Table of Contents
From Ivory Towers to Learning Organizations:
the Role of System Dynamics in the
“Managerialization” of Academic Institutions
Federico Barnabé
Department of Social and Business Studies
University of Siena, Italy
Piazza San Francesco, n. 8, 53100 - Siena (Italy)
Fax. 0039-0577-232641
E-mail: barnabe@ unisi.it
ABSTRACT
Higher Education organisations face today strong pressure to adopt renewed
structures and management systems. Efficiency, efficacy and market principles have
become common words within the University and management practices and principles
are migrating to the academic context, boosting a process of “managerialization”.
However, preliminary results show that the new policies adopted by university
managements have led to counter-intuitive and undesired results, thus adding further
ambiguity to the understanding of the dynamics existing within the HE sector.
This paper explores the role that System Dynamics could play in the
“managerialization” of universities. System Dynamics tools could allow academic
decision makers to better keep under control the complex and dynamic university
environment: in these terms, the paper suggests the use of modeling and simulation
techniques in order to capture the complex and dynamic structure of the university
system and to explore the consequences of the policies and decisions that academic
managements are currently taking.
KEYworps: University management; System Dynamics; Managerialization;
Complexity; Quality; Organisational learning; Common understanding.
1, INTRODUCTION
Higher Education (HE) organisations face today strong pressure from institutional
environments to adopt renewed structures and management systems. The reasons for the
vast reform sweeping across European and non-European countries have to be found in
a substantial lack of efficient and effective academic educational and research
programmes and in a widespread financial crisis of the public sector. The global
scenario is even worse because, as in Italy, the number of students is decreasing due to
demographic reasons.
As a consequence, calls for a more effective and efficient management of the
resources destined to universities are continuously and increasingly heard. These calls,
however, do not come only from external parties to the institution but also from the very
inside of it, ie. from professors and researchers. Efficiency, efficacy, flexibility and,
more in general, market principles, have become quite common words within the
University; managerial techniques and competition policies are often discussed;
management practices and principles, once adopted only by the private sector, are
migrating to the academic context, boosting a so-called process of “managerialization” .
However, the effects of recent moves in this direction are ambiguous: preliminary
results of the new policies adopted by university managements led to counter-intuitive
and undesired results, thus adding further ambiguity to the understanding of the
dynamics existing within the HE sector. This situation seems to be particularly
problematic when facing performance-related evaluation processes, such as those
related to the assessment of teaching and research quality.
This said, it is author’s opinion that academic managements need to adopt powerful
information tools in order to keep under control the complex and dynamic university
environment.
Starting form the previous considerations this paper suggests the use of modeling and
simulation techniques in order to capture the complex and dynamic structure of the
university system and to explore the consequences of the policies and decisions that
academic managements are currently taking. In particular, this paper explores the role
that the System Dynamics methodology could play in the reforming process of
academic institutions. The aim is to highlight the potentialities that the System
Dynamics approach offer to academic decision-makers, helping them to better face
organisational changes.
In so doing, section Two will summarize the main features of the managerialization
process of the University, focusing on the fundamental dynamic and complex problems
it is possible to identify within the HE system. Section Two also takes into
consideration the main organisational and behavioural consequences that the
managerialization process could provoke on academic players.
Section Three will be focused on the System Dynamics methodology, exploring its
main scopes and tools. Section Four will present some final remarks.
2. THE “MANAGERIALIZATION” OF THE UNIVERSITY
2.1, Preliminary considerations
As the oldest institution in European societies the University has continuously
evolved during the last centuries, transforming and adapting itself in accordance with
the evolutions and the demands of its environment.
In the past three decades universities of European and non-European countries have
faced a series of massive organisational reforms. The entire mission and the core values
of these institutions have been consequently reshaped and have evolved according to
new demands and new requests coming from the whole of their stakeholders. In so
doing, the traditional modus operandi of universities has changed and the once adopted
humboldtian model of university has going disappearing.
In this regard, two main features have traditionally characterized the University:
a) in European countries universities have generally been state agencies, owned by the
State and run by the government;
b) academic freedom has always been considered as a priority by scholars and has
become an individual right over the last centuries.
However, the deep state of crisis in which universities have recently fallen has led to
the introduction of a massive process of reorganisation. This “legitimacy crisis”, as
Neumann and Guthrie refer to (2002, 722), has consequently led to “the promotion of
«new» management systems, typically characterized by the downsizing, re-engineering
and restructuring” of these institutions.
This “revolution” is consequently obliging academic institutions to introduce
considerable changes in their decision-making processes, implement renewed
information systems and new managerial methodologies and reshape their
organisational structures and the strategic relationships with their stakeholders.
This vast process of transition has been defined and labelled with many different
terms as: managerialization, corporatization, marketization, customerization,
modernization, commodification, rationalization, privatization, commercialization,
professionalization, accountingization'. Generally, if referred to the whole of public
administration, this process has been frequently defined as “new Public Management”.
As a consequence, there is a general tendency to reorganise and restructure modern
universities as entrepreneurial universities and there is a clear need for modem
managerial techniques. Among these, in particular, evaluation processes, the Total
Quality Management (TQM) approach, continuous improvement processes or, even, the
Balanced Scorecard’.
Frequently led by laws, the reform of the University is consequently leading to a
relevant change in the core values of these institutions. From the “ivory towers” they
used to be, namely élite institutions characterised by complete and undisputed
intellectual and behavioural autonomy, the universities are now Pecoming sort of
customer-oriented and revenue-seeking enterprises in many countries’,
Summarizing this situation, many scholars suggest and indicate that the role of
academic institutions is changing as a response to societal, educational and
governmental pressures.
This situation is impacting on many academic players and stakeholders, and should
be analysed referring to its main features, as follows.
2.2. Governance
Universities are evolving from the collegial institutions they were in the past.
As previously mentioned, the traditional humboldtian model is being abandoned and
universities are becoming entrepreneurial institutions. This implies there could happen
many relevant changes in the traditional model of governance and that the role of key-
players and the procedures governing the decision-making process within academic
organisations could sensibly evolve.
The collegial community that in the past was mainly interested in producing a free
and widespread product, i.e. knowledge, it is now driven by the necessity to reach high
levels of revenues, to collect funds coming both form the public and the private sector
and to enroll new students.
This situation is definitely shifting the focus of academics from the aims pursued in
the past to new goals to be reached. Deans have become top-managers, teachers are
" See K. Saravanamuthu, T. Tinker (2002, 548); G. Boyce (2002, 588); B. Czamiawska, K. Genell (2003,
456); J. Currie, L. Vidovich (2000, 135); anak t 002, 682-! ay, L.D. Parker (2002, 605-606); R.
Neumann, J. Guthrie (2002, 721).
? On these topics see C. Hood (1995); M. Barzelay (1999); L.R. Jones, J. Guthrie, Steane (2001a and
2001b).
3 On these issues see L.D. Parker (2002, 605); S. Lawrence, U. Sharma (2002, 661); K. Saravanamuthu,
T. Tinker (2002, 549); J.F. Dillard (2002, 626).
“ Many scholars refer to universities as “ivory towers’: among them, H. Etzkowitz, A. Webster, C.
Gebhardt, B.R. Cantisano Terra (2000, 313) and B. Czarniawska, K. Genell (2002, 457).
businessmen, internal bureaus and committees are based on managerial teams operating
on the market. The interrelationships among these actors consequently evolved,
becoming much more complex than in the past decades”.
This situation is particularly relevant since, within a university, a single person could
be involved by many different decisions and be himself the decision-makers at different
levels of the institution. For instance, a single person could be:
- ateacher within a Degree Programme;
- amember of the University Evaluation Committee;
- amember of the Committee of Department Chairmen;
- amember of some Governing University Boards, such as the Academic Board or
the University Administration Committee;
- etc.
This said, an academic system most of the times, such as in the Italian case, is
characterised by the following structure:
Ficure 1. - An example of HE system architecture.
Ministry
t \ :
University n. 1 | University n. 2 | | University n. ... |
| ]
¥ Y ¥ Y Y Y
[Feat “| Faculty “b” [Feat “a” || Faculty “b”) | Faculty “a Faculty “|
thy tae WN thy ra
The picture shows the hierarchical levels within the University system. It is evident
that a single person could be involved in the decisions taken at different and interrelated
levels, thus impacting on his own job and interests in many different ways.
It also seems evident that with many decision-making levels, the evaluation and the
planning processes have to set different goals and be properly “customized”. In
particular, these tasks will have to be carried out separately by the respective evaluation
and planning bodies.
As some scholars suggest, this could eventually oblige academics to face high levels
of complexity, dealing with issues impacting on their own job-roles at different levels of
the structure. They could be consequently unable to discern the real impacts of their
5 As R. Neumann, J. Guthrie underline (2002, 725), “in many traditional universities, the traditional
committee-based model was perceived as being forced out early in the creation of the UNS, replaced
instead by a hierarchical management model. This model is characterized by a significant increase in the
number of «professional» management appointees in the central and faculty/school bureaucracy. (...)
With the increase in «professional» appointments has come a concomitant increase in their decision-
making authority (...) [and] collegial modes of governance have been quickly replaced by stronger
managerial structures and practices, which contain a concentration of executive power’.
decisions, or could be stimulated to pursue some short-term goals instead of long-term
aims. Even more important, they could be not aware of the real feedback structure in
which they are embedded.
In this regard, L.D. Parker (2002, 615) recognizes that “university change will be a
continuously unfolding, non-linear, dynamic process full of unforeseen contingencies,
modified pathways and revised strategies. Significant, long-term changes to
organization interpretive schemes practices are almost inevitably complex, messy and at
times painful, unsettling and stressful to organization members. Empathy, sensitivity
and stamina are required of all parties”.
Even more important, this situation could lead to a dangerous long-term problem for
universities, because their short-term goals are nowadays those of acquiring new
customers and competing on the market of knowledge production; as G. Boyce argues
(2002, 590), “the economic rationalist agenda privatizes and commercializes higher
education to such an extent that the total concentration on responding to market trends
means the capacity for critical, long-term thinking is lost”.
It is author's opinion that simulation techniques could be very helpful within
universities, particularly if used at high, top-management levels. System Dynamics, for
instance, could usefully help key players to better understand their position in the
system of knowledge production, making clearer the consequences of the actions carried
out and the possible impacts of the decision taken on the different academic bodies and
sub-units.
In this regard, Kennedy (2000a and 2000b) refers to many System Dynamics
applications and publications on the University management issue, proposing an initial
taxonomy of System Dynamics models in Higher Education. The author classifies the
contributions taken into consideration, into six different areas of concern over five
hierarchical levels, as follows:
TABLE 1. - Areas of concem and hierarchical levels in the University system
Specific Area of Concern Hierarchical Level
a. Corporate Governance 1. National
b. Planning, Resourcing and Budgeting] 2. Regional
c. Teaching Quality 3. University
d. Teaching Practice 4. Faculty
e. Microworlds 5. School
f. Enrolment Demand
2.3. The steering method
The process of university managerialization could be realised following different
paths. Trow (1994), for example, has introduced the terms soft and hard in order to
describe two possible forms of managerialism and their related impacts on the academic
profession®:
soft managerialism seeks to provide higher education at the lowest cost and focuses
on improving the efficiency through which an institution fulfils its stated mission.
This approach mainly operates at an institutional level, where academic managers
try to adapt to their universities policies which have been defined at a national level.
© On these topics see P.L. Galbraith (1998a; 1998b; 1998c).
As a consequence this approach should not imply significant organisational and
operational changes in universities;
hard managerialism involves the re-shaping of higher education through the
introduction of new management approaches at national level that become
continuing forces in directing the future. This second approach establishes
performance indicators, criteria and rules by which outcomes of educational
activities are assessed and access to public funding is determined by consequent
“reward” and “punishment”.
It is still unclear which path will be followed in many countries. In some experiences
the hard approach seems to have been preferred to the soft approach. In any case, care
should be taken in choosing the proper form of managerialization, and in understanding
its related strengths and weaknesses. Lastly, full consideration should be given to
alternative options.
This said, within the HE sector the reform process could be sustained imposing a
regulatory approach or could follow a different way, adopting a so-called meta-
regulatory approach. Basically, the regulatory approach is a much more prescriptive
approach in nature. Scott (2003, 9) deals with both approaches by analysing the HE
systems in the U.K. and Australia. These countries have led the field in enacting
changes which other states have subsequently emulated.
a) In Scott’s view, any kind of state or institutional regulatory system that sets rigid
prescriptions for universities, produces the side-effect of not guiding the subjects’
behaviour towards the desired direction. It could also provoke a sense of reticence
and bring out misgivings about the new evaluation process. Scott also underlines
that a regulatory approach all too often places the emphasis on quantitative scientific
production over a qualitative one and rigid direct control over autonomy.
b) By contrast, a meta-regulatory strategy, used by state institutions or institutional
bodies, provides forms of indirect control instead of direct control. By giving the
participants within the system a certain degree of autonomy, indirect forms of
control could stimulate managerial skills and organisation, and guide participants
towards the achievement of regulatory objectives set for each department or sector.
The implementation of a meta-regulatory approach could be also less costly than
direct forms of control and more effective in guiding public sector behaviour
towards the achievement of pre-set goals.’ This solution is particularly effective in
university institutions that are traditionally viewed as loosely-coupled institutions
and are strongly characterised by their autonomy and capacity for self-organisation®.
It also provides the basis and stimuli to guide the participants of the evaluation
towards their objectives even if those objectives are set by institutions outside the
university.
2.4, The academic stakeholders
The number of academic stakeholders can be considered much more increased if
compared to the past. Briefly, the following groups can be considered as academic
stakeholders’:
a) the students and their families;
7 See C. Scott (2003, 9).
® See T. Reponen (1999).
° On these topics, see G. Singh (2002, 689); M. Kennedy, C. Clare (1999).
b)
c)
qd)
private and public firms and institutions;
the State and all the national and local governments;
the community.
Recent reforms, the lack of financial resources and the request of increased levels of
efficiency, efficacy and flexibility have deeply changed the once in use relationships
between the University and the above-mentioned groups.
a)
c)
The students and their families: the relationship between the teacher and the student
has considerably evolved towards a relationship between a business-man and a
client/customer. The position of the students in the knowledge production sector is
indeed a particular one: they can be both considered as an academic stakeholder and
as the final product of this process. As a consequence, they must be willing to invest
in education for themselves and must be aware of the best “products” (i.e. academic
courses) offered on the related market'”. The ultimate consequence of this situation
is that teachers could look at students in a different way, so boosting a massive
process of “commodification” of higher education policies, products and processes.
Private and public firms and institutions: universities and private firms are
nowadays called to an increased cooperation, towards an overall integration of
means and scopes. In so doing universities should promote a larger number of
research programmes and be finalized to the creation of applicable knowledge: for
instance, the ever-increasing number of University “spin-off” companies testifies
this situation.
The State and all the national and local governments: reforms across European and
non-European countries have been primarily promoted through the direct
intervention of national and local Governments. In so doing, they can be seen both
as immediate stakeholders of universities and as the main actors of the reform.
Indeed, once the welfare state has proved to be largely ineffective in several
European countries, national governments moved towards the adoption of market
principles, aimed at introducing increased levels of competition among universities
and, more in general, the whole of public administration. Accountability measures,
performance-related evaluation and benchmarking systems have been discussed,
tested and introduced in the academic sector. The role of local and national
governments is even more stressed when considering some relevant issues related to
the current situation of the HE sector in many countries. Consequently a clear
picture of the reform involving European universities should be obtained also
considering the following issues (V. Lynn Meek 2000, 25-26):
0 higher education has become a mass phenomenon with substantial costs that
need to be reduced: the financial burden of this mass education should be shifted
or it should be possible to realise more value per Euro committed in this sector;
0 there is a clear will in order to tie in a more closely way the higher education
sector and the national economy;
o becoming a mass phenomenon, higher education is becoming more a political
issue;
© in countries, such as Italy, due to an aging population the social service burden
on the national treasury is continuously and dramatically rising, obliging
As V.Lynn Meek (2000, 24 and 29) stresses, “the shift towards the «market» as a form of higher
education steering is underpinned by an ideological shift towards higher education as a private rather than
a public good. (...) Knowledge produced within such a context becomes a commodity. It can be bought
and sold. It is intellectual property, private intellectual property”.
national governments to cut expenditure and to demand higher levels of
efficiency from public sector institutions;
oO in most of the industrialised countries, traditional manufacturing industries are
being replaced by the so-called “knowledge processing sector’, of which higher
education is an integral component.
d) The community: the wider community is a relevant academic stakeholder and each
academic institution has some obligations in the areas of"!
© access to the facilities of the institution for the local community;
© contribution to the wider academic community;
0 providing services to the international community via the enrolment of overseas
students, collaborative research, consultancy and other projects;
0 the welfare of society in general.
2.5. The “culture of quality”
One of the main goals of the reforms across Europe is to promote a more efficient
academic system, characterised by high standards of teaching and research quality.
The “quality” of a product or of a service can be considered in broad terms as the
capacity of that object to efficiently and effectively satisfy some predefined
requirements. It also refers to the capacity to assure a high level of customer satisfaction
at competitive costs and/or market conditions. Furthermore, the concept of quality
assurance has a great importance for several reasons:
- firstly, it recalls the academics’ responsibility to define appropriate standards and
ensure that those standards are being met;
secondly, it implies that universities and professors have to offer good quality
education to their students;
thirdly, it makes academics and higher education institutions accountable.
Consequently, they have to safeguard the public interest in regards to standards of
higher education qualifications and to encourage continuous improvement in the
management of higher education quality.
These goals and tasks are achieved by setting and reviewing standards and quality,
and providing reference points that could help to define clearer and more explicit
overall standards.
In the academic world, the so-called “culture of quality” is continuously spreading,
often resulting in the adoption of managerial techniques and approaches once used
traditionally only by private sector firms. Among these techniques we could mention
methodologies such as the Total Quality Management (TQM), “continuous
improvement” processes or the Balanced Scorecard.
It is fundamental to stress that most of these methodologies adopt a systemic
approach to management and have the ultimate aim to promote long-term efficiency and
strategic thinking.
One methodology, in particular, seems to be worth of consideration within the HE
system: Total Quality Management”. This approach is based on the idea that each
activity that receives inputs from an external environment and transforms those inputs
UM, Kennedy, C. Clare (1999, 3)
"2 See G. Singh (2002); N. Aly, J. Akpovi (2001); G. Holmes, G. McElwee (1995).
into outputs for an external market, can be considered and studied as a process!’. The
“process approach” is specifically adopted and promoted by the ISO 9000 family. The
ISO 9000 family of international quality management standards and guidelines has
eamed a global reputation as the basis for establishing quality management systems".
Moreover, the TQM approach adopts the PDCA (Plan - Do - Check - Act) model, i.e. a
system-oriented and problem solving method. This method could be represented as
follows:
FIGURE 2. - The PCDA approach to management.
The four steps of the method constitute a systemic approach to decision-making and
management and consequently require a long-term focus and a strategic thinking.
In particular, the four stages require managers to:
a) Plan: define and analyse a problem and identify the root causes;
b) Do: devise a solution, develop a detailed action plan, implement it systematically;
c) Check: confirm the outcomes against the plan, identify side effects and issues;
d) Act: standardise the solution, review and reflect and begin to identify the next issue.
The cycle should then systematically repeat itself, being a feedback loop.
2.6. Evaluation and formula funding
Assessment of teaching and research performance has become a priority within the
HE system.
In many countries this situation has led to the introduction of assessment schemes
and many formula funding have been developed and tested. Schemes such as the
Research Assessment Exercise (RAE) are increasingly suggested as the “one best way”
in the academic sector in order to provide and assure higher levels of efficiency,
flexibility and quality.
Such schemes, however, could provoke side-effects which could had not been
correctly anticipated, producing several organisational and behavioural impacts on the
'S The underlying assumption of this approach is that a desired result can be achieved more efficiently
when activities and related resources are managed as a process. Furthermore, each process is linked to
some other processes and can be divided into sub-processes.
“™ The new ISO 9000: 2000 is based on 8 fundamental principles: a) customer focus; b) leadership; c)
involvement of people; d) process approach; e) system approach to management; f) continual
improvement; g) factual approach to decision making; h) mutually beneficial supplier relationships. All
the principles mentioned above can be applied with some variations to a variety of different fields.
academic players, both at an individual level (the single teacher/researcher) and at a
system level (a whole University). Among them, many scholars identify relevant
changes in the behavioural and on-the-job attitude of academics. For instance, through
the RAE research is basically measured and funded by government in terms of previous
research grants won, the number and rate of post-graduate student degree completions
and quantum of published output. This situation has led to an increased amount of
publications in response to the pressures upon academics and departments to increase
the amount of research funding awarded by government. It is not completely clear if an
increase in the amount of publications is followed by a high level of quality””.
The real risk of this situation is that the evaluation process will eventually lead to a
decrease both in quantitative productivity and in quality value of the publications
carried out, as shown in the following picture:
Ficure 3. - Effects of evaluation on quantity and quality of research (Source R. Brook 2000 and G.
Rebora 2003, 48).
Research
quantity
quality
Amount of evaluation
Many scholars have commented on this situation highlighting its main consequences.
For example, Davies and Thomas (2002, 181) point out that, at least in their country,
“as there are no clear rewards from teaching excellence, the instrumental academic is
encouraged to concentrate on the more visible and quantifiable aspects of academic
performance. (...) As there is no direct funding attached to teaching quality, it is
unlikely to have the same status as research. (...) [Furthermore] discussion about
research, it is suggested, is invariably restricted to just two questions: how much money
will it bring in, and how many publications will it generate?”.
If we consider the Australian case, Butler (2003, 154) explains that “increased
system-wide and institutional performance evaluation based on aggregate output
measures appears to be altering researchers’ publication habits” so boosting a sort of
“publication inflation”.
Briefly, academics will focus their main efforts on a “production-measurement
approach” (Singh 2002, 689), that is to say, on those tasks that are measured and
rewarded, while diminishing or ignoring a variety of other unmeasured activities such as
journal refereeing, textbook writing, conference organising and other collegial and
5M. Abbott, C. Doucouliagos (2003, 92) take into account this problem stating that “there is the issue of
the quality of the output. In the case of the Australian universities focusing on outputs (students
enrolled/graduating and research) without considering the quality of education provided might bias the
efficiency scores in favor of high output and low quality institutions (if they exist). A lack of quality-
adjusted data for output levels necessitates the abstraction from the issue of quality”.
10
social activities. In this regard, Willmott (1995, 1022) stresses that “as the pressures
upon academics mount, it is only to be expected that corners will be cut or, at least, that
academics will become less generous and diligent when «servicing» their «customers»”.
Furthermore, some scholars clearly proved the inconsistency of some formula
funding schemes. Some of them developed a System Dynamics model in order to take
into account all the effects we have just mentioned and to explore both the short-term
and the long-term effects of such policies.
Among them, for instance, P.L. Galbright identified several feedback loops in the
Australian University system. Basically, in order to increase productivity, Australian
universities instituted various incentive schemes in order to make individual units more
active. Such schemes allocate most of the teaching and research budgets on the basis of
research productivity.
Ficure 4. - Causal Loop Diagram on the Australian formula funding problem (Source: P.L. Galbraith
1998, 79).
+
Resource gains for
Unit A
Unit A's ne)
mee Total resources
available for
f° G distribution
Othe PE de Resource gain per _/
units ‘ units year “hs o&$ | individual product,
\ B's research
“oh
A gains for
Unit B
As shown above, Galbraith developed some CLD’s and a simulation model that
showed that in the long term the effects of such a scheme were irrelevant: indeed,
“whether or not there is an increase in productivity, no increase occurs in the funds
available for allocation. (...) Ironically, in the absence of funding growth, every
additional publication, every additional grant obtained, and every additional thesis
student graduated helps to ensure that less is obtained for that unit of effort than for the
previous one” (Galbraith 1998, 80-81).
Summarizing the previous considerations, this section of the paper stressed that
universities are characterised for being not only messy institutions, but also very tightly
coupled organisations. Within them it is easily possible to identify a plethora of
feedback loops that impact on each other: competition in areas such as student
enrolment and research productivity, efforts to contain debt by staff attrition,
competition between institutions for students, setting goals for enrolment levels,
distribution of economic resources on the basis of research activity, are all elements that
11
provide contexts for the manifestation of delayed feedback loops, escalation, sliding
goals and “tragedy” scenarios.
Due to the difficulties in managing complex environments the whole picture in terms
of developing interventions is tough to analyse: hence, the impact of various external
interventions and strategies adopted by institutions to manage and control factors is
tough to evaluate, and to observe the impact on the system as a whole is problematic.
Furthermore, we should consider that limited human cognitive processes prevents an
adequate comprehension of the dynamics occurring within a system. Bounded
rationality, misperception of feedbacks, simplified or wrong mental models, inability to
infer correctly the dynamics of all but the simplest causal maps, limited information, are
only some of the major limits the human decision-maker has to face continuously
(Sterman 2000, 26-27).
For these reasons System Dynamics tools could provide a useful and powerful aid in
dealing with complex issues and systems such as the academic one.
This issue will be better analysed in the following section.
3. THE SYSTEM DYNAMICS APPROACH
System Dynamics models and tools have proved their validity over more than 40
years of application in a variety of different fields.
Based on the concept of feedback and on information-feedback control theory,
System Dynamics can be considered as “a perspective and a set of conceptual tools that
enable us to understand the structure and dynamics of complex systems. System
Dynamics is also a rigorous modeling method that enables us to build formal computer
simulations of complex systems and use them to design more effective policies and
organizations. Together, these tools allow us to create management flight simulators -
microworlds where space and time can be compressed and slowed so we can experience
the long-term side effects of decisions, speed learning, develop our understanding of
complex systems, and design structures and strategies for greater success”'®,
To reach its goals and to support the decision-making process, System Dynamics
offers a number of different tools, both qualitative, as diagramming tools (causal loop
diagrams, stock and flow maps, etc.) and quantitative (formal models based on a
rigorous mathematical language) in order to identify, portray and analyse the critical
feedbacks determining the dynamics of the analysed systems!”.
This said, a model could assume several forms as “models can be viewed as maps
that capture and activate knowledge. They can be also viewed as frameworks that filter
and organize knowledge. Finally they can be viewed as microworlds for
experimentation, cooperation and learning” '°.
However, it is particularly relevant to highlight that the role of a System Dynamics
model and even, more important, of the whole modeling process is to gain insight on a
167. Sterman (2000, vii); see also J.W. Forrester (1961 and 1968) and J. Richardson, Pugh A. (1981).
The use of “microworlds” (S. Papert, 1980), also called “virtual worlds” (D. Schén, 1983), in
particular, seems to be an important tool in order to boost the knowledge of operators and managers.
'8 ].D.W. Morecroft (2000, 3).
12
complex problem, at the same time influencing thinking and actions in management
teams”.
In this regards, we have to stress that System Dynamics is to be preferred to other
planning and control/simulation techniques whether there is the need to face the
dynamic complexity of an issue.
Complexity generally arises because real (social and economic) systems are”:
dynamic, tightly coupled, governed by feedbacks, nonlinear, history-dependent, self-
organizing, adaptive, counterintuitive, policy resistant, characterized by trade-offs.
Thus, it is a natural consequence of management that intended aims of actions carried
out could not be reached or could provoke unanticipated effects. This is because real
system are characterised by the presence of feedback loops. Actually, all dynamics arise
from the interaction of just two types of feedback loops: positive (or reinforcing) loops
and negative (or balancing) loops.
A positive loop tends to reinforce or amplify whatever is happening in the system.
This feedback generates exponential growth as its dynamic behaviour: “the larger the
quantity, the greater its net increase, further augmenting the quantity and leading to
ever-faster growth” (Sterman 2000, 108).
A negative loop tends to counteract the tendencies within a system, opposing change
and seeking for balance, equilibrium and stasis. This feedback operates to bring the state
of the system in line with a goal or a desired state, counteracting any disturbance
moving the system away from its goal. It generates goal-seeking as its dynamic
behaviour, describing processes that tend to be self-limiting.
A variety of other dynamic behaviours arise from the nonlinear interaction of the
above mentioned structures with one another.
The analysis of real systems is even more complex because they are govemed by a
plethora of players continuously interacting. Furthermore, these decision-makers
generally base their decisions on their personal mental models of the real system
surrounding them.
Mental models are extremely relevant when facing complex systems, characterized
by a large number of feedback loops and by the presence of delays and nonlinearities.
The concept of “mental model” has been central to System Dynamics since its
beginning in the Sixties because each decision is based on models, usually mental
models.
“The term mental model means the conceptual model that each member of the
management team carries in his or her head to explain the way the business (or more
generally, the outside world) operates” (Morecroft 2000, 7). Furthermore, it “includes
our beliefs about the networks of causes and effects that describe how a system
operates, along with the boundary of the model (which variables are included and which
are excluded) and the time horizon we consider relevant” (Sterman 2000, 16)”.
Thus, the real goal of methodologies such as System Dynamics could be that of
expanding “the boundaries of our mental models so that we become aware of and
understand the implications of the feedbacks created by the decisions we make. That is
‘8 The gain of a better insight and not the development of a predictive model is one of the fundamental
aims of System Dynamics model. On this topic see J.W. Forrester (1961, 49).
20 See J.D. Sterman (2000, 22).
21 On the definition of mental model also see P.M. Senge (1992, 9); A.M.J. Vennix (1996, 21); C. Bianchi
(2001, 51).
13
we must learn about the structure and dynamics of the increasingly complex systems in
which we are embedded’.
Particularly used in the form of Group Model Building, System Dynamics is a
powerful tool that can be used in order to stimulate a process of organizational learning
and in order to elicit the existing knowledge of the most important actors: in this way,
knowledge can be obtained more quickly and for conditions not observable in real life.
In this regard, V ennix (1996, 3) underlines that “system dynamics can be used as a
method to systematically elicit and share mental models in teams. The process of
building a model starts from the different perceptions of the participants. One
underlining idea is that people’s mental models are limited by human information
processing capabilities. System dynamics can be helpful to elicit and integrate mental
models into a more holistic view of the problem and to explore the dynamics of this
holistic view” *,
This situation has led to a relevant change in the use that of System Dynamics and
modeling techniques has been made over the past few years. In the last decades
modeling and simulation have been generally seen as technical tools to be used to solve
and get a better understanding about structured problems of prediction, optimisation and
financial planning. On the contrary, more recently models have reached a different
consideration: they are seen as instruments to support strategic thinking, group
discussion and leaning in management teams”. This situation is particularly relevant
when the decision-makers have to deal with complex and persistent issues, whose
effects will be experienced in the long period.
All the above mentioned considerations seem to be particularly evident with regards
to the University management system.
On the topics presented in the previous table, we could also mention several System
Dynamics applications and publications. For instance”:
a) Governance: Kennedy and Clare (1999); Saeed (1996);
b) Planning, Resourcing and Formula Funding: Galbraith (1998a; 1998b); Kennedy
and Clare (1999); Bell, Cooper, Kennedy, Warwick (2000); Vahdatzad and
Mojtahedzadeh (2000);
c) Teaching and Research Assessment and Quality Assurance (TQM): Kennedy
(1998a, 1998b);
d) Microworlds: Barlas and Diker (1996); Barlas and Diker (2000);
e) Enrolment Demand: Frances, Van Alstyne, Ashton, Hochstettler (1994).
This said, taking into account the considerations we have previously mentioned, we
could propose the following table. It briefly presents the major issues that are currently
occurring within the HE system and highlights some System Dynamics tools that could
be used by academic players in order to better face complex and dynamic problems.
Of course, it is not a comprehensive summary of all the dynamic issues we could
identify within a University system; it is just a first proposal about the role that System
Dynamics could play in the HE sector.
” J.D, Sterman (2000, 12)
23 On the use of the Group Model Building technique see J.A.M. Vennix (1996); J.A.M. Vennix (1999);
JAM. Vennix, D.F. Andersen, G.P. Richardson, J. Rohrbaugh (2000).
4 See J.D.W. Morecroft (2000, 3); J.D.W. Morecroft, J.D. Sterman (2000); J.W. Forrester (1961, 49).
°5 Other contributions include the works by: N.H. Roberts (1978); K. Saeed (1990, 1997); C. Frances
(2000).
14
TABLE 2. - Dynamic issues and System Dynamics tools/goals in Higher Education.
Issue Reasons for the intervention System Dynamics tools Focus and Goal
of System Dynamics
Governance Complexity; Need fora Causal Loop Diagrams; Stock and | Strategic and long-term
system approach; Presence of | Flow Diagrams; Boundary charts; | thinking; Organisational
behavioural side-effects; Group Model Building sessions. _| learning; Gaining
Short and long term effects insight; Development of
of policies; Self-organizing a common understanding
sector, characterised by and of a holistic view;
trade-offs. Inter and intra-
organisational analysis.
Changes in Non-linear relationships; Causal Loop Diagrams; Stock and | Organisational learning;
Teaching and Presence of behavioural side- | Flow Diagrams; Dynamic Gaining insight;
Research Sub- effects; Short and long term | simulation models; Group Model _| Discovering side-effects;
systems effects of policies; Self- Building sessions; Microworlds. _| Strategic thinking.
organizing sector,
characterised by trade-offs.
Planning, Complexity; Presence of Dynamic simulation models; Exploring complexity;
Resourcing and | systemic archetypes; Non- Causal Loop Diagrams; Stock and | Scientific and long-term
Formula linear relationships; History | Flow Diagrams; Microworlds. thinking; Discovering
Funding dependent sub-system; side-effects;
Behavioural side-effects.
Stakeholders Need for a system approach; | Dynamic simulation models; Inter and intra-
relationships Complexity; Policy resistant | Causal Loop Diagrams; Stock and | organisational analysis;
system. Flow Diagrams. Strategic and long-term
thinking; Organisational
learning; Gaining
insight.
Evaluation and | Need fora system approach; | Dynamic simulation models; Scientific and strategic
quality Presence of behavioural side- | Causal Loop Diagrams; Stock and | thinking; Discovering
assurance effects; Complexity; Short Flow Diagrams; Microworlds. long-term impact of
and long term effects of policies; Identification of
policies behavioural side-effects;
Organisational leaning.
Enrolment Short and long term effects| Dynamic models; Causal Loop| Scientific and strategic
Demand of policies; Need for a|Diagrams; Stock and Flow] thinking; Discovering
system approach; presence of | Diagrams; Microworlds. long-term impact of
nonlinearities. policies; Gaining insight.
However, as it emerges form the literature review we have previously presented,
many other scholars are stressing and underlining many dynamic and complex issues of
the current HE scenario that would require the use of System Dynamics tools or other
simulation techniques.
It is author's opinion that System Dynamics and System Thinking will progressively
acquire a major role within the managerialization process of modern Universities and
within a new re-shaped HE system.
4, FINAL REMARKS
This paper dealt with the managerialization process which is occurring in many
European and non-European universities and with its organisational and behavioural
consequences. Indeed, the overall process is impacting on many sub-systems and
15
organisational variables of universities, consequently requiring several changes and
adjustments.
Taking into consideration a review of the latest literature, we have highlighted the
main strengths and weaknesses that many scholars have reported about the reform of the
higher education system.
We have also argued that this massive reform is implying a change in the traditional
modus operandi and core values of universities, now becoming sort of customer-
oriented and revenue seeking enterprises.
This situation is significantly impacting on the decision-making process within
universities, requiring academic players to adopt a long-term oriented approach to
management and a strategic thinking about situations characterised by complex and
dynamic issues.
We have consequently assessed that the transition to renewed managerial and
organisational structures requires the adoption of methodologies and techniques once
only used in the private sector.
It is author’s opinion that simulation tools and techniques could provide a fruitful
help to decision-makers. In particular, we have suggested the adoption of the System
Dynamics methodology.
As previously mentioned, the System Dynamics approach is based on the concept of
feedback and on information-feedback control theory and offers a comprehensive set of
tools that enables decision-makers to understand the structure and dynamics of complex
systems characterised by soft and hard variables and by nonlinearities.
In this regard, even the use of simple System Dynamics tools as a Causal Loop
Diagram or a Stock and Flow diagram could provide useful information on the system
in which academic players are embedded and let them gain deep insight on the long-
term consequences of the actions carried out.
As stated, this approach could eventually facilitate a process of organizational
learning, a positive change in the mental models of the relevant actors, the creation of a
common understanding about systems characterized by the presence of feedbacks and
complexity and an overall better management of the available resources.
This could be the path modem universities ought to follow in order to finally become
“leaming organisations” and to adopt a strategic, pro-active, long-term thinking.
16
REFERENCES
ABBOTT M., DoucouLiacos C. (2003), The efficiency of Australian universities: a data development
analysis. Economics of Education Review 22: 89-97.
ALY N., AKpovI J. (2001), Total quality management in California public higher education. Quality
Assurance in Education Vol. 9, No. 3: 127-131.
BARLAS Y., DIKER G.V. (1996), Decision Support for Strategic University Management: A Dynamic
Interactive Game. In Proceedings of the 14th System Dynamics Conference, Boston, USA.
BARLAS Y., DIKER G.V. (2000), A dynamic simulation game for strategic university management.
Simulations and Games, Sage Publications Inc.
BARZELAY M. (1999), How To Argue About The New Public Management. International Public
Management Journal 2(2): 183-216.
BELL G., COOPER M., KENNEDY M., WARWICK J. (2000), The development of the Holon Planning and
Costing Framework for Higher Education Management. In Proceedings of the 18th System Dynamics
Conference, Bergen, Norway.
BIANCHI C. (2001), Processi di apprendimento nel governo dello sviluppo della piccola impresa. Una
prospettiva basata sull’integrazione tra modelli contabili e di system dynamics attraverso i
micromondi. Giuffré, Milano.
Boyce G. (2002), Now and then: revolutions in Higher leaming. Critical Perspective on Accounting,
13(5-6): 575-601.
BROOK R. (2000), The Evaluation of Research: the Benefit. The Risk and Some Simple Rules. In “Atti
del Convegno: La valutazione della ricerca. CIVR, Roma.
BUTLER L. (2003), Explaining Australia’s increased share of ISI publications - the effect of a funding
formula based on publication counts. Research Policy 32: 143-155.
CuRRIE J., VIDOVICH L. (2000), Privatization and competition policies for Australian universities.
International Journal of Educational Development 20: 135-151.
CZARNIAWSKA B., GENELL K. (2002), Gone shopping? Universities on their way to the market.
Scandinavian J ournal of Management 18: 455-474.
Davies A., THOMAS R. (2002), Managerialism and Accountability in Higher Education: the Gendered
Nature of Restructuring and the Costs to Academic Service. Critical Perspective on Accounting 13(2):
179-193.
DILLARD J.F. (2002), Dialectical possibilities of thwarted responsibilities. Critical Perspective on
Accounting 13(5-6): 621-641.
ETZKOWITZ H., WEBSTER A., GEBHARDT C., CANTISANO TERRA B.R. (2000), The future of the university
and the university of the future: evolution of the ivory tower to entrepreneurial paradigm. Research
Policy 29: 313-330.
FORRESTER W. J. (1961), Industrial Dynamics. The M.I.T. Press, Cambridge, Massachussets.
FORRESTER J.W. (1968), Principle of Systems. The M.I.T. Press, Cambridge, Massachusetts.
FRANCES C. (2000), Using System Dynamics as a Tool for Decision Making in Higher Education
Management - U.S. Experience. In KENNEDY M. (2000), Selected papers presented at an
international seminar on “Using System Dynamics as a Tool for Decision Making in Higher
Education Management. ed., held in June 1999 at the Royal Society, London and South Bank
University, London, UK.
FRANCES C., VAN ALSTYNE M., ASHTON A., HOCHSTETTLER T. (1994), Using System Dynamics
Technology to Improve Planning and Budgeting for Higher Education: Results in Arizona and
Houston, Texas. In Proceedings of the 12th System Dynamics, Stirling, Scotland.
GALBRAITH P.L. (1998a), System Dynamics and university management. System Dynamics Review 14(1):
69-84.
GALBRAITH P.L. (1998b), When strategic plans are not enough: challenges in University management.
System Dynamics. An International J ournal of Policy Modelling Vol. X, Nos. 1 & 2: 55-84.
GALBRAITH P.L. (1998c), Are Universities Leaming Organisations? In MOHAPATRA P.K J. (1998),
System Thinking in Management, ed., Department of Industrial Engineering and Management,
Kharagpur: 70-87.
HoiMes G., McELWEE G. (1995), Total quality management in higher education: how to approach
human resource management. The TQM Magazine 7(6): 5-10.
Hoop C. (1995), The ‘New Public Management’ in the 1980's: Variations on a theme. Accounting
Organizations and Society 20(2/3): 93-109.
17
Jones L.R., GUTHRIE J., STEANE P. (2001a), Learning From International Public Management Reform.
Elsevier Science Inc., New Y ork.
Jones L.R., GUTHRIE J., STEANE P. (2001b), New Public Management: Learning From International
Public Management Reform. Eds., Vol. 2, Elsevier Science Inc., New Y ork.
KENNEDY M. (1998a), Some issues in System Dynamics Model Building to Support Quality Monitoring
in Higher Education. In Proceedings of the 16th System Dynamics Conference, Quebec City, Canada.
KENNEDY M. (1998b), A Pilot System Dynamics Model to Capture and Monitor Quality Issues in Higher
Education Institutions. Experiences Gained. In Proceedings of the 16th System Dynamics Conference,
Quebec City, Canada.
KENNEDY M. (2000a), Towards a taxonomy of System Dynamics Models of Higher Education. In
Proceedings of the 18th System Dynamics Conference, Bergen, Norway.
KENNEDY M. (2000b), An extended taxonomy of System Dynamics Models of Higher Education. In
Proceedings of the 18th System Dynamics Conference, Bergen, Norway.
KENNEDY M., CLARE C. (1999), Some issues in building System Dynamics Model for improving the
Resource Management Process in Higher Education. In Proceedings of the 17th System Dynamics
Conference, Wellington, New Zeland.
LAWRENCE S., SHARMA U. (2002), Commodification of education and academic labour - using the
balanced scorecard in a university setting. Critical Perspective on Accounting 13(5-6): 661-677.
LYNN MEEK V. (2000), Diversity and marketisation of higher education: incompatible concepts?. Higher
Education Policy 13: 23-39.
MorecrorT J. D. W. (2000), Executive Knowledge, Models, and Learning. In Morecrort J. D. W.,
STERMAN J. D., Modeling for Learning Organizations. 1* Paperback edition, from Productivity Press,
Portland, Oregon, 1994.
MorecrorT J. D. W., STERMAN J. D. (2000), Modeling for Learning Organizations. 1* Paperback
edition, from Productivity Press, Portland, Oregon, 1994.
NEUMANN R., GUTHRIE J. (2002), The corporatization of research in Australian Higher Education.
Critical Perspective on Accounting 13(5-6): 721-741.
PAPERT S. (1980), Mindstorms. Basic Books, New Y ork.
PARKER L.D. (2002), It’s been a pleasure doing business with you: a strategic analysis and critique of
university change management. Critical Perspective on Accounting 13(5-6): 603-619.
REBORA G. (2003), Gli obiettivi della valutazione: miglioramento della qualita, trasparenza delle
informazioni, efficienza ed efficacia dei processi. In CRUI (2003), La valutazione: un indispensabile
strumento di garanzia e di governance, Roma: 25-71.
REPONEN T. (1999), Is leadership possible at loosely coupled organizations such as universities? Higher
Education Policy 12: 237-244.
RICHARDSON G., PuGH A. (1981), Introduction to system dynamics modeling with Dynamo. Pegasus
Communications, Walthan, MA.
Roberts N.H. (1978), System Simulation of Student Performance in the Elementary Classroom. In
Roserts E.B. (1978), Managerial Applications of System Dynamics. Ed., Pegasus, Waltham,
Massachusetts: 597-615.
SAEED K. (1990), Bringing Practicum to Learning: a System Dynamics Modelling Approach. Higher
Education Policy Vol. 3, No. 2.
SAEED K. (1996), The Dynamics of Collegial Systems in the Developing Countries. Higher Education
Policy Vol. 9, No. 2: 75-86.
SAEED K. (1997), System Dynamics as a Technology for New Liberal Education. Worcester Polytechnic
Institute Report No. 3, Worcester, Mass. USA.
SARAVANAMUTHU K., TINKER T. (2002), The University in the new corporate world. Critical Perspective
on Accounting 13(5-6): 545-554.
ScHON D. (1983), The Reflective Practitioner. Basic Books, New Y ork.
Scort C. (2003), Controlling the Campus. Risk& Regulation Spring: 9.
SENGE P.M. (1992), La quinta disciplina. L'arte e la pratica dell’ apprendimento organizzativo. Sperling
& Kupfer Editori (The Fifth Discipline. The Art and Practice of the Learning Organization.
Doubleday-Currency, New Y ork, 1990).
SINGH G. (2002), Educational consumers or educational partners: a critical theory analysis. Critical
Perspective on Accounting 13(5-6): 681-700.
STERMAN J. D. (2000), Business Dynamics. Systems Thinking and Modeling for a Complex World. Irwin
McGraw-Hill.
18
Trow M. (1994), Managerialism and the Academic Profession: the Case of England. Higher Education
Policy 7(2): 11-18.
VAHDATZAD M., MOJTAHEDZADEH M. (2000), Some issues in the strategic management in a fast growing
academic Institution: the case of University of Yadz. In Proceedings of the 18th System Dynamics
Conference, Bergen, Norway.
VENNIX A.M,J. (1996), Group Model Building. Facilitating Team Learning Using System Dynamics.
John Wiley & Sons, Chichester.
VENNIX A.M J. (1999), Group model-building: tackling messy problems. System Dynamics Review 15(4):
379-401.
VENNIX A.M,J., ANDERSEN D.F., RICHARDSON G.P., ROHRBAUGH J. (2000), Model Building for Group
Decision Support: Issues and Altematives in Knowledge Elicitation. In MorecrorT J.D.W.,
STERMAN J.D. (2000), Modeling for Learning Organizations. 1“ Paperback edition, from Productivity
Press, Portland.
WILLMOTT H. (1995), Managing the Academics: Commodification and Control in the Development of
University Education in the U.K.. Human Relations 48(9): 993-1027.
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