3) public charities in three Upstate New York cities (Albany, Syracuse, and Utica) from 2008 to 2014. The revised Form 990 is exploited to obtain information about board governance, including board governance policy and member information. Based on a list of board member names reported in Form 990 (Section A in Part VII),² an approximate name matching technique is employed to construct network data for board interlock during the study period. I use string matching packages in R to identify matches between the names of the nonprofit board members across the organizations. The initial data set contained an unbalanced panel of 1,811 organization-year observations over 7 years, of which 294 observations had to be removed due to either lack of available data or implausible financial data. For regression analysis, I use a 1-year lag for the independent and control variables, reducing the analytic sample to 1,517 organization-year observations.

Methods

The empirical analysis of this article proceeds in two steps. First, I construct a board governance policy index through a factor analysis, which assesses the latent structure of a variety of board governance policies and determines whether they are inter-correlated. Second, I utilize an aggregate index in the regression model as a dependent variable and model an index as a function of network characteristics and institutional factors, controlling for organization-specific and time- and geographic-specific covariates.

Dependent Variables: Board Governance Policy Index

This article includes a spectrum of board governance policies coded from the revised IRS Form 990 filings, including conflict of interest (COI) policy, whistleblower policy, document retention and destruction policy, and compensation policy for top managers and other key employees. Table 1 offers a brief description of each policy, and the last column displays the variations in the level of adoption for each of the policies examined. The table presents that governance standards recommended by the Sarbanes–Oxley Act (i.e., whistleblower and document retention and destruction policy) are no more likely to be adopted than other board governance policies: About 75% of the examined nonprofits have a whistleblower policy, and about 79% have a document retention and destruction policy. Overall, data summarized in the table reaffirm the findings from previous research, indicating wide variations in board policy adoption status reported in the revised IRS Form 990 filings (Benzing et al., 2011; Harris et al., 2015; Lee, 2016; Saxton & Neely, 2019).

Table 1.

Descriptive Overview of Board Governance Policy Measures Based on IRS Form 990 Submissions.

Indicator	Description	Data source from Form 990	Coding	M
Conflict of interest (COI)	Organization has a written COI policy	Part VI Section B. Question 12a	=1 if yes =0 if no	0.89
Disclosure of COI	Disclose items in COI policy	Part VI Section B. Question 12b	=1 if yes =0 if no	0.86
Monitoring of COI	Annual monitoring of COI policy	Part VI Section B Question 12c	=1 if yes =0 if no	0.84
Whistleblower policy*	Organization has written whistleblower policy	Part VI Section B Question 13	=1 if yes =0 if no	0.75
Document retention and destruction policy*	Organization has written document retention and destruction policy	Part VI Section B Question 14	=1 if yes =0 if no	0.79
Compensation policy for top management employees	Organization has written compensation policy for the review and approval of compensation for CEO, executive director, or top management officials	Part VI Section B. Question 15a	=1 if yes =0 if no	0.77
Compensation policy for other key employees	Organization has written compensation policy for review and approval of that given to other officers or key employees	Part VI Section B. Question 15b	=1 if yes =0 if no	0.58

Note. Policy with asterisk indicates a board governance policy recommended by the Sarbanes–Oxley Act.

In this article, I aggregate multiple policies to create an index score using factor analysis. The index represents a quantitative measure of board governance policy adoption. I apply factor analysis with varimax orthogonal rotation and polychoric correlation coefficients to address the dichotomous nature of the coded indicators for each policy. Results show that distinct latent factors make up policy reported in Form 990. Table 2 presents a factor analysis of the board governance policy. Results reveal that a range of policies loaded onto one factor. For example, a single dominant factor emerged with an eigenvalue of 3.3 (Cronbach’s α = .82), suggesting that all policies contribute to a reliable scale for a single factor which explains 85% of the variance in the data.³ Accordingly, I use the board governance policy index as a dependent variable in the linear regression model to examine the predictors of policy adoption.

Table 2.

Rotated Factor Loadings for Board Governance Policy.

Policy	Factor loading
Conflict of interest policy (COI)	0.81
Disclosure of COI	0.87
Monitoring of COI	0.87
Whistleblower policy	0.63
Document retention policy	0.62
Compensation policy for top management employees	0.50
Compensation policy for other employees	0.43
Eigenvalue	3.30
Variance explained	0.85

Note. Each policy from the IRS Form 990 is defined in Table 1. All policies contributed to a reliable scale for a single index (Cronbach’s α = .82).

Independent Variables

The analysis includes two sets of independent variables. The first includes two measures for network embeddedness, including board interlock network presence and network position. Network presence is operationalized as a dichotomous variable (i.e., coded as a numerical value of 1 when having at least one interlocking board member).⁴ Network position is measured using a weighted eigenvector centrality, operationalized as a numerical variable reflecting the level of inter-connectedness of a nonprofit organization relative to that of other organizations in the network. It measures the extent to which a given organization is connected to other well-connected organizations within board interlock network. A nonprofit with a high eigenvector centrality suggests that it is connected to other organizations that also have a high level of influence or importance over others conferred by their central network positions (Wasserman & Faust, 1994). Eigenvector centrality is used frequently in board interlock network literature as a measure for network position (Chu & Davis, 2016; Paarlberg et al., 2020; Zona et al., 2019).

The second set of independent variables have two institutional measures, including external funding and professionalization. External funding captures coercive pressures exerted from multiple institutional funders, including governments, foundations, and the general public. External funding sources include revenue raised from public and private contributions, gifts and grants, individual donations, grants, and contracts from the government (Carroll & Stater, 2009; Chang & Tuckman, 1994; Galaskiewicz et al., 2006). Following this research tradition, I operationalize external funding as the share of revenue raised from contributions, gifts, and grants (lines 1h of Part VIII from Form 990) divided by total revenue.

Professionalization variable captures the extent to which a nonprofit is staffed and run by paid personnel, including staff members, employees, and CEOs (Hwang & Powell, 2009; Lu & Park, 2018; Suárez, 2010). Following previous scholarly approaches, I use a professionalization index score⁵ created by summing four dichotomous indicators available in Form 990: (a) whether the organization is staffed by any paid full-time personnel (operationalized as the dichotomous variable of employees, reported in Part VIII from Form 990), (b) whether the organization uses only paid personnel to deliver services (operationalized as the dichotomous variable of volunteers, reported in Part I from Form 990), (c) whether the organization is managed by an executive director (operationalized as the dichotomous variable of the presence of the executive director, reported in Part VII from Form 990), and (d) whether the organization maintains a full-time executive director position (operationalized as the dichotomous variable of executive director compensation, reported in Part VII from Form 990).

Control Variables

I add several control variables, including age, volunteer size, board structure, sub-sector, and affiliation. Organizational age is operationalized as the natural logarithm of the years of existence since the start date, and volunteer size is operationalized as the natural logarithm of total volunteers. Both indicators address skewness in the data. Board size is operationalized as the total number of board members. Board oversight is operationalized as the share of independent voting members in the governing body—defined as board member who is not compensated as an officer or other employee, and board member who is not any family member of the existing board member of the organization or related organization (Internal Revenue Service, 2021). Sub-sector variable is created based on five major categories of the National Taxonomy of Exempt Entities (NTEE): education, health, human services, arts, and other. Finally, affiliation is operationalized as the dichotomous variable of whether an organization operates under other nonprofits within a local affiliate system. Finally, time- and geographic-specific effects are controlled in the model by including dichotomous indicators.

Descriptive Statistics

Table 3 presents descriptive statistics for the variables during the study period. The sample average for network presence is 0.61, meaning that over one half of all examined nonprofits had at least one interlocking board member on their boards. The average network position is 0.07, indicating that network ties connected to the nonprofits in the sample are relatively low. The average of external funding is 0.41, indicating that about 41% of the total revenues of the nonprofit organizations in the sample come from external funding sources, including contributions, gifts, and grants. The average professionalization index is 2.82, suggesting that the examined nonprofits tend to have paid leadership and staff. Descriptive statistics indicate that nonprofit organizations included in the data set are generally large and well established, as reflected by age and volunteer size. The nonprofits have about 19 board members, and nearly 90% of the total voting members are independent in the governing body. This predominance in board oversight suggests a strong board oversight in the nonprofits included in the study sample. Most organizations are in the areas of human services and health (about 69% of the total sample). Finally, only 3% of the organizations are nonprofits within a local affiliation system, meaning that most of the organizations in the sample are independent nonprofit organizations that are not affiliated with other organizations.

Table 3.

Descriptive Statistics.

Variable	M	SD	Minimum	Maximum
Network presence	0.61	0.49	0	1
Network position	0.07	0.19	0	1
External funding	0.41	0.38	0	1
Professionalization	2.82	0.99	0	4
Age	35	18	7	88
Volunteer size	226	765	0	6,000
Board size	19	11	1	88
Board oversight	0.90	0.25	0	1
Sub-sector
Education	0.11	0.32	0	1
Health	0.26	0.44	0	1
Human services	0.43	0.49	0	1
Arts	0.06	0.24	0	1
Other	0.13	0.33	0	1
Affiliation	0.03	0.17	0	1

Note. The natural logarithms for age and volunteer size variables are used in the main regression analysis (see Table 4).

Results

Table 4 displays the estimates from the regression model. Model 1 presents an estimation model that includes network embeddedness variables and control variables. The results show that both board interlock network presence and network position are positive and strongly associated with extensive use of board governance policy. Model 2 includes institutional variables and control variables. Estimates indicate that reliance on external funding is negative albeit non-significantly associated with written policy. The indicator for professionalization reveals a positive and statistically significant association with the governance policy, suggesting that nonprofits with paid leadership and staff are more likely to adopt a policy.

Table 4.

Results of Predictors for Board Governance Policy Adoption.

Variables	Model 1	Model 2	Model 3
Network embeddedness
$N e t w o r k p r e s e n c e_{n t - 1}$	0.223***	—	0.184**
$N e t w o r k p o s i t i o n_{n t - 1}$	0.322***	—	0.276***
Institutional forces
$E x t e r n a l f u n d i n g_{n t - 1}$	—	−0.206	−0.172
$P r o f e s s i o n a l i z a t i o n_{n t - 1}$	—	0.174***	0.166***
Controls
$L o g {(A g e)}_{n t - 1}$	−0.001	0.002	−0.006
$L o g {(V o l u n t e e r s i z e)}_{n t - 1}$	0.003**	0.005***	0.005***
$B o a r d s i z e_{n t - 1}$	0.006*	0.009**	0.005
$B o a r d o v e r s i g h t_{n t - 1}$	0.466**	0.597***	0.539**
Sub-sector
Education	0.385	0.324	0.370
Health	0.749***	0.660**	0.663**
Human services	0.567**	0.518**	0.528**
Other	0.596**	0.578**	0.588**
$A f f i l i a t i o n_{n t - 1}$	0.139	0.040	0.109
Year effects	Y	Y	Y
City effects	Y	Y	Y
Constant	−1.042	−1.381	−1.346
Observations	1,517	1,517	1,517
Adjusted R²	0.122	0.143	0.154

Note. Robust standard errors clustered by organizations (*p ≤ .10. **p ≤ .05. ***p ≤ .01). Analytics sample includes observations in years with complete data.

Model 3, the main model, includes board interlock network factors, institutional factors, and control variables. It explains about 15% of the total variance, which surpasses that of the two previous models (12% and 14%, respectively). Overall, the results reveal that not only the existence of interlocking board members on a board but also network centrality (i.e., the extent of being connected to other well-connected nonprofits) contribute to policy adoption (Burt, 1976; Shipilov et al., 2010). Thus, these findings support Hypotheses 1 and 2, suggesting that nonprofits with interlocking board members and those in central network positions are more likely to use extensive policies in managing governance operations. In particular, findings of network position are interesting because it suggests that not every nonprofit organization is connected in the same way within the board interlock network, and not every organization has the same amount of influence in governance policy adoption. Hypothesis 3 is not supported, reflected by negative and non-significant estimates for the external funding variable. Finally, the indicator for professionalization is positively and significantly associated with governance policy, thus supporting Hypothesis 4.

Among control covariates, variables such as volunteer size, board size, board oversight, and sub-sector are positively and significantly associated with governance policy adoption. Findings for organizational size covariates add evidence to previous literature showing that nonprofit size is positively associated with board governance policy (Iyer & Watkins, 2008; Nezhina & Brudney, 2010; Ostrower & Stone, 2010). Furthermore, positive effect of board oversight suggests a role of independent board members in governance decision-making. Finally, results show rather strong effects for sub-sectors (baseline group is arts). Here, the nature and type of services provided by health-related nonprofits may further promote extensive adoption of policy to meet regulatory requirements. Taken together, overall findings suggest that network embeddedness and professionalization relate to board governance policy adoption, while controlling for organization-specific and time- and geographic-specific covariates.

Discussion and Conclusion

I began this article by noting that research on nonprofit governance practices has primarily followed institutional theory, whereas only a few studies have used board interlock network perspective. By integrating the two perspectives, this article sheds light on how network embeddedness and institutional pressures exerted from operating environments jointly influence boards’ decision-making on governance policy. Results strongly support proposed hypotheses showing that network presence, network position, and professionalization are conducive to explaining policy adoption. These findings add suggestive evidence that having board linkages and paid professionals fosters written standards designed to enhance governance operations.

This article makes at least three contributions to research and practice. First, it is among the first attempts toward an integrated theoretical understanding of boards and their behavior in governance policy adoption. Findings highlight that board linkages and environmental considerations do make a difference in the use of a range of governance policies. Previous studies have exclusively devoted attention to either institutional or network perspectives to explore organizational phenomena in the nonprofit context. As noted by Renz and Andersson (2013, p. 19),

a growing number of scholars advocate the development of multi-theoretical perspectives, based on the recognition that nonprofit governance is complex and often paradoxical, and that single theories are too one-dimensional and narrow to effectively explain key aspects of nonprofit governance.

On this account, results from this article provide a starting point for future scholarly work that seeks to integrate theoretical foundations of governance research by demonstrating the usefulness of combined theory-based frameworks (Guo & Acar, 2005; Miller-Millesen, 2003; Stone & Ostrower, 2007; Van Puyvelde et al., 2012).

In particular, the role of board interlock has rarely been discussed as potential carriers of governance practices in nonprofit organizations (except for Bloch et al., 2020; Galaskiewicz & Wasserman, 1989; Yoon, 2021). While previous research neglects to take board linkages into account and overlooks the implication of network embeddedness (except for Guo & Acar, 2005; Ihm & Shumate, 2019), this article offers evidence on network presence and network position conferred through interlocking board members. The results broaden theoretical insights into understanding how the process and outcomes of governance is shaped by interorganizational relationships between nonprofit organizations (Cornforth, 2012; Renz & Andersson, 2013; Van Puyvelde & Raeymaeckers, 2020).

Second, this article advances institutional account of nonprofit governance practices. The findings clarify that institutional factors have a significant impact on board governance policy adoption, implying that the decision-making of the board of directors is shaped considerably by broader environmental considerations. The finding of a significant relationship between professionalization and board governance policy is interesting. Literature suggests that normative pressures exerted from professional bodies may influence the boards to employ formal written practices primarily because of increased legitimacy concerns (Hersberger-Langloh et al., 2021; Hwang & Powell, 2009; Suárez, 2010). Results confirm prior findings by revealing that the professionalization hypothesis applies to governing practices in nonprofit boards. This makes sense given the pervasiveness of having paid staff and executive leadership in nonprofit organizations to attract and retain competent human resources for effective management (W. A. Brown, 2007; Guo et al., 2011).

Third, this article also has implications for practice. Establishing accountable nonprofit board governance is an important goal for nonprofit managers. To achieve this goal, however, a governance policy designed to enhance governance must spread among nonprofit organizations. Findings offer valuable knowledge that nonprofit managers can employ when seeking to induce such organizational homogeneity in board behavior. A subset of policies assessed in this work is considered as “best practices” and “good governance practices” targeted to enhance transparency and accountability in nonprofit organizations (Benzing et al., 2011; Iyer & Watkins, 2008; Nezhina & Brudney, 2010, 2012; Ostrower & Stone, 2010). On this account, findings highlighting the significance of board linkages raise important questions regarding the potential of board composition in facilitating such governance standards. Perhaps not only having an interlocking board member but also being connected to other central nonprofits within overall networks may help to promote governance practices.

Finally, the limitations of the analyses encourage further investigation. First, results do not apply to nonprofits operating in other geographic contexts during different time periods. Similarly, findings may not be generalizable to small-sized organizations that are not subject to the filing requirements of the IRS Form 990. Given the economic and regulatory changes that have occurred in recent years that may influence nonprofit board governance, future studies may extend the findings using more recent data.

Second, it is worth noting that findings of network embeddedness can raise the question of causal circularity. For example, does governance policy adoption occur because of network connections through interlocking board members? Or, does interlocking board member tend to sit on boards that already use extensive governance policies? I argued that policy adoption is driven by network connections and used 1-year lagged explanatory variables in the analytic model, although undoubtedly, the reverse direction in the interpretation could also be true. A study that uses a larger sample of nonprofits with different panel estimator would make a valuable addition to our knowledge of the link between board interlock and governance behavior.

Footnotes

Acknowledgements

I would like to thank the anonymous reviewers for their thoughtful feedback and for their helpful suggestions.

Author’s Note

This article was accepted under the editorship of Dr. Chao Guo.

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.

ORCID iD

Nara Yoon

Notes

Author Biography

Nara Yoon is an assistant professor in the School of Strategic Leadership Studies at James Madison University. Her research interests focus on governance in public and nonprofit organizations, public policy, and volunteer management.

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