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THE UNIVERSITY AS AN ADAPTIVE
RESILIENT ORGANIZATION: A
COMPLEX SYSTEMS PERSPECTIVE
Ro
´mulo Pinheiro and Mitchell Young
ABSTRACT
This chapter provides an alternative conception of universities and the higher
education systems in which they operate in an attempt to comprehend the
ways in which such institutions and systems adapt and maintain themselves
over time. Conceptually, it builds on complex systems theory, most notably
critical insights from the study of complexity. We base our empirical analysis
on developments across the European continent in the light of recent efforts
to modernize university systems in the context of rising competition and pres-
sures toward vertical and horizontal differentiation. We contrast two models
of the university strategic versus resilient and critically reflect on the
implications their differences have for the development of systems and univer-
sities and future research work in the area.
Keywords: Resilience; complexity; systems theory; universities; adaptive
organizations; higher education
INTRODUCTION
There has been a tendency in the extant literature on university systems to
adopt reductionist (linear) perspectives whilst tackling the complexity inherent
to both institutions and the systems in which they are embedded. We argue that
this rather linear and rationalistic posture not only misrepresents what the
Theory and Method in Higher Education Research, Volume 3, 119136
Copyright r2017 by Emerald Publishing Limited
All rights of reproduction in any form reserved
ISSN: 2056-3752/doi:10.1108/S2056-375220170000003007
119
(c) Emerald Publishing Limited
university is all about as an entity/system, but, more importantly, has the
potential for destroying universities’ inbuilt capacity to respond to external
demands and circumstances, that is, to be resilient in the context of a rather
volatile external environment. In this chapter, we provide new insights on
approaching the university as a resilient organization by viewing it from the
perspective of a complex adaptive system.
Our primary aim is to provide an alternative conception of universities and
the higher education systems in which they operate in an attempt to comprehend
the ways in which such institutions and systems adapt and maintain themselves
over time. Conceptually, we build on complex systems theory, most notably
critical insights from the study of complexity (Byrne & Callaghan, 2014;Duit,
Galaz, Eckerberg, & Ebbesson, 2010;Morc¸ o
¨l, 2012;Room, 2011;Sawyer, 2005).
Complex systems literature takes as a starting point that systems are more than
the sum of their individual parts, and thus rejects reductionist approaches to
science. In so doing it moves away from a physics-inspired model of understand-
ing, and instead turns toward a biology-based one, that is, the laws of physics are
replaced with the dynamics of evolution (Room, 2016). Systems, biological or
otherwise, evolve because they adapt to emerging circumstances, gaining new
properties which either enhance or constrain their maintenance (survival) over
the long run. As a process, evolution “is a thick and tangled bush of branchings,
recombinations, transformations, and sequential path-dependent trajectories”
(Padgett & Powell, 2012, p. 2). Recently, this literature has been applied to social
scientific phenomena such as organizations and markets (Padgett & Powell,
2012), public policy and institutions (Morc¸ o
¨l, 2012;Room, 2011), sociology
(Sawyer, 2005), and governance systems (Teisman, van Buuren, & Gerrits, 2009),
but little has been done with it in the field of higher education. Complex systems
are nonlinear, dynamic and are characterized by many sub-entities and multiple
connections or linkages between them (Morc¸ o
¨l, 2012), and thus describe well the
university and its environment. We make a parallel between the university and
biological entities, like coral reefs, since both are multi-level systems, that is, both
are actors as well as function as arenas for other actors (Brunsson & Sahlin-
Andersson, 2000).
Empirically, we base our analysis on the European continent in the light of
recent efforts, at both national and supranational levels, to modernize university
systems in the context of rising competition and pressures toward vertical and
horizontal differentiation. Both internally (through management) and externally
(through policy pressures), the university is becoming more tightly coupled so as
to embody the role of a strategic actor that rationally creates and follows strategic
plans (Pinheiro & Stensaker, 2014). Very often this results in “unintended conse-
quences” or other empirical puzzles. In contradistinction, we present a model of
the university as an adaptive resilient actor, one which behaves more according
to biological models of evolution and niche-seeking than to Newtonian physics.
Complex systems theory thus provides an alternative way to answer the funda-
mental question of what a university is and how it evolves over time. In this
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chapter, we begin by demonstrating how those external pressures can be seen
from the perspective of complex systems theory, and how the latter can be used
to make better sense of the higher education system. Following that, we present
two stylized models of the university; strategic actor versus resilient actor.
Finally, we reflect on how a complex systems perspective can reframe current
thinking on universities and higher education systems in a way that allows it to
better address their varied and multiple missions.
COMPLEX THEORY FOR HIGHER EDUCATION
SYSTEMS
Over the past decade, complex systems theory has been making its way in to
the social sciences (Urry, 2005). While in general parlance complexity is often
used as a negative descriptor, that is, something which blocks our understand-
ings of how things work, complex systems theory attempts to reverse that and
provides a set of conceptual tools which allow sensemaking and analysis of phe-
nomena that are seemingly chaotic.
There is not a comprehensive theory of complex systems, rather there are a
broadly accepted set of interrelated concepts (developed in biology, chemistry,
physics, and information science) that are the building blocks upon which such a
theory may eventually rest (see Mitchell 2009 for a broad overview), but even as
isolated concepts they are powerful and revealing. Moving from the hard sciences
into social sciences requires translation, and this process is fraught with chal-
lenges (McLennan, 2006, pp. 139155), particularly the tendency to use these
concepts metaphorically, which can make them meaningfulness and invalid.
A system is thought to be “complex” when it cannot be fully described
through its individual components due to the nonlinear nature of the interac-
tions among them. Simple systems are composed of a few entities with a few
linkages or connections between these entities; complicated systems have more
entities and linkages but can still be explained in a linear model of causation. In
contrast, complex systems possess many sub-entities and multiple connections
or linkages between them that cannot be reduced to linear interactions; instead
they are dynamic and co-evolutionary, and show traits of emergence and self-
organization (cf. Padgett & Powell, 2012).
Understanding a system as complex also precludes several things. First, it
undermines the idea that policy is an intentional act by the government or the
university administration. Complexity means not only that there are multiple
actors with fragmented power to act, but also that intentionality is ambiguous.
Drawing on Luhmann (2012), we can argue that there is a horizontal configura-
tion between policy and higher education systems, which can communicate
with but not control each other (Young, Sørensen, Bloch, & Degn, 2016).
Second, it challenges the idea that reductionism and linearity can be used to
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analyze public or university policy. In other words, the outputs of the system
cannot be fully explained by the inputs, and the simplest solution is not neces-
sarily the best/truest solution. This is counterintuitive both to positivist science
and to a conventional view of governance.
Insights from the analysis of complex systems, like networks (Owen-Smith &
Powell, 2008), contend that an entity and/or entire system is complex because
of two critical characteristics. First, the considerable number of sub-systems it
entails within, and second, the synergies that occur as a result of the mutual
interactions among the system’s components. These elements, in turn, cast light
on: (a) the multifaceted nature of complex systems that are part and parcel of a
complex whole which is larger than the sum of its parts; and (b) that isolating
individual component the strategy used by scientific reductionism and the lin-
ear paradigm is problematic given the level of nested-ness that exists among
the various units, accounting for the observed outcomes.
Complexity arises in many aspects of the higher education system, but our
focus in this chapter is twofold. First, the internal complexity that is a result of
the multiple sub-entities; by which we mean the departments, research groups,
institutes, and faculties which have at least semi-autonomous positions within
the overall university structure. While these are all regulated by the university,
they are also subject to numerous outside institutions and actors, particularly
that of the academic profession, the discipline, and granting agencies and other
principals (Pinheiro, 2015). This autonomy and matrix of control influences
(Ashby, 1957) is the grounding for loose coupling. Second, the external com-
plexity of the competitive landscape created by economic and societal forces as
well as policy initiatives. Universities must determine not only how to position
themselves strategically within that landscape, but how to adjust to the constant
changes that are a result of other universities positioning and re-positioning
themselves (Fumasoli, Pinheiro, & Stensaker, 2015).
Following Morc¸ o
¨l (2012, p. 9), we define higher education as an emergent,
self-organizational, and dynamic complex system where the relations among
the actors or agents are characterized as nonlinear, with the relations among
system elements and with other systems being co-evolutionary. There are multi-
ple elements to unpack; here we only briefly summarize the key concepts (see
Mitchell, 2009; Morc¸ o
¨l, 2012;Room, 2011 for fuller treatments). To say that
something is emergent is to build on the idea that it is more than the sum of its
parts, but at the same time not randomly so. Complexity theory shows us that
emergent phenomena result from actions based on relatively simple rules, but
producing something that cannot be reverse engineered; that is, the parts can-
not be derived by deconstructing the whole. A classic example of this is the
behavior of birds flying in a “V” formation, which is formed without “manage-
ment” or “leadership” on the part of any of them. In more technical terms, we
can say that there are stable patterns on a macro level, as regards system
dynamics, that derive from micro level activities, but which are not explainable
with a simple (linear) causal model. Holland (1998, p. 7) writes that emergence
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“involves patterns of interaction that persist despite a continual turnover in the
constituents of the patterns.” The key here is that emergence is a pattern rather
than a one off event or phenomenon, and this in part explicates a link between
complex systems thinking and institutional theory (Padgett & Powell, 2012). It
points us toward an explanation as to how institutions can retain an identity
over generations of personnel turnover.
Room (2011) argues that institutionalism and complex systems theory are
complementary. Institutions, that is, sets of formal and informal rules that
determine the behavior of social agents (cf. March & Olsen, 1996), show emer-
gent properties. The structures and path dependencies observed by institution-
alists can be made dynamic when coupled with complex systems theory; that is,
the institutionalization which constrains individual actors (Mahoney & Thelen,
2010;Zucker, 1991) can, simultaneously, present new opportunities and enable
evolution, agency and the seeking of new niches (Room, 2011). This suggests
a possible response to the common critique that institutionalism, particularly
historical institutionalism, fails in its ability to explain change (Peters, 2012).
Further, it allows us to build on the significant work treating the university
as an institution that has traveled a remarkably similar path since its establish-
ment in the middle ages in Europe (Meyer & Schofer, 2007).
Several other concepts appear in the definition that we will treat briefly here.
Self-organization refers to the notion that systems have an internal capacity for
their own organization and continuation. This is at the heart of systems theory,
with seminal works by Luhmann (2012) which find their basis in biological
models of autopoiesis (Maturana & Varela, 1973), that is, self-reproducing and
maintaining systems, and those dealing with cybernetic theories like Ashby
(1957). The university system, particularly within the ideal type of a republic of
scholars (Olsen, 2007) has strong parallels to this model to the extent that it is
an autopoietic system (Young et al., 2016).
The second part of the definition brings in the concepts of non-linearity and
co-evolution. The former describes a situation in which there is a disproportion-
ality of effect. The term comes from mathematics, in which a rather simple
equation can produce something that looks entirely chaotic when plotted
on a graph (Morc¸ o
¨l, 2012, pp. 2832). This suggests that complexity is not
chaotic, but only appears so when viewed as an output. Again this challenges
reductionist approaches to social science, as tracing an effect backwards to its
cause becomes problematized. Finally, co-evolution builds on the concept of
evolution, which suggests that actors, and institutions, will evolve, undergo
selection and eventually thrive by finding niches in their environments.
Co-evolution recognizes that this is a dynamic process, meaning that as one actor
adapts, it enacts changes in the environment which will require subsequent
adaptations. In evolution, the selection environment is relatively fixed, but in
higher education this is not the case; a change of one variable (e.g., regulation)
leads to change in others (e.g., competition), and in that way to a reshaping of
the selection environment. Co-evolution captures this dynamic by claiming that
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the selection environment adjusts over time (Padgett & Powell, 2012): as one
actor or system changes, this creates a new selection environment in which the
other actors and systems must adapt and evolve so as not to face extinction.
Approaching higher education as an emerging, self-organizing, and evolving
system allows us to investigate the complexity inherent to the system as a whole
rather than investigating its constituent parts in isolation, as is often the case.
This also implies that, albeit certain parts of the system can be held together by
design (through policy), the broad dynamics of the system, including its evolu-
tionary path, are beyond control (Walker & Salt, 2006). At the micro level, this
phenomenon is similar to that of organized anarchies where no single actor is in
charge or has an overview of what is going on across the organization (Cohen,
March, & Olsen, 1972). By allowing the system to emerge and evolve rather than
trying to steer it into a given direction or predisposed outcome, self-adaptability
to new environmental dynamics is enhanced (Room, 2011). This, in turn,
increases the system’s ability to overcome or absorb major disturbances, resulting
in enhanced resilience, that is, “the ability of a system to absorb disturbance and
still retain its basic function and structure” (Walker & Salt, 2006,p.1).
THE QUEST FOR DIFFERENTIATION: THE UNIVERSITY
AS A STRATEGIC ACTOR
The conventional view of universities as organized anarchies (Birnbaum, 1988)
has recently been contested as a result of increasing formalization and rationali-
zation (Ramirez & Christensen, 2013), largely as a result of the rise of manageri-
alism in higher education (Berg & Pinheiro, 2016). Universities are, more than
ever, seen as accountable for their own actions and responsible for their destinies,
including the ability to operate efficiently in a competitive market place (Olsen,
2007). Universities face strong policy pressures for two types of differentiation:
vertical, which calls for stratification based on quality (i.e., excellence) and hori-
zontal, which calls for diversification of missions. For the most part, universities
have embraced vertical differentiation, through rankings, indicator-based man-
agement, scoreboards, and excellence initiatives (Huisman, Meek, & Wood,
2007;Pinheiro & Stensaker, 2014), but in large part have resisted horizontal dif-
ferentiation: “From the point of view of a system theory of functional differentia-
tion one can argue that the university as a modern institution can be
characterised by over-complexity and under-differentiation” (Enders & Boer,
2009, p. 174). Rather than leading to differentiation, universities have continually
added on new functions and units, resulting in what Kerr (1963) termed the “mul-
tiversity.” Why has one form of differentiation succeeded while the other seems
to have had more limited effects?
In Europe, excellence initiatives (Langfeldt et al., 2013) and the logic of
excellence embedded in EU programs such as Horizon 2020 (Young, 2015) are
rooted in the idea that it is better to have a few excellent universities and others
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that are less prestigious, rather than having a more even distribution of
quality. Particularly in Northern Europe (Germany, the Nordic countries, the
Netherlands), this is a radical change for a system that had previously been
highly egalitarian in both inputs and outputs (Geschwind & Pinheiro, 2017).
The vertical differentiation has largely been built on a common model or orga-
nizational archetype, namely the research-intensive university with an entrepre-
neurial bent (Pinheiro & Stensaker, 2014). The model is defined not on the
input side, but rather as the only means by which to meet the output character-
istics that allow an institution to be grouped with others that are considered
“world-class.” This model is driving both comprehensiveness of mission and
homogeneity. Though there are a limited number of institutions that could
meet these conditions, nevertheless, there is a broad trend of attempting to
compete for this status. An example of this can be seen in the recent trend to
amalgamate or merge existing institutions to enhance their fit with the arche-
type, and thus survivability in an increasingly competitive market place (Kyvik
& Stensaker, 2013;Pinheiro, Aarevaara, Berg, Geschwind, & Torjesen, 2017).
In this context, size (more so than variety) is seen as a precondition for market
success, despite the reverse often being the case in ecological systems, that is,
smaller but more diverse organisms tend to adapt faster, making them more
resilient (Walker & Salt, 2006).
The mission stretching that is part and parcel of being a more complete insti-
tution that addresses a multiplicity of societal demands also can be a threat.
According to Enders and Boer (2009, p. 166):
this also makes the university a rather vulnerable institution that tends to be overloaded with
multiple expectations and growing demands. The mission impossible of the modern univer-
sity is that it means too many things to too many and too diversified stakeholders. Overload
becomes endemic as growing and multiplying expectations seem to follow erratic public
“issue attention cycles.”
The strategic actor conception of the university rests, among other things, on
a particular model of competition and understanding of how the competitive
environment shapes an institution’s behavior. As institutions increasingly follow
a common archetype, competition is head on, that is, all institutions are compet-
ing with each other, not just those that belong to their particular type or niche.
This competition is supported and promoted by a neo-liberal policy trend across
Europe. While the aim of introducing competition is often benign, that is, pres-
suring institutions to improve themselves, the result is less so: some become win-
ners and others losers. This type of vertical differentiation is increasingly part of
policy objectives, but taken to the extreme, the model leads to organizational clo-
sures, or what Schumpeter (2012) termed “creative destruction.”
Ongoing structural changes in the internal fabric of universities, in large part
as a result of managerialism and mission stretch, tend to focus on improving
short-term efficiency or optimization at the expense of long-term adaptability
and, hence, resilience. This, in turn, has created a mismatch between fast-paced
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external dynamics and universities’ abilities to address them. This situation is
made more acute by the construction of a European-wide policy environment
substantiated in competition and quasi-markets (Maassen & Olsen, 2007) that,
instead of enhancing horizontal diversity, seems to be constraining it. From a com-
plex systems perspective, a less diverse higher education system (i.e., fewer forms or
types of institutions) may result in an overall decline in the system’s ability to
address unexpected events or external shocks, that is, a reduction in its overall levels
of resilience. A less resilient system or environment will, in turn, negatively affect
the institutions (their ability to adapt and evolve) that are tightly nested in it.
THE RESILIENT UNIVERSITY: KEY FEATURES
Resilient organizations and institutions tend to buffer themselves from environ-
mental constrains, such as external attempts for co-opting internal goals,
structures, and resources (Selznick, 1966). This, however, does not mean that
they do not change or adapt. To the contrary, it means that they are capable
of doing so while keeping their inner core (functions, proposes, identity, etc.)
intact. In this respect, resilience can be seen as the flexibility to adjust without
crossing thresholds of identity (Walker & Salt, 2006), that is the degree of
change that is possible before becoming something entirely different. In many
respects, the history of the university as an institution, going back to the medie-
val era, is an example of resilience in the face of enormous socio-economic,
political, and technological changes (Frank & Gabler, 2006;Rothblatt &
Wittrock, 1993). However, despite this, the university remains a unique and
recognizable type of institution. It has not been pushed beyond its thresholds.
That said, recent policy initiatives, both inside and outside the university,
pressure it to become more like a business and/or instrument of the government
for economic purposes. Both of these trends threaten to push it over a threshold,
one that would cause its demise as an institution, that is, an enduring collection
of rules and organized practices (Olsen, 2007), although not necessarily as an
organization, that is, a set of structures and activities aimed at accomplishing
pre-determined goals (for a discussion see Scott, 2008). Following earlier work by
institutionalists like Maassen and Olsen (2007) and Kru
¨cken (2003),among
others, our aim here is to identify key features of the university that allow it to
maintain resilience. The burgeoning literature on systems thinking and complex-
ity (Meadows & Wright, 2008;Morc¸ o
¨l, 2012;Room, 2011;Stroh, 2015;Walker
& Salt, 2006) sheds light on three critical features directly associated with
a system’s ability to foster resilience: slack,decoupling,andrequisite variety.
Slack
We conceive of slack as pertaining to repositories of redundant resources,
human or otherwise, at the disposal of organizational actors. In an attempt to
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enhance internal efficiency, managerial efforts to handle increasing environmen-
tal complexity are, more often than not, geared toward reducing rather than
embracing slack. Following systems theory:
Being efficient, in a narrow sense, leads to elimination of redundancies keeping only those
things that are directly and immediately beneficial …Though efficiency, per se, is not the
problem, when it is applied to only a narrow range of values and a particular set of interests
it sets the system on a trajectory that, due to its complex nature, leads inevitably to unwanted
outcomes …A drive for an efficient optimal state outcome has the effect of making the total
system more vulnerable to shocks and disturbances. (Walker & Salt, 2006, pp. 7, 9)
Thus, if slack depends on the existence of an internal repository of redundan-
cies, the reduction of the latter would imply an overall decline in slack within the
organization. Organizational scholars like Thompson (1967) conceive of slack as
a strategic resource in protecting organizations from environmental influences,
thus being associated with “buffering” mechanisms (Selznick, 1966). From an
evolutionary perspective, Bourgeois (1981, p. 30) contends that slack provides
“that cushion of actual or potential resources which allows an organization to
adapt successfully to internal pressures for adjustment or to external pressures
for change in policy as well as to initiate changes in strategy with respect to the
external environment.” Sharfman, Wolf, Chase, & Tansik (1988, p. 603) go one
step further in linking slack to efficiency while stating that there is an optimal
level of slack, with performance likely to decrease in situations where there is an
abundance of slack. From a functional perspective, slack refers to the fulfillment
of certain functions by a given sub-system(s) or functional group: “‘workers’ per-
form the same [internal] functions, but in different ways” (Walker & Salt, 2006,
p. 71). It is associated with resilience in the sense that it enhances the system’s
range of responses (variety) to external disturbances. For example, when
compared to Caribbean coral reefs, Australia’s great barrier reef has been found
to be more adaptable or resilient to emerging events like global warming since
it possesses a greater number of functional groups (species performing similar
functions in the ecosystem), which, in turn, helps enhancing its repertoire of
responses (ibid.,p.72).
From a system’s perspective, the literature refers to three critical factors in
the development of organizational slack: (a) exogenous conditions (e.g., compe-
tition or changes in regulations); (b) the endogenous characteristics of the
organization (e.g., size or age); and (c) the values and beliefs of influential inter-
nal actors or political coalitions (Sharfman et al., 1988). Earlier studies found
a direct relationship between slack, as a function of the extent to which
resources are allocated to either external (market) versus internal elements of
efficiency, and the degree of environmental response, with internal orientations
resulting in negative effects (Cheng & Kesner, 1997). Studies investigating the
interplay between organizational slack and risk-taking suggest that increases
in the former appear to be followed by more risky decisions (Moses, 1992).
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The same study also found evidence that slack is a multi-dimensional construct,
thus pertaining to more than simply resources.
Slack, either real or perceived, is often the reason for government and uni-
versity reforms that promote efficiency. When it comes to internal complexity,
in the realm of research there are ongoing attempts to centralize resources (peo-
ple and funding) across selected/fewer research groups in the quest for enabling
world class excellence (cf. Pinheiro & Stensaker, 2014). Similarly, in teaching,
managerialism and the rationalization that follows is resulting in a reduction of
study seats and/or programs that are considered to be too costly and inefficient,
as currently observed in Denmark. As for external complexity, in a number
of European countries recent governments have exerted profound changes in
the managerial structures of universities, by replacing elected with appointed
leaders (Pinheiro et al., 2017). Finally, current science policies across Europe
are increasingly geared toward a logic of “picking winners” as a means of
exploiting excellence, avoiding duplication, and leveraging the societal returns
on public investments (Sørensen, Bloch, & Young, 2016).
Requisite Variety
According to cybernetics, a stream of systems theory focusing on the study of
complex systems, requisite variety relates to the total number of states observed
in a given system (Ashby, 1968).
The law of requisite variety states that for every perturbation, there must exist an action to
counter it …The diversity of potential responses must be sufficient to handle the diversity
of disturbances. If disturbances become more diverse, then so must the possible responses.
If not, the system won’t hold together. (Page, 2011, pp.210211)
Diversity has been found to enhance the performance of complex systems
(Page, 2011). Going back to our earlier example of coral reef resilience, a key
factor why the Great Barrier Reef was found to be more resilient than the
Caribbean is that the former has more species of fish in all trophic functional
groups. These groups “play different and complementary roles in precondition-
ing reefs to permit the recovery of corals” (Walker & Salt, 2006, p. 71). In their
absence, the reef’s ecosystem would lose its ability “to absorb disturbance,
regenerate, and retain critical functions” (ibid.).
When applied to modern organizations operating in complex environments,
like universities, requisite variety postulates that the level of internal variety in
terms of structures, skills, knowledge, people, etc. needs to match the variety
present in the external environment if the organization is to survive and prosper.
This view is similar to the population ecology perspective on organizations, argu-
ing that only those organizations fit for survival in terms of matching or
addressing the environmental factors they face are likely to prosper in the long
run (Hannan & Freeman, 1989). The concept of “bounded rationality” (Simon,
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1991) plays an important role in this regard. Organizational actors (managers
and others) face cognitive limitations in comprehending the complexities inherent
to their internal and external and environments. Cameron (1984, p. 134) contends
that, given the limitations associated with adaptive (rational) strategies, the orga-
nizations themselves “will have to be designed so as to enhance their ability to
adapt, aside from the manager’s specific strategies.”
There are several examples of ongoing efforts, either purposive or uninten-
tional, that are reducing the internal diversity of universities as organizational
forms. From the perspective of internal complexity, there is evidence of a willing-
ness to close down departments that are considered weaker or which do not fit
universities’ strategic and competitive profiles (Hodges, 2006;Newman, 2009).
Similarly, with respect to external (system-wide) complexity, some governments
have allowed certain institutional forms to decline and gradually fade away.
Concrete examples include the university colleges in Norway, currently being
amalgamated as part of comprehensive universities, as well as private universities
in countries like Russia, Poland, and Portugal. Comparative scoreboards and the
use of indicators (including university rankings) serve rather to restrict the possi-
ble niches and through pre-planning prevent variety from emerging.
Decoupling
Universities have been characterized as loosely coupled entities where authority is
distributed and located downwards (Birnbaum, 1988;Clark, 1983), and thus
resemble organized anarchies (Cohen et al., 1972). This has created frustrations
for both government and managers within universities, and attempts have been
made of late to transform the university into a more complete organization, that
is, to rationalize internal processes and structures and centralize decision making
(Ramirez & Christensen, 2013). Structurally, one of the ways in which this has
been exercised is by increasing the degree of coupling from loose to tight
between higher level strategic goals (university/faculty level) and teaching and
research activities, on the one hand, and among teaching and research activities
both within and across faculties and departments, on the other (Pinheiro &
Stensaker, 2014). This increasing rationalization is expected to foster efficiency
gains and address external accountability concerns associated with the universi-
ties’ role in society and the economy (Butera, 2000). The policy environment rein-
forces this trend: European policymakers have recommended that modernization
“requires universities to overcome their fragmentation into faculties, depart-
ments, laboratories, and administrate units and to target their efforts collectively
on institutional priorities for research, teaching and services” (European
Commission, 2006,p.5).
Tighter coupling allows the university to behave as a “strategic actor,” that
is, one which through careful self-diagnosis can determine how to strategically
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maximize the opportunities and minimize the threats that its environment poses
(Kru
¨cken & Meier, 2006). For universities, that environment is both the real
social and economic environment as well as the constructed political environ-
ment, which for most public European institutions sets the conditions for fund-
ing and accreditation at a minimum. The ubiquity of strategic planning
activities in the university sector is emblematic of this strategic turn (Fumasoli
et al., 2015;Rip, 2004).
One of the key characteristics of complex adaptive systems is that they possess
independent yet interacting components (Walker & Salt, 2006, pp. 34, 35). In
adaptive emerging systems, sub-components are loosely connected to one
another, which enables them to respond or adapt differently to emerging circum-
stances. What is more, increasing interdependency within a complex system tends
to lead to a decline in the system’s overall levels of diversity (Page, 2011, pp. 138,
139), which, in turn, negatively affects its ability to adapt. Educational organiza-
tions, like schools and universities, have been characterized as loosely coupled
entities with little interaction between their parts or sub-units (Weick, 1976). In
the case of universities, this pertains both to vertical units, that is, the relation
between the central administration or “steering core” and faculties, as well as to
relations between the faculties and their subsequent sub-components: depart-
ments, research centers/groups, etc. Stated simply, what happens in the faculty of
education does not affect the faculty of engineering, and vice versa. This struc-
tural decoupling at the system level was best captured by work on academic lead-
ership around the concept of “organized anarchy” (Birnbaum, 1988;March &
Olsen, 1979). In recent years, there have been attempts to couple the internal
structures, strategies, and value-systems (cultures) within universities. This is part
and parcel of a process of rationalization aimed at enhancing control and predict-
ability (Ramirez, 2010), and results from external pressures for enhanced effi-
ciency, effectiveness, and accountability (Pinheiro & Stensaker, 2014).
As with slack, attempts to increase the efficiency of systems are inversely
related to loose coupling. From the strategic actor perspective, tighter coupling
is what enables the central core of the university to create and enact strategy
(Clark, 1998). It provides both the capabilities and the legitimacy necessary to
enforce change on the institution as a whole, allowing it to act as a single unit
pursuing collective aims. However, the multiplicity of missions (Enders & Boer,
2009; Kerr, 1963), as well as the bounded rationality of the central administra-
tion, means that the very definition of a collective aim must be a simplification
of this complexity, for example, moving up in global university rankings or
focusing on a particular mission or type of output.
Returning to the example of the coral reef, decoupling fosters both response
and functional diversity, that is, a redundancy of actors who perform similar
functions in a variety of ways as well as performing a diversity of functions,
which is found in the more resilient Great Barrier Reef but lacking in the
Caribbean reefs that are in danger. We suggest that these correspond to the uni-
versity sub-units, departments, and academics, and the emergence from them of
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distinct functional roles, and diverse responses to the needs of stakeholders and
society. Decoupling allows the internal autonomy and adaptability necessary
for units to explore and find their niches.
These three concepts of slack, requisite variety and decoupling, are central
to an understanding of the university as an evolving, self-regulated, and com-
plex system. Each, in its own way, addresses a particular type of diversity,
which serves to maintain the resilience of the university as a system. Table 1
sums up the key differences between strategic actor and resilient actor models
of the university.
CONCLUDING THOUGHTS
This chapter argues for an approach that conceives of both higher education
and the university as complex, emerging systems that self-organize and
co-evolve. In so doing, it critiques current policy and managerial approaches
throughout Europe focusing on rationalization and actor-hood substantiated
on strategic planning, linear thinking, and mitigating the complexities
associated with both internal dynamics and external forces. Current policy and
managerial approaches centered on promoting competition have resulted in
a gradual erosion of horizontal diversity while promoting vertical differentia-
tion. This, in turn, has resulted in enhanced short-term efficiency gains, among
other aspects, through the exploitation of existing internal assets and competen-
cies, in the form of resource concentrations and the tackling of redundancies.
This strategic posture is in stark contrast with the inner workings of complex,
evolving and self-organizing systems, which require flexibility (loose coupling),
slack, and (requisite) diversity as a means of fostering long-term adaptability
and hence the ability to overcome disruptions.
Table 1. The Models of University: Strategic Actor versus Resilient Actor.
Strategic Actor Resilient Actor
Strategic interface (internal
and external dynamics)
Reduce/manage complexity
(plan, steer, improve)
Cherish complexity (emergence, self-
organization, co-evolution)
Core value Efficiency Adaptability/robustness
Use of resources Maximize resources Allow slack
Approach to internal
diversity
Rationalize (streamline and
standardize)
Support requisite variety
Locus of control and unit
interdependencies
Tight coupling (hierarchy) Loose coupling (networks)
Preferred modus operandi Exploitation (specialization) Exploration (diversification)
Positional objective Winning (being the best
overall)
Thriving (adaption to niche and
excelling there)
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System resilience is, thus, best leveraged through the adoption of a posture
geared toward the continuous exploration of alternatives. In other words, to
foster resilience higher education systems and universities alike need to re-visit
a model akin to the “organized anarchy” identified in earlier historical periods.
This, in turn, necessitates the embracing of complexity, both internal and exter-
nal to the university, and unpredictability, yet it does not imply the institution-
alization of chaos. The reverse is the case. Emergence and self-organization are
better suited to handle a complex and unpredictable environment, minimizing
possible unintended outcomes such as a decline in horizontal diversity. A key
lesson of complex systems theory is not that we cannot make sense of the
world, but rather that looking backwards from effects to causes, as is conven-
tionally done in science, can be deeply problematic because of non-linearity.
The horizontal differentiation that policymakers (and academics alike) claim
is important, would require a more biological approach. It would entail provid-
ing universities with a greater degree of autonomy, both substantive (“what”)
and procedural (“how”) (Schmidtlein & Berdahl, 2005), but without the strong
meta-governance pressures pushing universities to conform to the competing
demands of multiple stakeholder groups. Rather it would require specialization
of an evolutionary type, by encouraging niche-finding (in contrast to conver-
gence or isomorphism), which it should be noted is the flip-side to competition.
Finding a niche is an evolutionary means of avoiding competition through spe-
cialization finding an area with less competition in which to thrive. Yet, as a
system, the university is deeply embedded or nested into a dynamic and com-
plex policy environment, thus one needs to pay close attention to the ways in
which this policy environment affects university dynamics and, in turn, the
ways in which resilience is either fostered or constrained.
Resilience, however, is the characteristic which allows adaptivity and is
therefore critical for enabling institutions to differentiate horizontally. In his
seminal article on new public management, Hood (1991) outlines an alternative
policy regime which would foster what he terms “robustness,” which corre-
sponds to the resilient actor model sketched out in Table 1. An organizational
design to maximize resilience encompasses:
multiple-objective …a relatively high degree of “slack” to provide spare capacity for learning
or deployment in crisis; a control framework which focused on input or process rather than
measured output in order to avoid building up pressures for misinformation; a personnel
management structure which promoted cohesion without punishing unorthodox ideas; a task
division structure organized for systemic thinking rather than narrow compartmentalization;
and a responsibility structure which made mistakes and errors admissible. Relatively loose
coupling and an emphasis on information as a collective asset within the organization would
be features of such a design structure. (p. 15)
Given the unprecedented pressures facing European universities, we contend
that the conditions for fostering resilient universities (and higher education sys-
tems for that matter) are not being met. Without resilience, universities could
be pushed over the thresholds that make them unique societal institutions,
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resulting in unpredictable consequences for themselves and society. It should be
made absolutely clear that our argument is not against change, but rather the
contention that change can go too far, and a recognition that we do not (yet)
know the precise thresholds at which that happens. A resilient university model
that takes into account the complexity associated with the university as an
institutional form, as well as the nonlinear ways in which its multiple sub-
components interact with its surrounding environment, both embraces change
and the maintenance of the unique institutional profile of the university. Future
studies building on seminal insights from complexity theory could illuminate
the extent through which universities as systems are co-evolving, in addition to
shedding light on the emergence of new organizational forms and the ways in
which these affect diversity at the system level. What is more, they could fur-
ther illuminate, empirically, the link (if any) between higher education and
science policy (at national and supranational levels), and the degree of resil-
ience at both the institutional and system levels.
ACKNOWLEDGMENT
A special thanks to the editors for insightful comments on an earlier version of
the paper, and to Sandra Hasanefendic. Any remaining errors are our own.
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