1

This is a preprint of an article whose final and definitive form has been published in the STUDIES IN HIGHER EDUCATION © [2010] Society for Research into Higher Education; STUDIES IN HIGHER EDUCATION is available online at: http://www.tandfonline.com/doi/abs/10.1080/03075070903050539#.UayM7eukDQ5 Please cite as: Rossi, F (2010) Massification, competition and organizational diversity in higher education: evidence from Italy, Studies in Higher Education, 35(3), 277-300

Massification, competition and organizational diversity in higher education:

evidence from Italy

Federica Rossi

Dipartimento di Economia “Salvatore Cognetti de Martiis”

Università degli Studi di Torino Via Po 53

Torino, Italy E-mail: rossi.federica@unito.it

Abstract

The article explores whether, and to what extent, several broad trends that have taken

place in most higher education systems in the last few decades – such as

massification, privatization, increased competition for students and for research funds

– stimulate more diversity between institutions. This question is widely debated, both

empirically and theoretically.

Using Italian data, the dynamics of organizational diversity are analyzed with respect

to several features of higher education institutions, namely (1) size, (2) specialization

and (3) mission orientation. This multidimensional approach offers some interesting

results both in their own right as well as in a comparative perspective with studies that

2

have investigated similar issues in other countries.

Keywords: Higher education, privatization, competition, diversity, organization studies

3

Introduction

The changing organization of higher education systems is an issue of interest both to

the academic community and to policymakers, who have in fact promoted platforms

for the discussion of the future of the university (European Commission, 2004) as

well as various attempts to forecast scenarios for the evolution of national university

systems (OECD, 2006).

While it is now generally accepted that the normative and organizational structure of

higher education systems depends on the complex interplay of contingent factors,

including specific legislative frameworks and historical development patterns (Scott,

2004), the academic literature has identified a number of broad trends that, in the

course of the last two or three decades, appear to have taken place consistently in

most countries, and has speculated about their likely implications. A particularly

debated issue is whether, and to what extent, such trends have led to more diverse

systems, able to accommodate a wider range of student needs and preferences and to

perform a broader range of functions (Trow, 1979; Birnbaum, 1983; Stadtman, 1980;

Van Vught, 1996, 2008).

In the absence of theoretical consensus on the determinants of diversity, and on the

dimensions along which higher education systems are likely to differentiate, empirical

analyses can contribute useful knowledge to the debate. The present article analyzes

the dynamics of inter-institutional diversity in the Italian higher education system, and

attempts to relate these dynamics to changes in the functions that universities are

required to perform and in the rules governing the university system.

First, it reviews several key trends in the development of higher education systems,

and introduces the debate about their impact on organizational diversity in higher

4

education. Second, the article describes the organization of the Italian higher

education system, and discusses the extent to which it has been affected by the trends

identified previously. Third, the dynamics of organizational diversity in Italian higher

education are explored empirically, with respect to a set of institutional features: (1)

size, (2) specialization and (3) mission-orientation. Finally, some conclusions are

drawn, and some broader implications of this study are discussed.

Change and organizational diversity in higher education systems

Trends in the development of higher education systems

In the last three decades, in Europe and in many other developed countries, a number

of general trends have taken place, which have affected the structure, governance and

organization of higher education institutions. Among the many changes that

universities have confronted, particularly remarkable are the increases in the number

of students that they are required to train and in the range of activities that they are

supposed to perform, as well as the modifications in the mechanisms regulating the

allocation of public funds to institutions and in the rules underpinning governance

processes within universities (Gumport et al, 1997; Skilbeck, 2001; Krause, 2007).

In most developed countries, the share of population who attend university at some

point in their lives has increased over time, with the most relevant waves of

massification having taken place in the mid-1960s, in the early 1980s and mid-1990s

(Bonaccorsi, 2006). Currently, in countries like Britain and the US, more than one

third of 18-24 year olds are enrolled in higher education (Douglass, 2004), a share

that is well above the 15% threshold which, according to Trow (1974) separates elite

from mass education.

Such massification of higher education has been interpreted as an indication of the

5

growing need for intellectual workers in most modern economic systems, in which

knowledge industries play an increasingly important role (Peters and Humes, 2003).

Universities are required to provide a flow of trained personnel for industry, and to

contribute to the ongoing re-qualification of human resources. An increasing share of

enrolments is composed of non-traditional students, including mature and foreign

students (Kelo, Teichler and Wächter, 2006).

The greater size and complexity of the student base has entailed growing costs for the

higher education sector, in a period characterized by tighter constraints on public

finances (OECD, 1990) and by growing consensus on a reduced role for government

intervention in the economy (Geuna and Muscio, 2008), particularly in areas like

higher education where private returns are high (Psacharopoulos, 1994).

In this context, the expansion of the private higher education sector has allowed many

countries to accommodate increased enrolments without the need to further expand

public budgets (Dima, 2004). Political support for the privatization of higher

education has increased significantly since the late 1970s (Teixeira and Amaral, 2001;

Dima, 2004). The political arguments have emphasized that privatization would entail

not only cost-effectiveness and greater efficiency and accountability (Cave, Kogan

and Smith, 1990; Dima, 2004), but also more competition and client choice, leading

to increased institutional responsiveness (Teixeira and Amaral, 2001).

In most Western countries, in the course of the 1980s and 1990s, even public

institutions have undergone governance reforms aimed at increasing their decisional

autonomy and their financial accountability since - in line with the shift towards New

Public Management practices (Pollitt, 1990) – such principles are considered crucial

in order to promote efficiency, improve administrative performance and induce

universities to develop strategic capabilities (Bonaccorsi and Daraio, 2007).

6

In parallel, governments have increasingly relied on mechanisms such as accreditation

processes, assessments and rankings in order to monitor the universities’

performance.

Governments have tried to reconcile the expansion of the higher education sector with

the stringency of public budgets also by encouraging universities to reduce their

dependency on government handouts through a diversification of their funding

sources. Changes in the rules governing the allocation of funds to higher education

have often been instrumental to achieve this objective.

First, universities have been encouraged to increase the share of private funding

accrued from student fees, often by being allowed to charge differential fees for

national and foreign students. Greater competition for enrolments between institutions

has been further stimulated by the substitution, since the 1980s, of the previously

dominant incremental systems (according to which resources for education were

distributed to institutions on the basis of their historical allocations) with formula

systems where resources are made proportional to the universities’ actual

expenditures per student enrolled (Geuna, 1999).

Second, universities are encouraged to derive a greater share of their research and

education funding from private firms and charities (for example through activities

such as the provision of educational services to employers, the procurement of

research contracts, the direct commercialization of academic discoveries). The

introduction of more competitive mechanisms for the allocation of public research

funds – which are increasingly assigned on the basis of performance and quality

criteria (Geuna, 1999; Lepori et al, 2007) – has, at least in certain countries, prompted

less successful universities to rely on consultancy and contract research for private

firms in order to supplement their research income (Geuna, 1999).

7

While these innovations in university management and regulations have mainly been

introduced in order to reduce the universities’ reliance on public budgets, to reward

performance and stimulate efficiency, transparency and accountability in the use of

public funds, they have also encouraged universities to pursue short-term objectives

in the use of funds and have resulted in more intense competition for resources for

education and research (Rothschild and White, 1991).

Finally, the increasing importance of industry contracts within university budgets

signals another much-discussed trend that has been taking place in the last two

decades: the tendency to view universities as agents of economic development. In

addition to performing their key research and education activities, universities are

increasingly expected to contribute to economic growth and wealth creation, by

ensuring the rapid production, certification and transfer of knowledge to the economic

system (Slaughter and Leslie, 1999; Etzkowitz, 2002; Nowotny, Scott and Gibson,

2001). Knowledge transfer is implemented through numerous channels, besides the

traditional “open science” dissemination of academic research results and the

provision of education services: the transaction of intellectual property rights over the

results of research, the establishment of collaborative contractual relations and

research joint ventures with industry, the creation of spin-off companies (Martin,

2003; Thursby and Kemp, 2002). Because the new functions of universities have

overlapped with their more traditional ones, some authors talk about a phenomenon of

“mission stretch” required from higher education institutions (Scott, 2007).

Organizational responses to massification and increased competition: towards

increasing diversity of higher education systems?

These processes pose radical challenges to university systems. First, universities are

required to accommodate a growing population of students with more varied

8

educational, social and cultural backgrounds, in the context of decreasing government

budgets. Second, since in the so-called knowledge-based economy universities are

increasingly required to produce knowledge that is relevant to the needs of the

economy and of society (Slaughter and Leslie, 1999; Geuna and Muscio, 2008), there

is a need for more trans-disciplinary science, as well as a dual need for the acquisition

of more generic competences and for understanding the specific context of knowledge

(Gibbons et al, 1994). Third, another challenge is how to accommodate the expanding

missions that the university is supposed to accomplish, finding ways to transfer

knowledge to the economic system through channels that are different from the

standard education and research routes (Etzkowitz and Leydesdorff, 2000).

Higher education analysts have argued that the answer to most, if not all, of these

challenges lies in fostering increasing diversity within higher education systems.

More diverse systems, it is claimed, can cope with new functions and respond to the

many demands coming from a larger and more varied set of stakeholders (Conceição

and Heitor, 1999; van der Wende, 2007). However, there is little agreement on the

determinants of diversity. Although policymakers sometimes assume that institutional

differentiation will follow spontaneously from a combination of the trends identified

above (see for example European Commission, 2004), the actual theoretical positions

are controversial. While some authors have argued that higher education systems have

an innate tendency to differentiate and to increase their diversity (Parsons and Platt,

1973; Clark, 1983), others, inspired by the theory of institutional isomorphism

(DiMaggio and Powell, 1983), have reached the opposite conclusion that higher

education systems are likely to become less diverse over time, because of the

homogeneizing influence of the institutional context (Neave, 2000; Huisman, 1998;

Goedegebuure et al, 1996; Van Vught, 1996 and 2008). The effects of increased

9

competition on diversity are also contested, with some authors claiming that

competition encourages institutions to look for market niches (Aldrich, 1979), others

claiming that competition encourages imitation (Riesman, 1956; Hannan and

Freeman, 1977; Aldersley, 1995) and yet others suggesting that competition can foster

both effects, depending on the circumstances (Geiger, 1996; Goedegebuure et al,

1996).

It is very difficult to reach a wide consensus on the causes and dynamics of

organizational diversity in higher education, for a number of reasons. First, there is no

prevailing organizational theory explaining the mechanisms that promote diversity in

social systems and the conditions under which differentiation processes take place,

which could be applied to the case of higher education (Huisman, 1998; Van Vught,

1996; Teixeira and Amaral, 2001). The dynamics of organizational diversity depend

on the outcomes of very complex interactions between agents at different levels of

social organization – individuals, political coalitions, institutions – and between these

agents and their environment: theories of organizational diversity are therefore

necessarily incomplete and may lead to contradictory interpretations (Teixeira and

Amaral, 2001). Second, diversity has many dimensions: it is possible, for example,

for the same process to foster diversity in one dimension while at the same time

fostering homogeneity in another dimension. It is therefore extremely important to

clarify the features of higher education systems to which the concept of diversity is

applied.

Table 1 summarizes several process that have been identified by the literature as

affecting the amount of diversity present in higher education systems, with respect to

some of their main features. For each of these features it is possible to find arguments

in favour of opposite views on the dynamics of diversity. Since it is very difficult to

10

anticipate purely on theoretical grounds whether processes promoting or hampering

diversity in the system will prevail, the support of empirical enquiry is particularly

important.

(Table 1 about here)

Higher education in Italy: context and trends

In the academic year 2007/2008, according to data reported by the Italian Ministry of

University and Research, 93 higher education institutions were active in Italy; of

these, 76 were universities, 10 were “distance learning” universities, 5 were advanced

postgraduate institutions, and 2 were “universities for foreigners”, specialized in

Italian language and culture.

Although the Italian university system is formally very homogeneous - universities

constitute the only institutional form in higher education (Kyvik, 2004) and until very

recently only one type of degree title existed - in practice there are marked differences

between institutions (Clark, 1977). With respect to historical origin, several “waves”

of creation of universities can be identified: a large share of universities have been

founded before the French revolution, mostly in medieval times; some have been

founded between the late XIX century and the second World War, a period which has

seen the creation of a number of specialized universities (the “politecnici” of Milan,

Turin and Bari, specialized in engineering and architecture, Bocconi university in

Milan, specialized in economics, and L’Orientale of Naples, specialized in Asian

languages); however, universities founded after 1945 constitute by far the largest

group.

The rate at which new universities have been created has broadly followed the rate of

growth in enrolments. Access to higher education was, for a very long time, restricted

11

to a small elite of wealthy students. Only after the mid-1960s, Italy finally moved into

mass secondary education. Yearly growth rates in enrolments were positive until the

late 1970s, followed by a slowdown until the early 1980s, and a subsequent period of

sustained growth until the end of the decade: overall, the number of enrolled students

increased five-fold between 1960 and 1991 (Catalano and Silvestri, 1992). After a

period of stall in enrolments in the early 1990s, due mainly to demographic decrease,

the number of enrolled students picked up again, increasing by about 9% between

2000 and 2005. Since in the same period the number of tenured teachers increased by

26.1%, the students/teachers ratio progressively decreased, remaining, however, one

of the highest among the OECD countries (MIUR, 2006).

Between 1945 and 1980, like in most other Western countries (Geuna, 1999), the

growth in demand for university education was matched by a large increase in the

number of public university institutions, and correspondingly of faculties and

teachers. After 1990, the share of private universities has instead increased rapidly, as

can be seen from Figure 1, which shows the number of universities active in Italy

since 1850. While 90% of the universities created between 1960 and 1990 were

public, 49% of the 35 universities created after 1990 were private. The trend towards

increased privatization has been even stronger after 2000, largely because of the

creation of numerous private institutions that exclusively provide distance learning

educational services. The lower costs (in terms of buildings and other physical

infrastructures) involved in setting up distance learning institutions and the rapid

development of web-based technologies, have allowed rapid growth in the number of

these so-called “telematic universities” (11 have been created between 2000 and

2006).

(Figure 1 about here)

12

Besides their historical origins, Italian universities differ markedly also in terms of

size and specialization, two aspects whose dynamics are explored in greater detail in

the next section.

Furthermore, over time, some of the rules enforcing institutional homogeneity have

been relaxed and elements of competition have been introduced. Between the end of

the 1980s and the early 1990s, numerous innovations have been introduced in the

system of rules governing the relationship between universities and central

government, which was previously characterized by very strong centralization:

universities were given the ability to set their own statutes and regulation (1989) and

to autonomously decide how to allocate their budgetary resources (1993). The

universities’ autonomy further increased after 2000, when they became responsible

for setting up and managing their own PhD programmes and for the direct recruitment

of teachers at all levels.

Starting with the academic year 2000/2001, in line with the Bologna process, the

standard duration of undergraduate degrees was shortened from four to three years

and a two-year master degree was introduced. There is some evidence that, like in

other European countries (Geuna, 1999), the Bologna reform has increased

participation rates (Giannessi, 2006) and has encouraged more enrolments on the part

of non-traditional students (Almalaurea, 2007). The number of international students

has also increased, although this phenomenon remains marginal if compared with

other countries. According to the Ministry of University and Research, in 2005/06

only 2.28% of students enrolled in Italian universities were foreign citizens, a very

small share when compared with other European countries: for example, according to

Kelo, Teichler and Wächter (2006), in 2003 the share of foreign students had reached

19.5% in Switzerland, 17.6% in the UK, 13.3% in Austria and 11.9% in Germany.

13

Following this reform, universities have been allowed to freely set up new bachelor

and master degree courses, within some broad ministerial guidelines in terms of

educational objectives to be fulfilled, minimum commitment expected from students,

and subjects to be included in each curricula. This has led to a large growth in the

number of curricula offered in the Italian university system, from the 2981 curricula

offered in 2001/02 to the 5434 curricula offered in 2006/07 (Giannessi, 2006).

The rules governing the allocation of public money to universities have also

undergone significant changes. Until the early 1990s, funding was allocated on the

basis of each institution’s historical expenditures, with incremental resources made

available for the development of new activities (Geuna, 1999). In 1993, it was

established that a share in the budget of each university (whose weight in the total

budget would increase over time) should be assigned on the basis of the university’s

actual expenditures: the estimate of production costs per student constituted one of the

main criteria for funds allocation (Bagues, Sylos Labini and Zinovyeva, 2008). Later,

in 1997, universities were allowed to set their own tuition fees independently, within

minimum and maximum thresholds defined by the Ministry (Catturi and Mussari,

2003).

A more competitive system was also introduced, in the mid-1990s, for the allocation

of research funds. Until then, the research funds allocated to each university were split

into a 60% and a 40% share. The former constituted a non-targeted form of research

funding, computed on the basis of the number of researchers: each university then

allocated these funds to individual professors according to their own procedures. The

40% share constituted instead a form of targeted funding, to be distributed by the

university on the basis of a competitive evaluation of research proposals presented by

the various research teams. Because of lack of external control on the universities’

14

evaluation procedures, these funds were distributed to a large extent on the basis of

academic politics (Bruno and Orsenigo, 2002). In 1997, in order to increase

transparency in evaluation and competition among universities, it was established that

the “40% Funds” would be allocated centrally by the Ministry on the basis of public

tenders: the projects submitted – requiring the collaboration between teams from

different universities –were to be evaluated by anonymous referees.

Together, these trends and interventions have increased the universities’ decisional

autonomy, reduced the extent of direct government control over the university system,

and have arguably contributed to intensifying competition for enrolments and for

research funds among universities. To gain empirical insight into whether they have

also led to increased diversity between higher education institutions, the analysis

considers, separately, three features of institutions with respect to which the issue of

diversity is often debated: (1) size, (2) specialization and (3) mission orientation.

The organizational development of the Italian university system: towards

increased diversity?

Empirically, the extent and dynamics of diversity in higher education have been

investigated in different ways. Several studies have constructed typologies of higher

education institutions and have shown how institutions move across categories over

time (Birnmaum, 1983; Aldersley, 1995); other possible approaches are cluster

analysis (Geuna, 1999), the use of statistical indicators (Taylor, 2003), the use of

positioning indicators (Bonaccorsi and Daraio, 2008). The analysis presented here

relies on a combination of techniques that include the study of the features of size

distributions, the development of indicators of diversity and the study of their

dynamics over time, and cluster analysis performed at different points in time.

15

The dataset used for the analysis includes institution-level variables drawn from

several sources. Data on university teachers from 2000 to 2007, data on enrolled

undergraduate, master and PhD students (number and region of residence) in the

academic years from 1999/2000 to 2005/2006 and data on undergraduate and master

curricula between 2000/01 and 2006/07 have been drawn from the online database

made available by the Ministry of University and Research (MIUR); while data on the

research grants obtained by Italian institutions, R&D revenues, tuition fees and tuition

revenues have been drawn from the database realized by the National Committee for

the Evaluation of the University System (CNVSU). The observations refer to a subset

of 72 higher education institutions active in the period from 2000 to 2007, for which

consistent and complete data are available. Of these, 12 are non-State universities and

the remaining 60 are State universities. The distribution of the size of institutions has

been studied over a longer period of time, by integrating recent MIUR data with data

on enrolments in 1965 provided by Clark (1977), referring to a smaller subset of 30

universities active between 1965 and 2007.

Diversity in terms of size

Data on the size of Italian university institutions measured in terms of enrolled

students show that the size distribution of the 30 universities active in 1965 was very

dispersed around the mean (the then smallest university, Pescara, enrolled 370

students, while the largest, La Sapienza in Rome, enrolled 58000) and was quite

skewed, indicating that the system included a large number of relatively small

institutions and a small number of relatively large institutions.

During the period 1965-2000, all universities have expanded in size: while larger

universities have grown more than smaller ones in absolute terms, growth rates have

consistently been higher for smaller universities (particularly those that in 1965 had

16

less than 5000 students), as can be seen from Figure 2.

(Figure 2 about here)

These differentials in growth rates, however, have not led to a convergence in the

universities’ sizes, since new, initially small, institutions have continually been

created during the period. While the sizes of the group of 30 institutions that were

active in 1965 have tended to converge over time (their size distribution in 2000 is

considerably less dispersed than it was in 1965, since the ratio between standard

deviation and mean has decreased considerably), the size distribution of the entire set

of universities active in 2000 is just as dispersed around the mean and just as skewed

as the overall size distribution was in 1965.

The same pattern is found if the set of universities active in the more recent period

between 2000 and 2007 is considered. The expansion in terms of number of teachers

has been greater in those universities that, in 2000, employed less than 1000 teachers,

while a similar, although less marked, pattern can be found with respect to the

increase in the number of students. At present, diversity in terms of size is

remarkable: in 2007, the smallest university in the dataset had 23 teachers and 266

enrolled students (San Pio V university in Rome), the largest had 4770 teachers and

almost 130,000 enrolled students (La Sapienza). The distributions of the number of

students and of the number of teachers are also quite skewed.

The process of massification of higher education could have fostered a polarization in

the system, with a set of more prestigious, large universities attracting an ever

increasing share of enrolments and with smaller and less prestigious universities

characterized by stagnating or even decreasing enrolments: instead, smaller

universities have consistently displayed higher growth rates. However, because the

17

increase in demand for university education has been accompanied by a rapid

expansion in the number of institutions, the size distribution of universities in the

system has remained quite similar over time, that is diversity has not decreased.

There is marked stability in the ranking of institutions, especially at the top: Rome’s

La Sapienza, Bologna and Napoli’s Federico II have remained the largest universities

in the country for the past 45 years. As shown in Figure 3, universities that were

founded a longer time ago are on average larger than more recent ones, and non-State

universities, which are generally younger than State ones, are also on average smaller.

Older universities are therefore more successful at attracting greater numbers of

students, probably thanks to the prestige they have acquired during centuries of

activity; however, they are not usually the fastest-growing institutions.

(Figure 3 about here)

Using data on a set of 271 European institutions, Bonaccorsi and Daraio (2008)

identified a set of high-growth universities which are characterized by small size,

specialization, private status, strong support from the local community, localization in

densely populated areas with overcrowded universities as well as, generally, lack of

specific research orientation. If the set of 11 Italian universities that have displayed

the highest growth rates in the period 2001/2002-2005/2006 (with average yearly

growth rates higher than 10%) are considered, about half of them show a combination

of features that are similar to those identified by these authors. While these

universities are all small or medium in size, they are quite heterogeneous with respect

to most other features: only 3 are private, 7 have been founded after 1960, most are

specialized in a few disciplines, although four are quite diversified; they are all

localized in regions where several other universities are present, although not all of

them have a direct competitor in the same city. The ability of a university to grow

18

rapidly is likely to depend on a range of factors and their complex interactions (such

as the size of the pool of potential users, the university’s geographic localization, its

offer in terms of range and prestige of courses and disciplines), so that successful

universities can enjoy different sources of competitive advantage.

Diversity in terms of mixes of disciplines offered

It has often been suggested that increased competition for enrolments among

institutions will foster greater diversity in terms of disciplines offered and modalities

of course delivery, as universities look for market niches in their competition for

students. However, it has also been pointed out that competition for enrolments can

lead universities to adopt risk-averse behaviour by imitating their most successful

competitors, following the short-term dynamics of student demand and hence

focusing on more popular subjects (Dima, 2004). An analysis of Italian universities

between 2000/01 and 2006/2007 (Rossi, 2009a, on which part of the analysis

presented in this section is based), has highlighted that the second effect has

prevailed.

The growth in enrolments that has characterized the Italian university system in the

last few decades has taken place differently in different disciplines. In the academic

year 2004/2005, 60% of Italian students were enrolled in only 5 of the 14 broad

groups of disciplines offered (13.3% were enrolled in law, 12.4% in economics and

statistics, 11.7% in sociology and political science, 11.7% in engineering, and 9.3% in

literature studies). While the number of students enrolled in scientific disciplines has

not decreased over the last 30 years, the share of enrolments in those subjects has

diminished, as many more students have chosen the arts & humanities and social

sciences (Carfagna, 2006).

19

The analysis of the dynamics of diversity with respect to the disciplines offered by

Italian universities has been performed through several indexes measuring

specialization, diversification and differentiation in terms of curricula, summarized in

Table 2.

(Table 2 about here)

Due to data availability, the analysis refers to a relatively short period of time (the

academic years between 2000/01 and 2006/07) characterized, however, by marked

changes in the structure of the educational offer. It must be noted that, while

according to ministerial guidelines, each bachelor degree curriculum must belong to

one of 42 possible categories and each master degree curriculum must belong to one

of 104 possible categories, in order to compute the indexes presented above both

bachelor and master degree categories have been aggregated into 14 disciplines (listed

in Table 3 below). In turn, these disciplines have sometimes been aggregated into 4

groups: natural & technical sciences, medical sciences, social sciences, arts &

humanities. The reason for such aggregation is that the purpose of the analysis is to

investigate trends in the offer of disciplines on the part of institutions, rather than the

dynamics of the educational offer within each discipline.

At the beginning of the period, the system was characterized by marked diversity

between universities in terms of their specializations. The application of a divisive

clustering technique (Kaufman and Rousseeuw, 1995) to the normalized

specialization indexes constructed using the data on bachelor degree curricula offered

in the year 2000/01 returns 4 well defined clusters (the divisive coefficient is 0.71),

characterized as follows:

• the first cluster includes 36 universities that are specialized in nine or more

20

fields; this group comprises the largest and oldest universities in the country,

including Rome’s three main public universities, and the universities of

Milano, Torino, Bologna, Bari, Genova;

• the second cluster includes a set of 13 smaller universities which are

specialized in between five and ten fields;

• the third cluster includes 14 universities that present positive specializations in

medicine and/or engineering and architecture, and/or law and economics and

statistics; this group includes all the technical universities (“politecnici”), three

universities specialized in medicine, and a few other small universities;

• the final cluster includes 10 universities that are strongly specialized in the

social sciences and/or the humanities, many of them private and recently

created.

While the system was quite diverse in terms of specializations in 2000/01, it is

interesting to explore what happened in the following period, which has been

characterized, as mentioned previously, by the introduction of a two-level

qualification system and by concession of greater autonomy to universities in terms of

their ability to organize new curricula. Although the period after 2000/01 has seen a

doubling in the number of curricula offered, the analysis performed at a higher level

of aggregation (14 disciplines) shows in fact that the range of disciplines taught on

average within each university has narrowed.

Between 2000/01 and 2006/07, Italian universities have consistently displayed over-

specialization in the social sciences and arts and humanities. This pattern is present

both for bachelor and master degree curricula: in the latter case, after a two or three

year period of instability following the formal introduction of master degrees, the

21

normalized specialization indexes have stabilized to values that are close to those

found in the former case (Rossi. 2009a). As shown in Table 3, private universities are,

on average, under-specialized in the hard sciences and medicine (the cells highlighted

in grey indicate relative over-specialization): rather than complementing the mix of

disciplines offered by public universities, they further contribute to the over-

specialization of the Italian university system in the arts & humanities and in the

social sciences. This finding is in line with analyses of other university systems,

which have shown that most private institutions tend to focus on popular subject areas

with low investment costs, in order to maximise short-term profits, leaving the

provision of costly or more risky activities to the public education system (Dima,

2004; Teixeira and Amaral, 2001).

(Table 3 about here)

The dynamics of the diversification index, computed for each institution using data on

bachelor degree curricula, show that, in the course of the period 2000/01-2006/07,

those universities that displayed higher values of the index at the beginning of the

period reduced their diversification, while those that displayed lower values of the

index at the beginning of the period increased it. This is shown in Table 4, where

universities are classified according to their size (universities are divided into large,

medium-large, medium and small according to the quartiles of the distribution of the

number of enrolled students in 2005/06), ownership (State and non-State) and market

(universities are divided into regional, trans-regional and national according to

whether their students come mainly from the same region, from neighbouring regions,

or from regions elsewhere in the country). Large and medium-large, public and

regional universities, which were more diversified at the beginning of the period, have

become less diversified, while small, private and national universities, which were

22

less diversified at the beginning of the period, have remained so. Therefore,

universities in the system have on average reduced their diversification.

(Table 4 about here)

Finally, the analysis of the differentiation index also confirms that the extent of

diversity present in the system from the point of view of the mix of disciplines offered

by university institutions has decreased. As can be seen from Table 5 (where the

indexes are computing using bachelor degree curricula, but similar patterns can be

found using master degree curricula), private, small and medium-small universities

present higher differentiation (higher distance from the “average university”)

throughout the period, but such differentiation is decreasing. State, large and medium-

large universities present lower differentiation throughout the period, but such

differentiation is stable or increasing. The convergence in the differentiation indexes

indicates that universities have increased their similarity in terms of the mix of

disciplines they offer.

(Table 5 about here)

Universities face contrasting pressures for specialization (for example, in order to find

specific market niches) and for diversification (for example, in order to capture a

wider range of student preferences). The present analysis indicates that in recent years

the overall diversity present in the system has decreased, since universities have

tended to specialize in the same direction. On average, universities have increased

their specialization in the more popular social sciences and arts & humanities, as

Table 6, which reports the variations over time in the average normalized

specialization indexes, shows.

(Table 6 about here)

23

There is some evidence that, in the same period, variety has increased in terms of

modes of course delivery: the offer of online and evening courses has expanded, even

in the absence of public support for this kind of initiatives (Conferenza dei Rettori

delle Università Italiane, 2006). This is consistent with international studies that have

highlighted how newer institutions, often private, have contributed to innovations in

course delivery modes and have been successful in accommodating a more diverse set

of students than their more established public counterparts.

Diversity in terms of mission orientation

Several studies have suggested that the introduction of more competitive mechanisms

for the allocation of funds, especially of research funds, have led to increasing

polarization between universities (Geuna, 1999; Thomas, 2001; Krause, 2007), with

some universities becoming increasingly research-oriented and others relying on

teaching, and often on third mission activities, as a way to compensate for their lack

of success in obtaining research funds. Besides the role of funding mechanisms that

lead to concentration of resources in a few institutions (Huisman, Horta and Heitor,

2008; Ljungberg, Johansson and McKelvey, 2006), the literature suggests that

increasing polarization is fostered by government policies aimed at bolstering the

development of research universities, and by the increasingly diffused practice of

ranking universities according to the quality of their research and education activities

(Scott, 2004; Geuna, 1999).

To find out whether the Italian system has become increasingly polarized, a cluster

analysis exercise has been performed at two different points in time, 2000 and 2004,

allowing us to categorize Italian universities on the basis of their orientation towards

teaching and research. While data availability issues force us to focus on a relatively

short period, these years have been chosen in order to capture at least in part the

24

effects of the reform which has introduced the two-level qualification system.

Universities have been quite independent in their choice of how to react to the reform,

and this should be reflected in their different behaviours. The clustering exercise has

been performed using the following variables:

• the ratio between research grants obtained and the academic staff of the

institution (GRANTSTAFF). Since in the Italian system all academics

(researchers, associate and full professors) are supposed to perform both

research and teaching activities, the variable “number of academics” used to

construct this ratio includes all academic positions;

• the ratio between the number of PhD students and the total number of students

enrolled in undergraduate courses (PHDUNDERGRAD). The definition of

undergraduate courses here includes both bachelor and master degree curricula

since both have very little, if any, research content;

• the ratio between the number of bachelor and master curricula and the academic

staff of the institution (CURRSTAFF). Again, the variable “number of

academics” used to construct this ratio includes all academic positions.

The first two variables are positively associated to research orientation, as they

indicate, respectively, the institution’s ability to procure competitively allocated funds

for research and the importance that the institution attributes to the training of young

researchers. In order to measure research orientation, indicators of research

productivity based on research outputs, such as the number of publications, would

have been more appropriate. However, complete data on the publications of Italian

universities are not available for two separate years during the period in question.

Although research grants are an input measure, it has been shown empirically that an

25

institution’s ability to procure research grants is positively related to its orientation

towards research (Ljungberg, Johansson and McKelvey, 2006; Rossi, 2009b). The

amounts of research grants per academic staff therefore can be thought to capture at

least partially the research orientation of an institution. Finally, the last variable is

positively associated with orientation to teaching, since more curricula per academic

staff indicate that greater demands are placed on his or her time in terms of number or

variety of courses to teach.

The divisive clustering algorithm (Kaufman and Rousseeuw, 1995) is applied twice,

once to the values of these three variables in 2000 and once to the values in 2004. In

both cases, the number of clusters is found by cutting the dendrogram at the same

height (h = 02).

For 2000, 3 significant clusters (divisive coefficient 0.965) are found: one (cluster I)

includes most universities in the sample (86%); another (II) includes a smaller set of

institutions (12.5%); the last (III) includes a single observation. The institutions in

cluster I are more research-oriented than those in cluster II, having, on average, higher

research grants per academic staff, more PhD students per enrolled student and a

lower number of curricula per academic staff, as shown in the Table 7. The outlier

institution in cluster III has much higher values of all three variables. The research-

oriented institutions in cluster I are on average older, larger (both in terms of

academic staff and of enrolled students) and more diversified than the more teaching-

oriented institutions in cluster I. Research-oriented universities also have a much

higher amount of R&D revenue per academic staff. Teaching-oriented institutions

tend to be younger, smaller, less diversified (in particular, they are relatively over-

specialized in the arts & humanities) and to attract a greater share of students from

their own region. There are not strong differences across clusters in terms of

26

ownership.

(Table 7 about here)

When the cluster algorithm is applied to the values of the same set of variables in the

year 2004, it returns 7 significant clusters (divisive coefficient 0.938). Of these, two

(clusters I and III) comprise universities that display comparatively greater orientation

towards research, with high amount of research grants per researcher, many PhD

students per undergraduate and (particularly cluster III) low number of curricula per

researcher. One cluster (II) comprises universities that are more oriented to teaching:

low amount of research grants per researcher, few PhD students per undergraduate

and a relatively high number of curricula per researcher. Three clusters (IV, V and

VI) present intermediate features between the more research-oriented and the more

teaching oriented-clusters. Finally cluster VII includes the same outlier institution

which was previously included in cluster III. Table 8 summarizes some features of the

institutions in each cluster: for simplicity, the 7 clusters have been aggregated into

three groups (research-oriented, intermediate and teaching-oriented universities).

(Table 8 about here)

Research-oriented universities are older and larger (both in terms of academic staff

and of enrolled students), and have higher R&D revenue per academic staff, than

teaching oriented-ones. There are no differences in terms of diversification, while

teaching-oriented institutions are all public. Intermediate institutions generally display

values of these variables that are intermediate between those of the institutions in the

other two groups.

In order to understand the extent to which the system has increased its polarization

between teaching-oriented and research-oriented institutions, we explore how

27

institutions have moved across clusters over time. The large cluster of 62 institutions

that in 2000 were more research-oriented has split between the research-oriented (28

universities), intermediate (30) and teaching-oriented (4) clusters, while also the small

set of teaching-oriented universities (9) has split between research-oriented (2),

intermediate (5) and teaching-oriented (2) clusters.

The research-oriented institutions that have remained so over time, are generally

older, larger, more diversified and predominantly public; in 2000, they had much

higher R&D revenues per academic staff. The research-oriented institutions that have

moved towards the intermediate and teaching-oriented clusters, instead, tend to be

younger and smaller than the former, with a higher share of students coming from the

same region; in 2000, they were able to charge, on average, higher tuition fees per

student, and had a higher share of tuition fees as a percentage of total revenue. The

institutions that have moved from the teaching-oriented cluster in 2000 to the

research-oriented ones are quite young, small, over-specialized in the technical &

natural sciences and in the social sciences. The teaching-oriented institutions that

have remained so over time, in 2000 had lower R&D revenues per academic staff but

were charging higher tuition fees per student.

Given that the share of institutions that have moved from research to teaching

orientation (34) is greater than the number of those that have moved in the opposite

direction (7), these figures lend some support to the view expressed by Bonaccorsi

(2007) who argued that one of the effects of the rapid adoption in Italy of the Bologna

scheme was a refocusing of universities on undergraduate teaching. However, this

kind of analysis should be performed over a longer time span to see whether the

patterns identified here prove to be persistent.

It is not possible to infer, from the limited time period to which the analysis refers, if

28

such differentiation is a consequence of the more competitive allocation of research

funds, introduced in 1997 but referring only to a share of the total research funding, or

whether it has been especially fostered by the introduction of a two-level qualification

system in 2000, which was used as an opportunity to redesign the whole educational

supply, or both. One possible explanation is that in a context of increased competition

for funds and with increased decisional autonomy, universities have been “playing to

their strengths” emphasizing their teaching or research orientation according to their

relative performance in these areas. Figure 4 provides some support for this claim,

showing that many of the institutions that have moved from being research-oriented

to being teaching-oriented had the ability, in 2000, to charge higher tuition fees per

student but were less successful in procuring R&D revenues; while the contrary

applied to those universities that have remained more oriented towards research.

(Figure 4 about here)

Conclusions

The introduction of measures that have increased competition among institutions and

the autonomy of universities from the central government has had different effects on

the extent of diversity present in the system, according to the institutional features

with respect to which diversity is measured. We have chosen to focus on three aspects

– size, specialization and mission-orientation – although many more could be

investigated.

(1) The analysis of the size distribution of universities, over a long time span, shows

that the process of massification has affected all institutions in the system. The

expansion in the number of students has mainly been addressed through an increase in

the number of higher education institutions. It is not possible to identify high growth

29

institutions on the basis of common structural features, indicating that the sources of

universities’ success in attracting students are many and complex.

The analysis of the institutions’ specializations, performed over the period 2000/01-

2006/07, shows that disciplinary specializations have tended to converge, while

modalities of course delivery have increased. While greater diversity in modalities of

course delivery facilitates access to higher education, and this process has taken place

without the need for specific policies, there is no general guarantee that increased

competition per se will foster diversity in the disciplines offered. If the expansion of

the educational offer is entirely left to the “market dynamics” of competition, the risk

is a refocusing of the system on the disciplines for which demand is higher, as

universities seek to maximize enrolments (given that their allocations depend

crucially on the amount of students that they are able to attract), but which are not

necessarily reflecting the competences that are mostly needed in the social and

economic system (Rossi, 2009a). In the period considered, Italian universities appear

to have increased their specialization in the social sciences and arts & humanities, at

the expense of the technical & natural sciences. This suggests that competitive funds

allocation mechanisms could have strong effects on the offer of disciplines on the part

of universities, and therefore they should be carefully constructed; in particular, they

should be sophisticated enough to incentivize universities to offer courses and

promote enrolments also in promising and important fields which may not be highly

demanded from students.

The analysis also shows, albeit with reference to a short time span (2000-2004), that

increased differentiation has taken place in terms of mission orientation, since the

cluster of universities that in 2000 were more-research oriented have divided into

different groups. A smaller share of universities have maintained their research-

30

orientation, while a larger share have turned more heavily towards teaching. This

finding is consistent with analyses carried out using data from the UK (Geuna, 1999;

Taylor, 2003), Sweden (Ljungberg, Johansson and McKelvey, 2006) and Australia

(Valadkhani, and Worthington, 2006), where it has been argued that increased

competition for funds among universities and the tendency of research funds to

concentrate in a few prestigious research institutions have increased the universities’

polarization along the teaching-research dimension, inducing those universities that

display weaker research performance to become more teaching-oriented. Our data

suggest that a similar process may be taking place in Italy, although the analysis

should be carried out over a longer time span.

Increased diversity in mission orientation could be considered as a positive

development if it is believed that more diverse institutions are better able to satisfy a

wider range of student needs and to accommodate into higher education a greater

variety of students with different abilities and aspirations. However, it could also be

considered problematic if it is believed that high quality research is necessary for the

delivery of good quality university education (Neumann, 1996; Leisyte, Enders and

De Boer, 2008).

While this study has focused only on a small set of institutional features for which

different measures of diversity have been computed, the analysis suggests some

general implications.

Increased competition for students and research funds between university institutions

has different effects on different characteristics of the system. In order to investigate

the effects of policies and trends on diversity in higher education systems, it is

important to specify which aspect of the system the concept of diversity is applied to,

31

and to study it separately from other aspects.

Higher education systems face pressures for diversification as well as very strong

pressures for homogeneization. As argued by Huisman, Horta and Heitor (2008),

while the competitive allocation of research funds promotes diversification in

mission-orientation, processes of imitation among institutions are also present,

especially with respect to other features of universities. Diversity cannot always be

assumed to result spontaneously by assigning to universities more decisional

autonomy and by infusing more competition in the system. Therefore, if diversity

with respect to certain aspects of higher education is considered desirable, specific

policies in order to encourage it are often required.

32

Acknowledgements

This research has been supported by a doctoral grant from MIUR. I wish to thank

Cristiano Antonelli, Aldo Geuna and Allison Wylde for helpful comments and

suggestions. I am also grateful to three anonymous referees whose comments have

greatly helped me to improve the article. Any errors are my own.

33

References

Aldersley, S.F. 1995. “Upward drift” is alive and well. Research/doctoral model still

attractive to institutions. Change Sept.-Oct.: 51-56.

Aldrich, H. E. 1979. Organizations and environments. Englewood Cliffs, NJ:

Prentice-Hall.

Almalaurea. 2007. Indagine 2007: profilo dei laureati 2006.

http://www.almalaurea.it/universita/profilo/profilo2006/ (Accessed January

2009).

Bagues, M., Sylos Labini, M. and N. Zinovyeva. 2008. Differential Grading

Standards and University Funding: Evidence from Italy, CESifo Economic

Studies 54(2): 149-176.

Birnbaum, R. 1983. Maintaining diversity in higher education. San Francisco: Jossey-

Bass.

Bonaccorsi, A. 2006. The new European university. Paper presented at the The

Atlanta Conference on Science & Technology Policy, May 18-20, in Atlanta,

USA.

Bonaccorsi, A. 2007. Census microdata on European Universities. The Aquameth

project. Paper presented at the EUROSTAT Task force meeting on Euro

university statistics, June 7-8, Luxembourg.

Bonaccorsi, A. and C. Daraio. 2007. Universities as strategic knowledge creators:

some preliminary evidence. In Universities as strategic knowledge creators ed.

A. Bonaccorsi and C. Daraio, 31-81. Cheltenham: Edward Elgar.

Bonaccorsi, A. and C. Daraio. 2008. The differentiation of the strategic profile of

34

higher education institutions. New positioning indicators based on microdata.

Scientometrics 74(1): 15-37.

Braun, D. 1998. The role of funding agencies in the cognitive development of

Science. Research Policy 27: 807–821

Bruno, G. and L. Orsenigo. 2002. Le determinanti dei finanziamenti industriali alla

ricerca universitaria in Italia. In Il sistema della ricerca pubblica in Italia,

Bonaccorsi, A. (Ed.), Milano: Franco Angeli.

Catalano, G. and P. Silvestri. 1992. Il finanziamento del sistema universitario italiano.

Ministero del Tesoro, Commissione Tecnica per la Spesa Pubblica, Ricerche 3:

16-18.

Carfagna, M. 2006. Lo studio delle scienze in Italia, Approfondimenti CRUI, 1: 17-27.

Catturi, G. and R. Mussari. 2003. Il finanziamento del sistema pubblico universitario

dal dopoguerra all'autonomia. Annali di storia delle università italiane, 7: 9-29.

Cave, M., Kogan, M. and R. Smith. 1990. Output and performance measurements in

government: the state of the art. London: Jessica Kingsley.

Clark, B.R. 1977. Academic power in Italy: bureaucracy and oligarchy in a national

university system. Chicago: University of Chicago Press.

Clark, B.R. 1983. The higher education system: a cross-national perspective.

Berkeley: University of California Press.

Comitato Nazionale per la Valutazione del Sistema Universitario (CNVSU). Online

database: http://nuclei.cnvsu.it/

Conceição, P. and M. V. Heitor. 1999. On the role of the university in the knowledge

economy. Science and Public Policy 26(1): 37–51.

35

Conferenza dei Rettori delle Università Italiane (CRUI). 2006. L’universita’ verso l’e-

learning. Finlandia, Francia e Italia a confronto. Roma: CRUI.

De Fraja, G. and E. Iossa. 2002. Competition Among Universities and the Emergence

of the Elite Institution, Bulletin of Economic Research 54(3): 275-293.

Dewatripont, M., Thys-Clement, F. and L. Wilkin. 2002. The strategic analysis of

universities. Microeconomics and management perspectives, Bruxelles:

Universitè Libre de Bruxelles.

DiMaggio, P.J. and W.W. Powell. 1991. The new institutionalism in organizational

analysis. Chicago: University of Chicago Press.

Dima, A.M. 2004. Organizational typologies in private higher education, paper

presented at Consortium of Higher Education Researchers 17th Annual

Conference, Sept.17-19.

Douglass, J.A. 2004. The dynamics of massification and differentiation: a

comparative look at higher education systems in the UK and California. Higher

Education Management and Policy 16 (3): 9-35.

Etzkowitz, H. 2002. MIT and the Rise of Entrepreneurial Science. London:

Routledge.

Etzkowitz, H. and L. Leydesdorf. 2000. The Dynamics of Innovation: from National

Systems and "Mode 2" to a Triple Helix of University-Industry-Government

Relations. Research Policy 29: 109-123.

European Commission. 2004. Proceedings of the conference The Europe of

knowledge 2020: a vision for university-based research and innovation, 25-28

April, in Liege, Belgium.

36

Gautier, A. and X. Wauthy. 2007. Teaching versus research: A multi-tasking

approach to multi-department universities. European Economic Review 51(2):

273-295.

Geiger, R.L. 1996. Diversification in U.S. higher education: historical patterns and

current trends. In The mockers and the mocked: comparative perspectives on

differentiation, convergence and diversity in higher education, ed. V.L. Meek,

L. Goedegebuure, O. Kivinen and R. Rinne, 188-203. Surrey: Pergamon.

Geuna, A. 1999. The economics of knowledge production. Cheltenham: Edward

Elgar.

Geuna, A., Muscio, A., 2008. The governance of university knowledge transfer.

SPRU Electronic Working Paper Series 173.

Giannessi, F., 2006. La riforma universitaria: evoluzioni e effetti. Approfondimenti

CRUI 1: 5-15.

Gibbons, M., C. Limoges, H. Nowotny, S. Schwarzman, P. Scott and M. Trow. 1994.

The new production of knowledge: the dynamics of research in contemporary

societies. London: Sage Publications.

Goedegebuure, L., Meek, V., Kivinen, O. and R. Rinne. 1996. On diversity,

differentiation and convergence. In The mockers and the mocked: comparative

perspectives on differentiation, convergence and diversity in higher education,

ed. V.L. Meek, L. Goedegebuure, O. Kivinen and R. Rinne, 2-13. Surrey:

Pergamon.

Gumport, P., Iannozzi, M., Shaman, S. and R. Zemsky. 1997. The United States

Country Report: trends in higher education from massification to post-

massification. Research Institute for Higher Education (RIHE) International

37

Seminar Reports 10: 57-93.

Hannan, M. T. and J. Freeman. 1977. The population ecology of organizations,

American Journal of Sociology 82: 929–964.

Huisman, J. 1998. Differentiation and diversity in higher education systems. In

Handbook of higher education theory and research vol. XIII, ed. J.C. Smart, 75-

100. New York: Agathon Press.

Huisman, J., Horta, H., and M. Heitor. 2008. Does a competitive research funding

encourage diversity in higher education? Science and Public Policy 35 (3): 146-

158.

Kaufman, L. and P. J. Rousseeuw. 1995. Finding groups in data: an introduction to

cluster analysis. New York: John Wiley and Sons.

Kelo, M., Teichler, U. and B. Wächter, 2006. EURODATA: Student Mobility in

European Higher Education, Bonn: Lemmens.

Kyvik, S., 2004. Structural changes in higher education systems in Western Europe.

Higher Education in Europe 24(3): 393–409.

Krause, K. 2007. Knowledge transfer, engagement and public scholarship: Emerging

possibilities for an integrated approach to academic enquiry. Paper presented at

International policies and practices for academic enquiry: an international

colloquium, 19-21 April, Winchester, UK.

Leisyte, L., Enders, J. and H. De Boer. 2008. The balance between teaching and

research in Dutch and English universities in the context of university

governance reforms. Paper presented at Bureau of Research in Complexity and

Knowledge (BRICK-DIME) Workshop The economics and policy of academic

research, July 14-15, Torino, Italy.

38

Lepori, B., Benninghoff, M., Jongbloed, B., Salerno, C. and Slipersæter, S. 2007

Changing models and patterns of higher education funding: some empirical

evidence. In Universities as strategic knowledge creators ed. A. Bonaccorsi and

C. Daraio, 85-110, Cheltenham: Edward Elgar.

Ljungberg, D., Johansson, M., McKelvey, M. 2006. Does structure matter for

science? The Matthew effect in the Swedish university sector. R&D, Innovation

and the Dynamics of Economies/Institute for Management of Innovation and

Technology (RIDE/IMIT) Working Paper 84426-014.

Martin, B. R. 2003. The changing social contract for science and the evolution of the

university. In Science and innovation: rethinking the rationales for funding and

governance, ed. A. Geuna, A.J. Salter and W.E. Steinmueller, 1-29,

Cheltenham: Edward Elgar.

Ministero dell’Istruzione, dell’Università e della Ricerca (MIUR). 2006. L’universita’

in cifre. Roma: MIUR.

Ministero dell’Istruzione, dell’Università e della Ricerca (MIUR). Online database:

http://statistica.miur.it/ustat/Statistiche/IU_home.asp.

Neave, G. 2000. Diversity, differentiation and the market: the debate we never had

but which we ought to have done. Higher Education Policy 131: 7-21.

Neumann, R. 1996. Researching the teaching-research nexus: A critical review.

Australian Journal of Education 40 (1): 5-18.

Nowotny, H., P. Scott and M. Gibbons. 2001. Re-thinking science: knowledge and the

public in an age of uncertainty. Cambridge: Polity Press.

Organization for Economic Cooperation and Development. 1990. Financing higher

education – Current patterns. Paris: OECD.

39

Organization for Economic Cooperation and Development. 2006. Four future

scenarios for higher education. Paris: OECD.

Parsons, T. and G.M. Platt. 1973. The American university. Cambridge: Harvard

University Press.

Peters, M. and W. Humes. 2003. Education in the knowledge economy. Policy

Futures in Education 1(1): 1-19.

Pollitt, C. 1990. Managerialism and the public services: The Anglo-American

experience. Oxford: Blackwell.

Psacharopoulos , G. 1994. Returns to investment in education: a global update. World

Development 22 (9): 1325–1343.

Rhoades, G. 1990. Political Competition and Differentiation in Higher Education, in

J.C. Alexander and P. Colony (eds.) Differentiation Theory and Social Change,

New York: Columbia University Press, 187-221.

Riesman, D. 1956. Constraint and variety in American education. Lincoln: University

of Nebraska Press.

Rossi, F. 2009a. Increased competition and diversity in higher education: an empirical

analysis of the Italian university system. Higher Education Policy 22 (3), 1-25.

Rossi, F. 2009b. Universities’ access to research funds: do institutional features and

strategies matter? Tertiary Education and Management 15 (2), in press.

Rothschild, M. and L. White. 1991. The university in the marketplace, National

Bureau of Economic Research Working Paper 3853.

Scott, P. 2004. Hierarchy or diversity? Dilemmas for 21st century higher education/

Paper presented at Centre for Higher Education (CHE) Conference, 29-30 April,

40

Berlin, Germany.

Scott, P. 2007. Back to the future? The evolution of higher education systems, in

Looking back to look forward. Analyses of higher education after the turn of the

millennium, ed. B. M. Kehm, 13-29. University of Kassel: International Centre

for Higher Education Research.

Skilbeck, M. 2001. The university challenged. A review of international trends and

issues with particular reference to Ireland. Dublin: The Higher Education

Authority.

Slaughter, S. and J. Leslie. 1999. Academic capitalism : politics, policies, and the

entrepreneurial university. Baltimore: Johns Hopkins.

Stadtman, V. A. 1980. Academic adaptations: higher education prepares for the

1980s and the 1990s. San Francisco: Jossey-Bass.

Taylor, J. 2003. Institutional diversity in UK higher education: policy and outcomes

since the end of the binary divide. Higher Education Quarterly 57 (3): 266-293.

Teixeira, P. and A. Amaral. 2001. Private higher education and diversity: an

exploratory survey. Higher Education Quarterly 55(4): 359–395.

Thomas, H. 2001. Funding mechanisms or quality assessment: responses to the

Research Assessment Exercise in English institutions. Journal of Higher

Education Policy and Management 23 (2): 171-179.

Thursby, J. G. and S. Kemp. 2002. Growth and productive efficiency of university

intellectual property licensing. Research Policy 31 (1): 109–124.

Trow, M. 1974. Problems in the transition from elite to mass higher education,

General report on the Conference on future structures of post-secondary

41

education, 55-101. Paris: OECD.

Trow, M. 1979. Aspects of diversity in American higher education. In On the making

of Americans, ed. H. Gans, 271-290. Philadelphia: University of Pennsylvania

Press.

Valadkhani, A. and A. Worthington. 2006. Ranking and clustering Australian

university research performance, 1998–2002. Journal of Higher Education

Policy and Management 28 (2): 189–210.

van der Wende, M. 2007. European responses to global competition in higher

education. Paper presented at the Crisis of the publics symposium, March 26-

27, Berkeley, USA.

van Vught, F. 1996. Isomorphism in higher education? Towards a theory of

differentiation and diversity in higher education systems. In The mockers and

the mocked: comparative perspectives on differentiation, convergence and

diversity in higher education, ed. V.L. Meek, L. Goedegebuure, O. Kivinen and

R. Rinne, 42-57. Surrey: Pergamon.

van Vught, F. 2008. Mission diversity and reputation in higher education. Higher

Education Policy 21 (2): 151-174.

Walckiers, A. 2008. Multidimensional contracts with task specific productivities: an

application to universities, International Tax and Public Finance, 15(2):165-

198.

42

Figure 1. State and non-State universities active in Italy since 1850

0

10

20

30

40

50

60

70

80

90

1001850

1900

1910

1920

1930

1940

1950

1960

1970

1980

1990

2000

2007

years

cum

ula

tive n

um

ber

of univ

ers

itie

s

Total

Non-State

State

43

Figure 2. Average yearly growth rates of Italian universities between 1965 and 2000

0.0%

5.0%

10.0%

15.0%

20.0%

25.0%

30.0%

35.0%

40.0%

<5000 500 - 10000 10000 - 25000 25000 - 50000 >50000

n. students 1965

ave

rag

e y

ea

rly g

row

th r

ate

19

65

-20

05

44

Figure 3. Relationship between age and size of universities (2005/06)

0

20000

40000

60000

80000

100000

120000

140000

160000

1000 1100 1200 1300 1400 1500 1600 1700 1800 1900 2000

foundation year

n. stu

dents

(2005/0

6)

Non-State universities

State universities

45

Figure 4. Universities’ relative performance and mission-orientation

0

1

2

3

4

5

6

7

0 10 20 30 40 50 60 70

R&D revenue per academic staff (2000)

Tuitio

n fees p

er

stu

de

nt (2

000)

Teaching-oriented

From teaching to research-oriented

Research-oriented

From research to teaching-oriented

46

Table 1. Processes promoting or hampering diversity in higher education systems

Nature of systemic diversity:

Processes promoting diversity Processes hampering diversity

Internal organization • Increased autonomy of public universities

• Attempt of universities to make best use of their local human and other resources

• More freedom of private institutions to define their internal structure and rules

• Increasing convergence of managerial regimes and organisational cultures

• Homogeneity of the academic profession; power of academics to defend their own norms and values

• In Europe, weak role of President; tradition of shared governance in the Academic Senate

Funding structure • Existence of separate funding sources in different regions or for different disciplines

• Freedom of universities to set their own tuition fees

• Inequality in the access and capabilities for private funding

• A large share of government funding is still assigned on a per capita basis and with political criteria

• Limited freedom of universities to set student fees

Mixes of disciplines offered

• Competition, leading institutions to seek market niches

• Homogenizing forces of the nation state and of emerging supranational structures, especially in Europe (for example the Bologna process)

• Competition, leading institutions to imitate the offer of more successful competitors

• Competition leading institutions to focus on popular subjects

Quality of research and education (hierarchical stratification)

• Mechanisms of resource allocations based on research productivity and quality, leading to concentration of resources and “Matthew effect”; for example, the Research Assessment Exercise in the UK

• Government policies aimed at bolstering the development of an explicit category of research universities (based on the American pattern)

• Rankings of universities produced by newspapers, or groups of institutions ‘approved’ by professional bodies

• Lack of mechanisms promoting vertical differentiation (absence of institutionalized mechanisms for comparison; shared political culture in favour of the principle “all universities are equal”; legal value of degrees)

• Constraints to financial autonomy, limited mobility of positions (mainly internal careers and limited mobility; disciplinary and/or clanistic academic control over admissions and career progression)

Mission orientation • Public policies allowing universities to be active in different core areas, but with very different degrees of intensity

• Massification of higher education and financial constraints, which force universities to rethink the priorities of their core functions

• Introduction of separate contracts between universities and the State regarding teaching and research

• Lack of mechanisms promoting horizontal differentiation alongside the research dimension: uniform contracts between universities and the State regarding teaching and research; impossibility to differentiate job descriptions for academic staff.

* This table builds upon Bonaccorsi (2006), Bonaccorsi and Daraio (2007, 2008), De Fraja and Iossa (2002), Dewatripont, Thys-Clemens and Wilkin (2002), Gautier and Wauthy (2007), Geiger (1996), Geuna (1999), Huisman, Horta and Heitor (2008), Leisyte, Enders, and De Boer (2008), Rhoades (1990), Riesman (1956), Rossi (2009a), Scott (2004), Thomas (2001), Van Vught (1996), Walckiers (2008).

47

Table 2. Indexes measuring specialization, diversification and differentiation

Index Formula Explanation Range of values

Specialization

index Sji = (xji / Xj ) / (xi / X )

measures the extent to which a

university specializes in each

discipline, relative to the average

specialization all of universities

in the system

Positive values. It can be transformed into a

normalized specialization index which takes

values between –1 and +1 and is symmetric

around zero: a positive [negative] value indicates

that university j is relatively over [under]-

specialized in discipline i.

Diversification

index Vj = 1/ (∑i (xji / Xj)2)

measures the scope of the range

of disciplines offered by a

university

Between 1 and n, where n is the total number of

disciplines present in the system. A low value

implies that the university is specialized in a

smaller number of disciplines, a higher value

implies that the university is more diversified. It

can be normalized to take values between 0 and

1.

Differentiation

index Dj =∑i (xji/Xj - xi/X)2

measures the extent to which the

mix of disciplines offered by an

institution is close to the mix of

disciplines offered, on average,

in the system.

Between 0 to 1, with zero indicating minimum

differentiation from the average and 1 indicating

maximum differentiation. The standard deviation

of this index captures the extent of diversity in the

system, with high standard deviation indicating

high diversity.

For all indexes: xj i is the number of curricula in discipline i offered by university j, Xj is the total number of curricula offered by

university j, xi is the number of curricula in discipline i offered by all universities, and X is the total number of curricula offered by

all universities.

48

Table 3. Specializations of State and non-State universities

type of university: State type of university: Non-State

Bachelor degrees Master degrees* Bachelor degrees Master degrees

Mathematics -0.0513 -0.0296 -0.3975 0.0538

Physics -0.0777 -0.0489 -0.7758 -0.8403

Chemistry -0.0932 -0.0620 -1.0000 -1.0000

Natural sciences -0.0412 -0.0308 -1.0000 -1.0000

Biology -0.0252 -0.0346 -0.4229 -0.5479

Medicine -0.0608 0.1647 -0.1738 -0.8477

Agriculture -0.0337 0.0412 -0.4737 -0.6902

Architecture 0.1588 0.1045 -1.0000 -1.0000

Engineering 0.0767 0.0080 -0.5979 -0.1185

Arts and literature 0.1019 0.0220 0.0702 -0.1069

Other humanities -0.0975 -0.1760 0.0874 0.0444

Law 0.0133 0.0815 0.3782 0.2691

Economics and statistics -0.0204 -0.0554 0.3752 0.4443 Political and social

sciences -0.0016 -0.0190 0.3891 0.2356

* The normalized specialization indexes are computed using 2001-2007 averages, except for those relating to master degrees which use 2002-2007 averages.

49

Table 4. Diversification of Italian universities in terms of disciplines offered

Type of university 2000-01 2006-07

Size

Small 0.1208 0.1442

Medium 0.3199 0.3196

Medium-large 0.4742 0.3999

Large 0.5706 0.4438

Ownership State 0.4141 0.3600

Non-State 0.1483 0.1717

Market

National 0.3471 0.3079

Trans-regional 0.3610 0.3041

Regional 0.3868 0.3482

50

Table 5. Differentiation of Italian universities in terms of disciplines offered

Type of university: 2000-01 2006-07

Size

Small 0.4465 0.3882

Medium 0.2078 0.1795

Medium-large 0.1074 0.1286

Large 0.0862 0.1124

Ownership State 0.1729 0.1727

Non-State 0.3783 0.3178

Market

National 0.3972 0.3558

Trans-regional 0.1705 0.1708

Regional 0.1757 0.1671

51

Table 6. Specialization of Italian universities in terms of disciplines offered

Natural & technical sciences Medical sciences Social sciences Arts & humanities

Bachelor degrees 2002 -0.0775 -0.0670 0.0861 0.0162 2007 -0.0732 -0.0902 0.1073 0.0327

difference 0.0043 -0.0232 0.0212 0.0165 Master degrees

2002 -0.0505 -0.0037 -0.0506 -0.2619 2007 -0.0631 0.0003 0.0825 -0.0544

difference -0.0126 0.0041 0.1330 0.2075

52

Table 7. Descriptive statistics of the clusters obtained for the year 2000

cluster I

(“research-oriented”) II

(“teaching-oriented”) III

(“outlier”) nr. observations 62 9 1

% observations 86.10% 12.50% 1.40%

GRANTSTAFF 0.0734 0.0424 0.5882

PHDUNDERGRAD 0.0134 0.0037 0.3016

CURRSTAFF 0.0522 0.122 0.2941

AGE 245.55 34.78 16.00

Total acad permanent staff 797.13 96.78 17.00

Total enrolled students 25854.39 6735.56 63.00

% State 82.00% 89.00% 100.00%

% students from the region 0.76 0.81 0.41

Diversification index (bachelor degree curricula) 6.23 3.84 1.00

R&D revenue per academic staff 16.92 1.60 0.14

53

Table 8. Descriptive statistics of the clusters obtained for the year 2004

cluster I & III

(“research-oriented”) IV, V & VI

(“intermediate”) II

(“teaching-oriented”) VII

(“outlier”) nr. observations 30 35 6 1

% observations 41.67% 48.61% 8.33% 1.39%

GRANTSTAFF 0.13 0.08 0.04 0.44

PHDUNDERGRAD 0.02 0.03 0.01 0.08

CURRSTAFF 0.05 0.06 0.07 0.11

AGE 263.19 213.88 177.00 16.00 Total acad permanent

staff 1151.13 595.96 216.00 32.00

Total enrolled students 36429.76 18094.08 11181.83 341.00

% State 0.96 0.77 100.00% 100.00% % students from the

region 0.78 0.75 64.73% 49.15%

Diversification index (bachelor degree

curricula) 5.85 5.60 5.90 2.25

R&D revenue per academic staff 10.27 9.84 12.73 8.59