It is well established that like other entities, universities are in the business of identifying and developing competitive advantages in the marketplace for students and knowledge, based on capability, location, tradition and technology. Global rankings, although criticised, do provide some insight into competitive positioning of universities.
In this article we use the economist notion and formulation of Revealed Comparative Advantage (RCA) in trade (exports), applied to student load (total domestic and international). RCA in the traditional reckoning measures “disproportionateness” of exporting activity, that is the extent to which a country’s exports of a commodity in its total export mix is higher than the global share of exports of that same commodity in total global exports. We have re-configured this approach and instead of commodities we use load by broad field of education. RCA thus shows the extent to which load in a particular broad field of education is disproportionality represented in the load mix of an institution compared to the sector as a whole. A value greater than 1 for an institution’s load by field of education is considered to be representative of a comparative advantage. The analysis was undertaken for all Table A Australian higher education providers, and for all 12 broad fields of education, data for which was provided by the Commonwealth Department of Education for 2019. It should be noted that this measure as applied to the higher education sector is not a quality measure but a volume one.
The key points from our analysis are that when looked at by broad field, 25 out of 39 institutions have a Revealed Comparative Advantage in Education, 22 in Health, 22 in Information Technology (IT), 21 in Natural and Physical Sciences, 18 in Management and Commerce, 18 in Society and Culture. Architecture and Building and Agriculture, Environment and Related follow with 17 and 15 respectively. Of course, broad field could be masking considerable variation at the narrow field of education, and so care needs to be taken.
Nonetheless, what is clear is that most Australian institutions have a similar load profile and advantage, suggesting lack of real diversity in the system.
While factors such as student preference and perceived job potential are likely determinants, it is also possible that the system limits choice in the aggregate. What is also interesting is that only 13 Institutions out of 39 have an RCA greater than 1 for Engineering and Related Technologies, which one could normally assume is a corollary of Natural and Physical Sciences and even IT, yet does not seem to be the case. Seems that Engineering does not figure as heavily in the load deliberations of institutions as other fields.
Thirteen institutions have an RCA greater than 1 for Creative Arts while only 6 higher education providers have an advantage in Food, Hospitality and Personal Services indicating some clear specialisation in this field.
We also considered changes in RCA between 2014 and 2019. This reveals that more institutions have disproportionately higher load in Health, Natural and Physical Sciences, IT and Architecture and Building in 2019 compared to 2014. On the contrary, fewer institutions were found to display this tendency in Engineering and Related Technologies, Management and Commerce, Society and Culture, Creative Arts, Food, Hospitality and Personal Services and Agriculture, Environment and Related in 2019 compared to 2014. Over time, the focus of load by institution and broad field of education has been narrowing.
Returning to 2019 data we classify institutions according to the following categories: generalist; semi-specialist; and specialist. Generalist are those institutions which have an RCA greater than 1 for more than half of the fields of education; semi-specialist are those which have RCA of greater than 1 in 3-5 fields; and specialised are those which have RCA greater than 1 for 1-2 fields.
Using this configuration, we identified 11 generalist institutions. Monash University, Griffith University and University of Tasmania led the field with comparative advantage in 7 out of the 11 broad fields of education. Apart from sheer size in the case of Monash, which accounts for greater number of fields, in the case of the other two, specific spatial factors appear to be at work. For example, in essence University of Tasmania needs to cater to the whole of the State.
There are 26 institutions that we describe as semi-specialist, accounting for the bulk of the Table A providers. Finally, there are only two institutions that conform to what we describe as specialised: these are ACU (which has 2 fields of revealed comparative advantage), and Bachelor of Indigenous Tertiary Education.
We also labelled those institutions with RCA between 0.7 and 1.00 by field of education as partial advantage. On this score, we find that nearly all institutions have at least one broad field of education in this range, and most have 2 to 3.
Finally, we considered a range of cross sectional analysis. There was little relationship between universities with more fields of education with advantage and Global University Rankings. This is in part because Global University comprises more than student data, and puts a significant emphasis on research performance, not captured here. Second there is not a great deal of relationship between disproportionate load and net operating results of institutions, surprising given load profiles and CSP funding clusters. However, it should be noted that our analysis captures both domestic and international students and hence more disaggregated analysis might reveal a different story.
As the data pertains to 2019, clearly the impact of COVID-19 is yet to be fully felt for comparative purposes. However, one could anticipate further narrowing of the focus on the part of institutions aligned to the most profitable domestic segments. This may also open the door for new funding possibilities that foster cross university offerings to promote “diverse specialisations”.
Dr Anand Kulkarni is a higher education professional at Victoria University. This article represents the author’s views entirely.
 The notion of Revealed Comparative Advantage was developed by Bela Belassa pertaining to exports. We have reformulated it as follows. Revealed Comparative Advantage (RCA) equals University A’s load in Field of Education B/University A’s Total Load divided by Sector load in Field of Education B/Total sector load. Where this result is greater than 1, then University A has a Revealed Comparative Advantage in Field of Education B. The analysis is replicated for each field of education, for each University.Do you have an idea for a story?
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