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A coalition perspective on nonprofit governance quality: Analyzing
dimensions of influence in an exploratory comparative case analysis
Citation: Willems, J., Andersson, F.O., Jegers, M., & Renz, D. O. 2016. A coalition
perspective on nonprofit governance quality: Analyzing dimensions of influence in an
exploratory comparative case analysis. Voluntas: International Journal of Voluntary and
Nonprofit Organizations. Published online before print DOI: 10.1007/s11266-016-9683-6
Abstract
We answer the call that governance research should focus more on processes outside the
boundaries of boards, especially for nonprofit organizations. In particular, we suggest and
elaborate concrete steps with respect to the advantages of a leadership coalition perspective to
focus more on the behavioral and informal aspects of governance. Through a comparative case
analysis of five nonprofit organizations we explore contingencies between characteristics of
nonprofit leadership coalitions and governance quality. We identify two dimensions to classify
leadership coalitions: centralized versus diffused influence, and specific versus holistic influence.
These dimensions are subsequently related with observed governance quality. We frame our
finding in the existing literature on group faultlines, which are socially-construed dividing lines
within groups, and we discuss the importance of establishing a balanced coalition between a
weak or non-existent and a strong dominant coalition to ensure high governance quality. We also
present propositions on how governance quality and its various sub-dimensions can be studied as
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a complex, non-linear intermediate concept between coalitional aspects of leadership groups and
nonprofit organizational performance. Finally, we discuss concrete avenues for further testing
and verification of our theoretical interpretation.
Key Words: nonprofit governance quality; leadership coalitions; comparative case analysis
Introduction
Governance has long been a central and important topic in the organizational and
management literatures (Daily, Dalton & Cannella, 2003; Gabrielsson & Huse, 2004). Moreover,
governance still continues to attract attention from researchers and practitioners in the areas of
both corporate governance (among others: Aguilera & Jackson, 2003; Hambrick, van Werder &
Zajac, 2008; van Ees, Gabrielsson & Huse, 2009) and nonprofit governance (among others:
Parker, 2007a/b; Callen, Klein, & Tinkelman, 2010; Cornforth, 2011). Yet, despite its relevance,
popularity and significant progress, some scholars note that governance scholarship “has so far
yielded conflicting and ambiguous results” (van Ees et al., 2009, p. 307) and “what we know
about the efficacy of corporate governance mechanisms is rivaled by what we do not know”
(Daily et al., 2003 p. 371).
In addition, governance scholars have also started to critically examine the dominant reliance
on agency theory in governance research (Daily et al, 2003; Gabrielsson & Huse, 2004). Despite
the fact that agency theory still is and will likely continue to be a powerful approach, alternative
lenses are needed to enable scholars to look beyond its basic assumptions (Blair & Stout, 2001).
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Boards exist for multiple reasons and do more than simply scrutinize managers on behalf of
shareholders (Daily et al., 2003). As a result, several scholars have called for new and different
approaches to expand the scope of existing governance research, and to challenge conventional
wisdom about organizational governance and boards (Daily, Dalton & Cannella, 2003;
Gabrielsson & Huse, 2004; Hambrick, van Werder, & Zajac, 2008; Huse, Hoskinsson, Zattoni &
Viganò, 2011).
In particular, informal and behavioral aspects deserve more attention, in contrast to the formal
and structural governance aspects that are often dealt with in contributions on board composition
and documented practices (Hambrick et al., 2008). Hence, empirical research is needed that
includes direct observations of behavior, input from multiple respondents within organizations,
and a qualitative and quantitative investigation of such observations, both for overall governance
research (Hambrick et al., 2008; Lynn et al., 2000; Van Ees et al., 2009) and for the specific area
of nonprofit governance (Parker, 2007a/b; Stone & Ostrower, 2007). Redirecting the focus on
these behavioral elements would recognize that organizations’ governance practices and their
quality can be contingent upon the relative power positions of the individuals involved in
organizational governance practices (van Ees et al, 2009).
Furthermore, in the particular subarea of nonprofit governance an additional challenge
remains. Nonprofit organizations are incredibly heterogeneous with regard to mission and
purpose, which has important governance consequences. Several goals might be at the origin of
existence for a single organization. For example, a development organization can simultaneously
focus on awareness creation in Western countries in combination with improving life quality in
developing countries. Both these goals may well support each other in the long term but, when it
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comes to allocation of scarce resources, tradeoffs have to be made in the short term. Such
complexity requires a nonprofit organization’s governance processes, rather than its managerial
strategic and tactical processes, to address the preferences and interests of a multitude of potential
stakeholders (Herman & Renz, 2000; McClusky, 2002; Solansky, Duchon, Plowman, &
Martínez, 2008; Willems, Jegers & Faulk, 2016). Moreover, multiple organizations might be
involved in the achievement of a single goal (e.g. maintaining the environment), which makes it
difficult to distinguish the impact of any single organization (Kaplan, 2001; Perrow, 1961;
Willems, Boenigk & Jegers, 2014). Hence, the governance function for a nonprofit organization
often can be substantially less delineated by the boundaries of a single organization and its direct
stakeholders and, instead, is spans a broad network of closely related organizations (Willem &
Lucidarme, 2014; Vangen, Hayes & Cornforth, 2014; Willems, Van Puyvelde, Jegers,
Vantilborgh, Bidee & Pepermans, 2015; Faulk, Willems, Johnson & Stuart, 2016). As a result,
given the nature of nonprofit organizations, the research community is still undecided about
where traditional insights from corporate governance can be applied to nonprofit organizations
versus where a more specific or independent course should be pursued.
Given (1) the need for a stronger focus on the informal and behavioral aspects of governance
and (2) the nature of nonprofit organizations that might call for a dedicated governance research
approach, it is our aim to develop a theoretical framework that enables an understanding of
nonprofit governance based on the behavioral relationships among individuals involved in the
governance processes of nonprofit organizations. We use the perspective of leadership coalitions
and build on the relevant literature from which we derive two dimensions to conceptualize the
interpersonal influence dynamics of individuals involved in governance process of nonprofit
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organizations. Subsequently, we describe a qualitative case comparison analysis, in which we
document for five nonprofit organizations the contingencies between behavioral coalition
characteristics and nonprofit governance quality. We contrast the observed contingencies with
existing literature on corporate and nonprofit governance to provide an initial theoretical
perspective and propose avenues for further research.
Nonprofit Governance Quality
Similar to for-profit corporate governance research, nonprofit governance research has to date
targeted mainly the attributes, structures and roles of boards of directors. The board is often
considered the central actor in the governance process and thus the principal unit of analysis for
studying how governance affects organizational output and performance (Brown, 2005; Callen,
Klein & Tinkelman, 2010; Green & Griesinger, 1996). However, given the inherent
characteristics of nonprofit organizations, nonprofit governance and boards should not be seen as
synonymous (Cornforth, 2012; Renz, 2006).
We define nonprofit governance as the set of conditions that should be fulfilled and practices
that should be applied in order to enhance the achievement of a nonprofit organization’s mission
and vision (Brown & Iverson, 2004; Brown, 2005; Stone & Ostrower, 2007; Callen, Klein &
Tinkelman, 2010; Cornforth, 2012; Renz & Andersson, 2011, 2012). A board, its attributes, its
internal structure and what its members do, can thus been seen as conditions and practices
relevant to this definition, but are not the only elements that constitute nonprofit governance. In
other words, actors both inside and outside the boardroom, such as managers, staff and advisory
committees can contribute in various governance functions (Bradshaw, Murray & Wolpin, 1992;
Carpenter, Geletkanycz, & Sanders, 2004; Cornforth & Edwards 1999; Saidel & Harlan, 1998).
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With this definition, grounded in the nonprofit context, we deliberately leave the options open
on (1) the extent that governance is confined to the boundaries of a single organization and its
board, (2) the extent to which different types of stakeholders are involved, and (3) the multitude
of complementary and competing goals that might be comprised in a single organization’s
mission. We acknowledge that this remains a broad, though generalizable definition for the wide
range of nonprofit organizations, and that further refinement will be useful.
Therefore, we draw upon the extended concept of ‘nonprofit governance quality’, explained
and operationalized by Willems et al. (2012). Nonprofit governance quality adds to the definition
of nonprofit governance the varying extent– regarding sufficiency – with which several
conditions are met and practices applied in order to ensure the achievement of the organization’s
mission. As it deals with sufficiency to achieve a desired state, it has a strong normative
perspective. As a consequence, Willems et al. (2012) distinguish in their study five dimensions
that together formatively construct the overall concept of nonprofit governance quality: (a)
external stakeholder involvement, (b) consistent planning, (c) structures and procedures, (d)
continuous improvement, and (e) leadership team dynamics. It is the combination of these
dimensions that we investigate in relation to behavioral aspects of governance processes in order
to develop our theoretical propositions.
Leadership Coalitions: Two Dimensions
The coalition concept has been present in the organizational literature since the 1950s
(Thompson & McEwan, 1958) and, perhaps because of its intuitive appeal and feasibility, this
concept can be found in a variety of disciplines, including political science, social psychology,
strategic management and organizational behavior (Stevenson, Pearce & Porter, 1985). The roots
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of the organizational coalition construct go back to Cyert and March’s (1963) A Behavioral
Theory of the Firm.
We define a nonprofit leadership coalition as a system of individuals and the relationships
among them through which they influence each other in the processes of collective responsibility
and decision making. For this we build on governance-related research that is framed within
Cyert and March’s behavioral foundation and its emphasis on organizational coalitions (Pearce,
1995; Renz & Andersson, 2011, 2012; Stevenson & Radin, 2008; Van Ees et al., 2009), and we
include insights from the literature on power and influence in organizations (Cohen & Bradford,
1989; Krackhardt, 1990; Pettigrew & McNulty, 1995; Pfeffer, 1992),
However, an empirical inquiry of this perspective on governance quality requires further
conceptualization. To date there is no generally-accepted way to define organizational coalitions.
In fact, as noted by Stevenson et al. (1985 p. 261): “one of the most striking features of the
literature on organizational coalitions is the variety of meanings this term has come to assume”.
We therefore deconstruct the leadership coalition concept based on two dimensions derived from
literature; these guide this research on nonprofit governance.
The first dimension focuses on the distribution of governance power in an organization: Is
power concentrated within a small group, or perhaps even with one individual (centralized
influence), or spread over several groups or individuals (diffused influence)? This dimension
results from the imbalanced power distribution within groups of individuals that can emerge in
decision processes. The number of people involved in the decision processes, the complexity of
decision topics and the extent that personal agendas dominate decision taking can create
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differences among (groups of) people with respect to having more or less influence (Pearce, 1995;
Stevenson and Radin, 2008; Thompson, 1967).
The second dimension acknowledges that governance entails multiple decision areas (Brown
& Iverson, 2004; Renz, 2010) and focuses on whether an actor is influential in one or several of
these areas. Power bases can be very different since there are different forms of power and
influence (Cohen & Bradford 1989) and overall power is determined by the various decision
areas in which one can influence decisions (Krackhardt, 1990). As a result, individuals and/or
groups of individuals can range from being influential in a particular domain of governance, such
as budgeting (specific influence), to being influential in multiple or all decision domains (holistic
influence).
Introducing these two dimensions to study coalitions in the context of nonprofit governance
has two major advantages. First, as coalitions emerge due to different levels of individual
influence within an organization (Bradshaw et al., 1992; Saidel & Harlan, 1998; Stevenson et al.,
1985), coalitions can be studied from an organizational perspective in which overall coalition
characteristics are analyzed to compare organizations (e.g. Baysinger & Butler, 1985; Siciliano,
1996), or individuals within coalitions can be analyzed. Both dimensions allow behavioral
aspects of coalitions to be studied simultaneously on an organizational level and on an individual
level. Second, individuals within coalitions might be influential to different extents and for
different types of governance decisions (Cohen & Bradford, 1989). As a result, coalition
boundaries may be difficult to define (Stevenson et al., 1985). These two dimensions reflect on
the existence of a continuum, thereby allowing for a more graduated operationalization of the
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construct in which people can be ‘more’ or ‘less’ part of coalitions, in comparison to the binary
divide of being ‘in’ or ‘out’ of the board.
Research Method: Comparative Case Analysis
Given the exploratory nature of our research, we have chosen to employ a comparative case
approach. In particular, we were guided by the work of Fox-Wolfgramm (1997) (Dynamic-
Comparative Case Study Method), Eisenhardt and Graebner (2007) and Parker (2007a/b). In this
approach at least two organizations are contrasted with each other for a series of relevant
dimensions. Starting from observable differences between the cases, contingencies across various
conceptual dimensions can be explored and theorized (Eisenhardt & Graebner, 2007; Yin, 1993),
leading to the formulation of testable theoretical propositions (Fox-Wolfgramm, 1997).
We investigated five organizational cases, drawing on qualitative data including interviews,
observations at board meetings, website information, financial reports, bylaws and annual reports.
We also considered aggregated quantitative data (from online questionnaires). Data collection
happened over a timespan of about 14 months (first contacts around end 2010, till spring 2012,
when results were discussed with key informants from each organization). Inspired by the
concrete methodological steps described in Parker (2007b), the first author logged notes and
personal reflections through memo writing regarding various formal and informal interactions
with the five organizations. Repetitive reconsideration of notes and reflections in interaction with
the other authors led to the formulation of the concrete findings, and to framing them in the
theoretical context of leadership coalitions. Furthermore, data collection was complemented with
surveys of multiple individuals within each organization, in order to make interpretations less
dependent on single-observer biases. In order to improve external validity, a benchmark
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regarding coalition structures and related governance quality of the five organizations was
discussed with representatives of each organization.
We sought to go beyond choice of respondents based on formal roles within the organization
(e.g. only focusing on board members), so intensive initial interviews were implemented with
two key informants in each organization (often the CEO and the board chair, or people with
similar formal leadership positions), to identify the members of the leadership group. For the
purposes of this study, the leadership group is defined as the total group of individuals who are
(potentially), formally or informally, involved in the governance and strategic management
processes of the organization. In addition, it was assured that all board members, the CEO (or a
similar position in the organization), (other) members of a core executive team, advisors, and/or
additional committee members of each organization were included in the group of respondents.
Each of these respondents received an online questionnaire on (1) who they considered as
influential within the context of their organizations, and (2) the governance quality of the
organization. Among the list of people that were identified as being influential by these
respondents, no names were given that were not included in our original leadership groups, which
confirms the adequacy of the initial selection of leadership respondents. Up to three reminders
were sent, either by the researchers or by an internal key informant, in order to get a survey
answer from all people in the leadership groups of all five organizations. Hence, all identified
leaders also responded for the referral questions and for evaluating the organization with respect
to governance quality. Numbers and descriptive statistics are given in Table 1.
Once the survey data was collected from all leaders in each organization, an additional
meeting was held with several key informants (CEO and board chair, in combination with two or
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three extra leadership group members) and/or a presentation was given at an executive team or
board meeting. There, the aggregated results at the organizational level were discussed and
evaluated. These were benchmarked with the results of the four other organizations
(organizations received descriptions about the other organizations similar to Tables 1, 2 and 3).
These discussions ensured a more robust qualitative interpretation of the data obtained, helped in
adjusting external validity, and enabled the concrete formulation and refinement of potential
contingencies regarding dimensions of influence and governance quality (Flick, 2002; Fox-
Wolfgramm, 1997).
Table 1 presents selected core descriptive statistics and background information on each of
the five cases. We selected organizations with various missions and target groups, to enable our
theoretical interpretations to be more generalizable (Eisenhardt & Graebner, 2007, Yin, 1993).
Furthermore, this enables us to extract sufficiently clear similarities and differences, which helps
make relevant contingencies for theory development more apparent (Fox-Wolfgramm, 1997; Yin,
1993). However, the willingness of each organization to collaborate and to provide in-depth
information (by all relevant respondents) was also an important selection criterion. We have to
mention that Organization E has substantially more employees than the other organizations, and
therefore they have a substantially higher operational budget. This can be explained by the fact
that its target group is disabled people who, as a part of its mission and vision, are hired as
employees in production workshops in order to provide them the means and self-respect to build
an independent life. Therefore, given this difference, it makes sense for this organization to make
a distinction between operational workers (i.e. mainly beneficiaries of the organization, similar to
beneficiary groups of the other organizations) and strategic-managerial collaborators (similar to
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the employees of the other organizations). From annual reporting of this organization we could
deduct that it has about 30 of these strategic-managerial collaborators. Hence, it is slightly bigger
with respect to managerial-employee size than the other organizations (e.g. Organization B has
18 fulltime employees). From these 30 employees, the CEO and four department managers
(production workshops are grouped in four production departments) are part of the leadership
group identified for Organization E. This obvious difference was also openly discussed with the
representatives of the five organizations when discussing the benchmarking of the organizations,
and was taken into account for the formulation and verification of our interpretations.
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<Insert Table 1 about here>
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For each of these cases we classify and analyze several metrics derived from the survey data
with respect to (a) dimensions of influence in leadership coalitions, and (b) the (perceived)
quality of governance practices. Evaluating each organization for these concepts and measures
led to organizations being labeled as ‘low’, ‘medium’ or ‘high’ (see the next two sections). For
this we take a simple approach, inherent to comparative case analysis, where we rescale for each
measurement the lowest organizational score among the cases as the relative minimum (and thus
this organization is classified as ‘low’ for that indicator) and the highest as the relative maximum
(and thus the organizations is classified as ‘high’ for that indicator). The other organizations are
subsequently scaled within this range. When values are between the lowest value and 33% of this
range, they were classified as ‘low’, between 33% and 66% as ‘medium’, and above 66% as
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‘high’. We acknowledge that we have little information on how “high” or “low” certain metrics
are from an absolute perspective but, as comparative case analysis focuses on discovering
potential contingencies for theory development, this approach suits our aim (Eisenhardt &
Graebner, 2007).
Quantifying Dimensions of Leadership Coalitions
We derive the coalition metrics from three survey questions focusing on the notion of ‘being
influential’. Respondents could list, for three governance decision areas, the names of the people
that they considered influential: (1) ‘introduction of renewing governance and management
practices’, (2) ‘input for the mission, vision and strategy of the organization’ and (3) ‘introducing
important contacts with other organizations and institutions in the field’ (Cornforth, 2001, 2003;
Eeckloo, Van Herck, Van Hulle, & Vleugels., 2004; Gill, Flynn, & Raising, 2005; Pearce, 1995).
This data provides insight into the extent to which people are considered influential by other
individuals in the leadership group, and whether people are influential for distinct governance
functions. Figure 1 gives examples of how leaders referred to others with respect to being
influential.
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These questions are quantified in two independent ways, in line with the two relevant
dimensions identified in our literature section: (1) centralized versus diffused power, and (2)
holistic versus specific power. For the development of our quantifications we took the non-
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discrete character of coalitions into account and the fact that they are preferably applicable both
at the individual and organizational levels. This is consistent with the two advantages discussed
above with respect to quantifying coalition dimensions. We rely on metrics derived from social
network analysis (Hanneman & Riddle, 2005) because of their value for aggregated data when
comparing cases with different group sizes, and the possibility to derive metrics both at the
organizational and individual levels (Borgatti et al., 2002; Hanneman & Riddle, 2005).
For the quantification of centralized versus diffused power, we look at the distribution within
an organization of the referrals that people received across all three questions. A person’s in-
degree rating for a question is the number of times he/she is referred to by others (Hanneman &
Riddle, 2005). On the individual level, this can serve as indication of centralized versus diffused
power. Additionally, the skewness of the in-degree distribution per organization can be used to
assess the extent to which power is centralized (high skewness) or diffused (low skewness).
When skewness is high, this means that only one or a few people receive relatively many
referrals from others, while the majority receives relatively few or no referrals. Regardless of the
decision area for which referrals are made, this metric indicates the extent to which a single
person, or only a few people are considered strongly influential (centralized influence), or
whether many people share influence within the leadership group (diffused influence). Skewness
for in-degree distributions is calculated for all three referral questions (decision areas). Results
are given in Table 2. A combined comparative-case judgment is made to classify the
organizations based on these rankings.
To get insight in the dimension distinguishing holistic versus specific power, we look at the
extent to which the three referral questions correlate (which can be done both for individuals and
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for organizations). Again, this is done to be consistent with the advantages of both dimensions: (1)
applicable both to individuals and to coalitions as a whole; and (2) providing a continuous
quantification. When persons are considered by others being simultaneously influential in
different decision areas, they are deemed to have a more holistic influence in the leadership group.
In contrast, when individuals are only referred to for a single decision area, they have a more
specialized influence. At the organizational level, a high correlation between two referral
questions means that when individuals in that organization are referred to for one of the decision
areas, it is likely that they are also referred to for the other decision areas. For the quantification
at the organizational level, the overall correlations are calculated as the probability that a person
receives a referral from another person in one decision area when a referral already is made by
that person for another decision area (Borgatti et al., 2002; Hanneman & Riddle, 2005). The
magnitude of these correlations at the organizational level indicates the extent to which powers in
the three decision areas match with each other. All correlations are significant ( p < 0.05).
However, we observe differences across organizations. A high match at the organizational level
(high correlations) of these three questions indicates a holistic type of influence by the ones who
are influential. This means, regardless whether influence is centralized or diffused, that when
people are considered influential in one domain they likely are also influential in other domains.
In contrast, a low match (low correlations) indicates that people are identified as having a specific
influence for a specific governance function.
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<Insert Table 2 about here>
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Governance Quality
In order to assess the governance quality of each organization we rely on the nonprofit
governance quality index (Willems et al., 2012). This formative, second-order index probes for
the opinions of nonprofit leadership group members in five governance domains: (1) stakeholder
involvement, (2) consistent planning, (3) structures and procedures, (4) continuous improvement,
(5) and leadership team dynamics. This index is suitable for our analysis as it elicits opinions
within boards, but also from other leading persons in an organization. Furthermore, different
elements of governance are evaluated. In each dimension five or six indicators, assessed by 7-
point Likert scales, are used to probe for distinct elements of governance quality. Building on the
suggestions made by Willems et al., (2012), we look at the five dimensions separately before
combining them in a single governance quality metric. All identified leaders in each organization
completed the full index for their organization. This allows us to (1) compare mean scores for
perceived governance quality across organizations and the within-group variances for the
governance quality dimensions as an approximation for inter-rater agreement (Boyer & Verma,
2000; Klein & Kozlowski, 2000; Willems, 2015). Despite the fact that the literature does not
provide real cut-off values to judge high inter-rater agreement, and given the subjective nature of
nonprofit performance assessments (Green & Griesinger, 1996; Herman & Renz, 2000), we
believe this offers sufficient reliability for the aggregated results, since intra-class correlations
(ICC) for all five dimensions are above 0.25, and average rWG values exceed 0.7 (Boyer & Verma,
2000; Klein & Kozlowski, 2000).
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We are interested in the relative differences across the five organizations. As a result, the
lowest scores for each of the dimensions, both averages and agreement on the score, are
considered as the relative minimum (classified as low) and the highest as relative maximum
(high). Other organizations are classified within this range as explained above (low, medium or
high). Results are given in Table 3.
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Results and Discussion
In the next section ‘Classifying coalitions’ we consider the five cases according to the two
coalitional dimensions, based on the comparative-case classification (Figure 2). In the subsequent
section, ‘Coalitions and governance quality’ we describe the observed influence behaviors of
each coalition, based on our qualitative observations, and we include governance quality to the
classification and formulate theoretical propositions regarding the potential relatedness.
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Classifying Coalitions
Figure 2 gives a visual representation of the classification of the five cases based on the two
coalition dimensions investigated. First, a distinction can be made between organizations where
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influence in the leadership group is mainly holistic (Organizations A and D), and organizations
where influence in the leadership group is mainly specific (Organizations B and C). The
likeliness that people are referred to for one governance function when they are referred to for
another function ranges from 0.625 to 0.788 for Organization D and from 0.519 to 0.701 for
Organization A. We therefore classify them both as holistic influence. In contrast, for
Organization B they range from 0.358 to 0.593 and for Organization C from 0.373 to 0.529, for
which we classify them as specific influence (see Table 2). Organization E is less straightforward
to classify since a high correlation is found with respect to reported influence in the leadership
group for the governance functions ‘governance and strategic practices’ and ‘mission, vision and
strategy’, while a low correlation is found for these two dimensions with regard to ‘external
contacts’. As such, for Organization E two sub-coalitions can be observed: one focused on
internal governance functions (‘governance and strategic practices’ and ‘mission, vision and
strategy’), and one more focused on the external governance function (‘external contacts’).
A second distinction can be made between organizations typified by a leadership group where
influence is diffused among many individuals (Organizations A and B) and organizations where
one or few people are considered influential by many others (Organizations C and D). In cases
with more centralized influence skewness is in most cases close to 2.0 (except for ‘mission,
vision and strategy’ in Organization C where skewness is 1.04). Skewness is substantially lower
for Organizations A and B, with skewness scattered between -0.4 and 1.5. Again, E has to be
classified as a relatively ‘medium-level’ organization. For all three referral questions, skewness
values are within or close to the range of 33 and 66 percent of the range of observed case values.
This means that moderate situations regarding diffused versus centralized influence can be
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observed for each of the governance functions. In practice, for the two sub-coalitions observed in
Organization E, a balanced situation between centralized and diffused influence exists.
Furthermore, the additional observation can be made that across all cases skewness is smaller for
‘mission, vision and strategy’, potentially due to the fact that it is more an inherent function for
all people involved in leadership positions (McClusky, 2002; Solansky, Duchon, Plowman, &
Martínez, 2008).
Coalitions and Governance Quality
When combining the classification of both dimensions, we observe that Organizations A, B,
C and D are distinct from each other, while E can be classified as a combination of all four other
cases. To explore the distinctiveness of the cases, we discuss first the primary diagonal of the
framework (i.e. from bottom-left corner to top-right corner; see Figure 2), and compare B, E and
D. Subsequently, we discuss additional differences by comparing A and C.
Starting with the B-E-D diagonal in Figure 2 (i.e. the horizontal axis in left graph of Figure 3),
Organization B is typified by a situation where power is diffused among many people, with each
of them having their own ‘area of expertise and/or decision power’ (specific influence).
Furthermore, from the qualitative interviews and observations, we observed that people within
this organization were well aware of what the (claimed) expertise of each group member was,
and that, in order to avoid conflict, decisions and responsibility were regularly placed with those
members who were considered to be specialists in a particular area. In general, decisions in
specific areas were often left to the perceived and self-claimed specialists from the team, with
little in-depth discussions among individuals. As such, a weak or even non-existing coalition
could be observed in this organization. In contrast, Organization D is typified by a leadership
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group where a few people (centralized) were considered influential in multiple domains (holistic).
Within this organization a core team, including the chairman and two other board members, met
on an almost weekly basis and/or communicated on and regularly discussed strategic, tactical,
and even operational issues. Decisions at board or executive meetings were most often already
discussed and prepared upfront by this core team. Other leadership members acknowledged or
endorsed this strong dominant coalition within the organization and took a much more passive
role in decision making.
Organization E can be framed as a case in-between a weak or non-existing coalition (B)
and a strong dominant coalition (D). Compared to Organization B, some degree of central
leadership and a (partial) match of functions exist. However, compared to Organization D this is
not (too) strongly centralized among a few people, as power is distributed over two sub-coalitions
with several shared people in both these coalitions. As a result, depending on the decisions to be
made in this organization, differently-composed groups of people are indicated to be more
strongly involved and influential. As such, the observation was made that most people were
involved in some kind of decision making although, depending on the decision topic, certain
individuals might have been more or less involved. For that reason, the situation as observed in
Organization E could be referred to as a more balanced coalition.
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When it comes to governance practices, governance quality was reported to be high for
Organization E, as a balanced coalition between a weak or non-existing coalition (B) and a strong
dominant coalition (D). In addition, these extreme cases (B and D) received lower scores for the
five dimensions of the Governance Quality Index. For reasons of conciseness, we refer the reader
to Table 3 for the details and scores on distinct governance quality dimensions for each
organization. From the comparison of these three cases along the diagonal, we speculate that a
balanced situation is most favorable for obtaining overall high governance quality. In
Organization E, we see that sufficient input of various people was obtained for decision making
(robustness and broad acceptance of decisions). However, sufficient leadership agreement exists
to actively move forward with the organization. Also, in this context, it is very important to
mention the particular status of Organization E with respect to the larger number of strategic-
managerial collaborators (30, in comparison to the employee numbers in the other organizations,
ranging from 9 to 18) in combination to the much larger value of assets (see earlier description of
mission and vision of organization E). These are indications of a higher level of formalization
and/or professionalization, which we consider a third factor within the proposed relationship
between coalition characteristics and perceived governance quality.
With respect to the proposition on the potential relatedness of a balanced coalition with higher
governance quality (and levels of formalization), Cornforth (2003) makes a related claim, at least
for boards, that the composition and role should be balanced between extremes to avoid
governance crisis situations or low organizational effectiveness. Similarly, when looking at the
full leadership group, we could expect that (too strong) deviations from a balanced situation
could result in lower quality of governance practices. These findings can be considered in the
22
context of earlier empirical work on board faultlines (van Knippenberg, Dawson, West, &
Homan, 2011; Kaczmarek, Kimino, & Pye, 2012). Faultlines are informal dividing lines made by
team members, based on personal characteristics and that result in several more homogeneous
subgroups, which in turn have a negative impact on organization or team performance
(Kaczmarek et al., 2012). For organization D a clear faultline has emerged between a dominant
group of decision makers and a passive group of followers, while for organization B faultlines
seem to exist to such an extreme extent that various individuals are considered to be independent
decision makers. However, the faultlines also seem to be very weak as they do not result in
clearly distinct subgroups. When evolving to such a situation, like Organization B, where
multiple people are considered as ‘absolute rulers in their own domain’, little coordination and
mutual collaboration exist. Driven by avoiding personal conflicts with other leaders, rather than
being driven by the overall goal of the organization, such a situation can lead to substantial
governance malfunctions (Middleton, 1987). Accordingly, the lowest case scores for
Organization B are given for the governance quality dimensions ‘consistent planning’ and
‘continuous improvement’, showing the lack of a structured and sustainable collaboration within
the leadership group.
When an unbalanced situation exists with a small and highly dominant group of people, as
exemplified by Organization D, decision making might be based too much on the intuition of
these few people. As a result, transparency regarding decisions might be endangered
(Organization D has the lowest score on the governance quality dimension ‘structures and
procedures’); and the collaborative and informal dynamics among the full group of organizational
leaders might lack the associative and enhancing power for innovative decision making
23
(Organization D has the lowest score on ‘leadership team dynamics’). This supports the
theoretical proposition that clearly-emerged distinctions, or board faultlines, potentially can have
a negative impact on the collective decision making of a nonprofit board due to emotional
conflict, task conflict, and behavioral disintegration in leadership groups (Li & Hambrick, 2005).
When contrasting these preliminary findings regarding the diagonal (B-E-D) with the finding
of Gibson and Vermeulen (2003), the theoretical proposition that a more balanced situation is
appropriate for governance quality opens important avenues for further research. Gibson and
Vermeulen (2003, p 225) confirm the hypothesis that “the relationship between subgroup
strength and team learning behavior would be an inverted U-shape, such that moderate
subgroups would be associated with high learning behavior, while weak or very strong
subgroups would demonstrate low levels of learning behavior.” A similar relationship, between
strength of subgroups and learning behavior, is suggested based on our analysis regarding
subgroups and governance quality, with organization B being an example of weak subgroups and
organization D exemplifying strong subgroups (See Figure 3). However, van Knippenberg et al.
(2011) could not confirm this inverted U-shaped relationship for performance of profit businesses.
As such, this opens opportunities to investigate board learning behavior, as a sub-dimension of
nonprofit governance quality, related to ‘continuous improvement’ and ‘leadership team
dynamics’. Hence, building on the work of several academics who have theorized and tested the
relationship between nonprofit governance and performance (Bradshaw et al. 1992; Siciliano
1996; Brown,. 2005; Gill, Flynn & Raising, 2005; Callen, Klein & Tinkelman, 2010), a next step
could be to include coalitional dimensions as relevant antecedents and to dig deeper into this
relationship by including them as complex and non-linear intermediaries. In addition, this also
24
opens opportunities to further examinethe relatedness of the concepts ‘learning behavior’ and
‘nonprofit governance quality’.
In consideration of the cases not found on the primary diagonal, organizations A and C could
be considered as configurations where one dimension is compensating for the other (consider the
horizontal axis in right graph of Figure 3). For example, Organization C has a high degree of
centralization, although also high specific influence is observed. And, in organization C, five
people consider the chairman influential for all three referral questions. Furthermore, none of the
other people is considered influential in all three domains, but except for one they are all
considered by at least one other person to be influential in a single area. As a result, we judge that
the chairman is a holistic and highly centralized leader in a leadership group where specific
influences are distributed in several sub-coalitions. He can be considered as the head of a
hierarchical coalition, who oversees different sub-coalitions each specialized in more distinct
decision areas. This is in contrast to Organization B, with diffused and specific influence, as one
person takes a more central role, resulting in compensating centralized influence over
differentiated and specific functions in a weak coalition. It also varies from D, with centralized
and holistic power, as only one person has such centralized and holistic influences. From this
perspective, that person could compensate for the lack of coordination in an organization with a
weak or non-existing coalition (Organization B). In addition, the fact that multiple sub-coalitions
are coordinated in such a hierarchical way can compensate for the lack of broad involvement of
the full leadership group or for the existence of conflicts within a leadership group that has a
strong dominant coalition (Organization D) (Li & Hambrick, 2005). This compensation might
25
explain the medium quality of governance practices reported in Organization C, which is higher
when compared to B and D (see right graph in Figure 3).
Similarly, in Organization A the highly democratic decision process might compensate for the
weaknesses observed in cases such as organizations B and D. Organization A has a leadership
group with diffused and holistic influence. As a result, no explicit and distinct set of individuals
from the leadership group will be observed taking the lead in either one or multiple areas
(compared to Organization D). Thus, Organization A might lack strong leadership in cases where
an urgent decision has to be made, but decisions are more democratically legitimized. The
observed situation shows that most decisions are made with input of most leaders (‘many things
are decided by many people’), and therefore we could label this type of coalition a democratic
coalition. Consequently, the highest differences regarding governance quality dimensions
between both organizations exist for ‘structures and procedures’ and ‘leadership team dynamics’
(Organization A: High – Organization D: Low), showing that the democratic nature in
Organization B is both formally and informally stronger embedded. Compared to Organization B,
many leadership members in Organization A are considered influential in multiple domains.
Therefore, there is less a situation typified by unique specialization or individually claimed
decision areas. Similarly, the higher rating of formal structures and procedures in Organization A
support the judgment that this organization has a formalized higher democratic nature. In addition,
consistent planning is also substantially higher, perhaps due to the more in-depth and
collectively-considered subsequent steps after decisions have been made.
However, despite the fact that compensating mechanisms might preserve a medium or high
quality of governance practices (comparing A and C with B and D), one could argue that such a
26
situation is potentially unstable. If, for example, the chairman in Organization C were to
(suddenly) leave the organization, the compensating coordinating mechanism might be
endangered. In such a case, an organization might potentially switch to other quadrants in our
model, possibly resulting in the loss of governance quality. Similarly, if Organization A were to
be confronted with a situation where an urgent and important decision had to be made, the
democratic but time-consuming process that involves everyone might hamper a timely decision.
Therefore, our theoretical interpretations could be further examined by taking a longitudinal
approach to study how changes in coalitional dimensions result in changes regarding governance
quality.
Limitations and Future Research
While our study is exploratory, we have sought to answer the call of several seminal
contributions in the corporate and nonprofit governance literatures asserting that governance
should be explored and theorized for a context broader than only boards. We propose two
dimensions of power to scrutinize the impact of different types of leadership coalitions on
governance quality. Our comparative case analysis provides initial insights as a foundation for
the development of more concrete and testable propositions and hypotheses. Further exploration
is necessary for a more robust development of the preliminary insights of this work. We identify
at least three research paths that can be taken.
First, despite the fact that mainly case research and qualitative inquiry have been used to
explore coalitions in organizations (van Ees et al., 2009), our understanding of governance
quality of organizations, can be substantially enriched by following organizations and closely
observing them for a relative long period of time (e.g. based on ethnographic, participatory and/or
27
action research, and with recurrent interactions (Parker, 2007b)). In addition, important insights
on changes over time could be gained.
In our analysis we focus on five organizations, which offered a practical trade-off between
sufficient cases for a sound comparison and reasonable efforts and costs for a thorough
exploration of each case (Groves & Heeringa, 2006). When researchers decide to focus on
multiple cases for a longer period of time, it can become overly cumbersome to explore them in
sufficient depth because too many criteria might appear to be relevant (Parker, 2007b). For this
study, however, we acknowledge that our insights and interpretation are limited to static
contingencies, and more in-depth case analyses over a certain period of time could enrich and
complement the current analyses and interpretations.
Second, we endorse suggestions made by Hambrick (2007) that a semi-experimental setting
could enhance understanding of the relation between coalition characteristics and governance
quality. For example, test subjects could be put in various simulation-like situations that
approximate (extreme) situations. In this way, multiple scenarios can be explored, which allows
verification and fine-tuning of the propositions (Eisenhardt & Graebner, 2007; Huse, 2009). To
test propositions, situations could be imposed on test groups where access to information, formal
roles, or different leadership types would be differently designed across scenarios. Variations on
how decisions are made and what their outcomes are across test groups could be hypothesized
and tested.
Third, a more quantitative network approach could be taken to test some the initial findings of
our exploratory study. Networks among people in organizations that are at the basis of mutual
28
influence and decision making could be reconstructed. For example, critical incidents could be
probed for and the role of particular people in each event could be documented. As such, a rich
analysis could be performed on how relations between individuals constitute coalitions and how
they are employed as a basis for decision making. In this context we strongly suggest an
examination of variations that may exist at the organizational and individual levels. In this study,
we have taken a broader perspective than many other studies by focusing on the overall
leadership group rather than on the strict selection of board members. However, we did not
include many details on the specific characteristics, backgrounds, formal roles and other relevant
elements of each of them. These too may be important pieces of information that can help explain
the origins of the social dynamics underway. In particular, a more explicit focus on processes
outside the board may help test the relevance of the coalition concept in nonprofit governance.
Furthermore, decomposing the concept of coalitions in distinct dimensions may enable others to
test the assumptions at the core of our theoretical reasoning and research design, thus enhancing
the generalizability of fundamental relations regarding coalitions and governance practices.
Conclusions and Practical Implications
Building on our comparative case analysis at the organizational level we speculate that a
balanced coalition is likely to be important to obtain and maintain high governance quality, and
that the two coalition dimensions we have identified could compensate for each other with
respect to combined impact on nonprofit governance quality. From a theoretical perspective, our
analysis contributes to the literature in at least three ways. First, we answer the call that
governance could and should be studied from a perspective that is broader than the formal
boundaries of a board. For this we have built on coalition theory and we have translated this
29
approach in the formulation of two influence dimensions, which enabled us to undertake a more
quantifiable investigation of coalition types. Second, based on these two influence dimensions,
and fueled with the qualitative case material studied, we propose a preliminary classification of
various coalition types. Introducing such classification supports contrasts among different
situations, making it possible to extract potential contingencies and link with other relevant
concepts. In this paper, we have focused on governance quality and propose an inverse U-shaped
relationship with the influence dimensions. Third, we have described and applied a qualitative
empirical approach to use to develop these interpretations. This approach can be replicated and,
more importantly, complemented with other methods to further examine our findings and
interpretations and to expand on our insights with new relevant dimensions and concepts. We
acknowledge the hypothetical nature of our current interpretations, which is inherent to
qualitative exploratory studies, and we have proposed several pathways to further scrutinize our
findings.
Our practical recommendations focus on (1) being able to discover when an organization is
drifting to an ‘extreme’ or unstable coalition, such as for example a too strong dominant coalition,
and (2) subsequently being able to remedy the situation. For this, a strong sense of self-evaluation
is needed in nonprofit leadership groups, both at the group and individual levels. However, in
particular for nonprofit organizations, objective and decisive self-evaluations might be an almost
impossible challenge, given the inherent subjective nature of nonprofit performance (Herman and
Renz, 2000; Willems et al, 2014). In the context of profit organizations, shareholders and
customers have, as primary stakeholders, recurrent moments to express their trust in the
leadership of an organization: maintaining investments in the organization and (continue to) buy
30
products or services. This can give very objective and outside signals to the leadership of an
organization about the quality of their governance and management processes. However, it often
is the case in nonprofit organizations that their leaders have the responsibility to represent the
interests of the primary external stakeholders in the governance processes (Cornforth, 2003), and
outside signals might be lost or blurred when these leadership representatives are at the same time
at the core of the inside decision making. As a result, nonprofit organizations are in need of other
and additional mechanisms to assure that outside signals are captured when the decision
structures and processes drift away from what is most needed to address the particular needs and
preferences of a nonprofit’s primary stakeholders (e.g. beneficiaries, donors, etc.). Therefore,
various dedicated mechanisms could be given particular attention in the formal structures of
nonprofit organizations including, for example, the embedded and recognized role of
whistleblowers (inside and outside the organization), binding and recurrent third-party
evaluations of the leadership team (not only the board), broad and representative feedback from
various stakeholder types in the form of surveys, open-feedback platforms or general assembly
meetings (two-tier board structures).
31
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40
Table 1: Organizational descriptives
Descriptives /
Classification
Organization A
Organization B
Organization C
Organization D
Organization E
Mission /
Vision
Promoting overall
vegetable production
and consumption, to
reduce animal
production and
consumption. Events
and programs focus
on informing public
opinion on the
benefits (personal
health and
environment) of
eating less (or no)
meat, and more
vegetables.
Training people on
First Aid capabilities,
transporting ill and
injured people, and
provide voluntarily
First Aid support on
events, festivals,
concerts,
demonstrations, etc.
Non-formal, self-
education of children
and adolescents on the
environment (youth
movement), with a
strong focus on self-
organization and
collaboration. Several
events are organized
by youngsters in
which they set their
own goals and
collaborate on
maintaining and
protecting the
environment
Promote and educate
on socially
responsible arts from
different cultures,
through various
events organized by
member-volunteers
for other member-
volunteers and non-
members of the
organizations
Through workshop
and industrial
production providing
jobs to mentally and
physically disabled
people in order to
enhance their
independence in
society (improving
their social life, self-
esteem and self-
realization)
Main target
group(s)
(a) Whole society, (b)
mainly reached
through advocating
and supporting
'member-volunteers'
(a) Member-
volunteers (mainly
adults), (b) Society
(people in need for
first aid and transport
when ill or injured)
Youngsters
(a) Whole society, (b)
mainly reached
through advocating
and supporting
'member-volunteers'
Mentally and
physically disabled
people
Start
2000
1927
1970
2000
1969
Leadership
Team
(Respondents)
8
10
12
15
17
41
Board of
Directors
Board size: 6 (4
female, 2 male),
Age: mean: 39,7, min:
29, max: 52
Board size: 7 (7
male),
Age mean: 53,9, min:
40, max: 66
Board size: 10 (2
female, 8 male),
Age mean: 24,2, min:
22, max: 26
Board size: 8 (2
female, 6 male),
Age mean: 57,8, min:
42, max: 68
Board size: 12 (2
female, 10 male),
Age mean: 58, min:
39, max: 71
Non-board
members
1 CEO and 1 strategic
staff collaborator
(paid)
1 paid, executive staff
member and 2 board
advisors
2 paid executive staff
Committee of 3 (part-
time) executives, and
4 volunteers.
1 Director, with a
management team of
4 (one department
each)
Outside board
positions held
by leadership
group
In nonprofits: 0.33
In profit orgs.: 0.00
Nonprofit: 0.57
Profit: 0.14
Nonprofit: 0.40
Profit: 0.00
Nonprofit: 1.75
Profit: 0.25
Nonprofit: 2.25
Profit: 0.42
Personnel
11 (9 female, 2 male)
/ 7.7 FTE
18 (9 female, 9 male)
/ 15.4 FTE
9 (2 female, 7 male) /
6.4FTE
13 (9 female, 4 male)
/FTE 11.7
30 strategic-
managerial
collaborators. In total,
with beneficiaries
included:
666 (233 female, 433
male) / FTE 566
Volunteers
Large impact of
volunteers, various
regional chapters and
thematic groups
Large impact of
volunteers, various
regional chapters and
thematic groups
Large impact of
volunteers, various
regional chapters and
thematic groups
Limited number of
volunteers (relative to
personnel)
Limited number of
volunteers (relative to
personnel)
Total assets
€300k
€4,000k
€420k
€620k
€20,000k
Yearly budget /
Revenues
Yearly budget is
about €540k
(expenses: about 240k
personnel, 300k
operational costs)
//(Income: €200k long
Yearly budget is
about €2.800
Expenses: €730k
Personnel, €2070k
operational costs //
Income: which 2/3 is
Yearly budget is
about € 300k, with
about 250 personnel
expenses
Yearly budget is
about €620k (from
which 600 personnel
costs)
Commercial income
14.600k and donative
income is 8.350k,
Personnel expenses
are about 15.500k
42
term (5years)
subsidies, about 200k
membership fees and
donations, and about
140k commercial
income )
commercial income
and 1/3 donations,
membership fees and
subsidies
Donative/
Commercial
Mainly donative
Mainly commercial
Strongly donative
Strongly donative
Mainly commercial
Proportion of
personnel
expenses
Medium
Low
High
High
Medium-High
43
Table 2: Dominant Coalition Quantification: Aggregated reference measures.
Overall Network
Measures
Organization A
Organization B
Organization C
Organization D
Organization E
Correlations between
reference networks
Holistic influence
(High-medium)
Specific influence
(Medium-low)
Specific influence
(Low-medium)
Holistic influence
(High)
(Medium)
Corr(‘Outside
resources’*‘Mission,
vision, strategy’)
0.701
(80.40%) High
0.593
(56.23%) Medium
0.373
(7.03%) Low
0.788
(100.00%) High
0.342
(0.00%) Low
Corr(‘Practices’*‘Mission,
vision, strategy’)
0.697
(100.00%) High
0.481
(51.25%) Medium
0.253**
(0.00%) Low
0.671
(94.10%) High
0.684
(97.03%) High
Corr(‘Practices’*‘Outside
resources’)
0.519
(60.02%) Medium
0.358**
(0.00%) Low
0.529
(63.96%) Medium
0.625
(100.00%) High
0.417
(22.11%) Low
Skewness of in-degree
distributions
Diffused influence
(Low-medium)
Diffused influence
(Low-medium)
Centralized
influence
(High-medium)
Centralized
influence
(High)
(Medium)
In-degree(Mission, vision,
strategy)
-0.394
(0.00%) Low
0.188
(25.60%) Low
1.036
(62.84%) Medium
1.882
(100.00%) High
0.791
(52.07%) Medium
In-degree(Practices)
1.539
(44.26%) Medium
1.003
(0.00%) Low
2.214
(100.00%) High
1.907
(74.66%) High
1.835
(68.67%) High
In-degree(Outside
resources)
0.312
(0.00%) Low
1.345
(49.89%) Medium
2.382
(100.00%) High
2.022
(82.61%) High
1.526
(58.65%) Medium
44
Table 3: Classification of governance quality: mean scores and agreement within organizations (1- 7)
Governance Quality
Index
Organization A
Organization B
Organization C
Organization D
Organization E
Group Mean
Medium(-high)
Low
High(-medium)
Low
High
Stakeholder
Involvement
5.083
(51.99%) Medium
4.367
(0.00%) Low
5.056
(49.98%) Medium
4.556
(13.70%) Low
5.745
(100.00%) High
Consistent Planning
4.813
(68.02%) High
3.267
(0.00%) Low
5.042
(78.11%) High
4.244
(43.03%) Medium
5.539
(100.00%) High
Structures and
Procedures
4.944
(66.75%) High
4.167
(16.86%) Low
5.463
(100.00%) High
3.904
(0.00%) Low
5.118
(77.85%) High
Continuous
Improvement
4.708
(46.36%) Medium
4.083
(0.00%) Low
5.403
(97.88%) High
4.378
(21.84%) Low
5.431
(100.00%) High
Leadership Team
Dynamics
4.719
(81.03%) High
3.988
(36.38%) Medium
4.635
(75.94%) High
3.392
(0.00%) Low
5.029
(100.00%) High
45
Figure 1: Examples of reference networks from which coalition metrics are derived.
46
Figure 2: Visual representation of case classification based on coalition dimensions.
47
Figure 3: Abstracted representation of derived propositions.
