Satellite university campuses and economic development in peripheral regions

ABSTRACT

Satellite university campuses – whereby established universities decentralise part of their activities, often to areas previously lacking a university – contribute to the diversification of university systems. While satellite campuses, due to their small scale and limited resources, might perform some activities less efficiently than their larger parent universities, we argue that they are uniquely placed to serve the needs of their localities. Based on the case of a satellite campus in North-West Italy, we show that: (i) the campus’ main contribution lies in widening access to higher education to residents who would not attend university in the absence of local provision; (ii) the campus contributes to local development also through research and business and community engagement, and by stimulating local demand for knowledge-intensive services; (iii) research and engagement are more effective for local development where local firms possess relevant absorptive capacity and where there is a favourable institutional framework.

KEYWORDS:

• Satellite university campuses
• higher education decentralisation
• local economic development
• economic impact
• human capital development

Acknowledgements

The data collection underpinning this work has been supported by Fondazione Cassa di Risparmio di Cuneo and by the Faculty of Political Sciences of the University of Torino in Cuneo. We thank Aldo Enrietti for valuable comments on previous versions of the work, Federico Caviggioli for support in organizing the surveys, and Isabel Bodas Freitas for methodological advice. We are also grateful to two anonymous referees whose comments have greatly helped us to improve the work, and, of course, to all survey respondents and interviewees for their valuable contributions.

Disclosure statement

No potential conflict of interest was reported by the authors.

ORCID

Federica Rossi http://orcid.org/0000-0002-5869-4469

Valentina Goglio http://orcid.org/0000-0001-6341-4815

Notes

1 Several universities (particularly North-American, British and Australian ones) have developed programmes of expansion overseas (in particular in the Arabic Gulf, China and Southeast Asia) which range from the opening of full university branches issuing degree programmes, to focussed joint research ventures (Youtie et al. 2017). Unlike intra-country establishments of satellite campuses, this process has two main objectives: (i) to expand the revenue base represented by international students and boost the image and brand of the university; (ii) to develop partnerships in countries with great potential in terms of economic prospects and human capital supply (Altbach 2011; Olds 2007; Addie, Keil, and Olds 2015).

2 Eurostat data from http://ec.europa.eu/eurostat/cache/RCI/# (accessed 23 April 2018).

3 Provincial and regional data relating to 2015 are drawn from http://dati.istat.it/ (accessed 23 April 2018).

4 The percentage of students eligible to receive some form of support (tax break, study grant, free lodging) had stalled at around 10%–11% of the university population for around ten years. Further, among those eligible, the beneficiaries were roughly 8% of the university population, with large regional disparities (Laudisa 2017).

5 Interviews with one of the academic directors of the Cuneo site (7 June 2012), and a lecturer of the University of Turin involved in the setup of the Cuneo site (17 October 2012).

6 The relatively low response rate of the student population was due to the fact that, for most of them, the only available email address was the institutional one supplied to students by the University of Turin, a mailbox used by the university to communicate with the students and only occasionally opened by the latter. Personal email addresses were only obtained for 837 students of the Faculties of Law, Political Science, and Medicine (and 45 of these were found to be invalid). This explains why these three faculties had higher response rates. No significant differences in response rates were found in relation to gender or level of study (bachelor or master degree).

7 No significant differences in response rates were found in relation to gender or campus location (Cuneo, Savigliano, or Alba). The response rate was higher for non-academic staff than for academics, and for the social sciences and humanities compared to science and medicine.

8 Table A1, in the Appendix, recaps the criteria used to estimate the direct effects of the presence of the satellite campuses, calibrated to take into account, inasmuch as possible, only of those expenditures that would not have been made in the province of Cuneo in the absence of the campus. Table A2, also in the Appendix, reports the sum of the direct effects of the presence of the campus, classified according to whether they were expenditures made by the campus, by its staff, or by the students. In the case of academics and of technical-administrative staff, the main contribution to the direct effects generated by the presence of the campus was made by the salaries that the campus paid to its Cuneo resident employees who, had they not been working for the campus, would have been living elsewhere (or would have been living within the province but could have been unemployed). The expenditures made in the province of Cuneo by non resident staff represented the second contribution in order of importance. In the case of the students, the main contribution to the direct effects came from the expenditures made within the province by students attracted (either as residents or as commuters) by the presence of the campus, and by students who, in the absence of the campus, would have been residing in the Cuneo area anyway, but would have been studying or working elsewhere.

9 To calculate the type I and II Leontief multipliers, we used the input-output table for Piedmont (IRPET 2003), as, at the time of the data collection, input-output tables with a higher degree of disaggregation were not available. To estimate the proportion of total family incomes derived from salaries, we further used INPS (2009) and CNEL (2004) databases.

10 Among which, for example: the ways in which expenses are allocated to the various economic activity sectors; the estimations of the prices of various goods; the way in which the income differentials of those students who, in the absence of a satellite campus, would not have gone to university, are calculated; the choice of considering all the expenditures of those students who, in the absence of a local campus, would be studying elsewhere while residing in the province of Cuneo (it is likely that, in such an instance, those students would in any case make some of their expenditures in the province of Cuneo); the choice to not consider any of the expenditures made by locally resident staff members who, in the absence of the campus, would have continued to live in Cuneo (if they worked outside of the province of Cuneo, their expenditures within it would be lower), and so forth. While the use of a regional multiplier instead of a provincial one, due the lack of disaggregated input-output tables at the provincial level, may lead to a minor overstimation of the indirect and induced effects, many calculation choices were made with great caution; it is therefore likely that the various effects balanced each other out.

11 This was based upon a Probit regression on the ‘mobile’ variable’, defined on the 184 students residing in the province of Cuneo, that took a value of 1 if, in the absence of the satellite university campus, the student would have moved elsewhere, and of 0 if he or she would have stayed.

12 Based on the chi-square test, the difference between these two populations is significant with p-value < 0.001.

13 Based on the chi-square test, the difference between these two populations is significant with p-value < 0.1.

14 We do not have any figures on student entrepreneurship.

15 We cannot however exclude that some academics may appear as inventors in patents filed by other organisations—e.g., research companies or agencies, a phenomenon that is highly relevant both in Italy and in other countries in continental Europe (Geuna and Nesta 2006; Lissoni et al. 2008).

16 Mostly due to the reduction of the duration of undergraduate courses from four to three years, in line with the ‘Bologna process’, which enabled many already enrolled students to quickly complete their studies (Giannessi 2006). The possibility offered to many public sector workers to quickly graduate by utilising training credits also fed this phenomenon.

17 Data extracted from the Eurostat Europe 2020 Indicators databse: http://ec.europa.eu/eurostat/web/europe-2020-indicators/europe-2020-strategy/headline-indicators-scoreboard (last accessed on the 23rd of October 2017).

18 According the Istat data for 2016, only 8.3% of individuals aged between 25 and 64 had attended a training course within the 12 months preceding the survey (ISTAT 2017).