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CAUL-Industry Think Tank Intra-consortium cost allocation: CAUL-SCIP model. Alex Byrne University of Technology, Sydney. SCIP National Site Licence Working Group Criteria. Transparency Inclusiveness Fairness Predictability Sustainability. Transparency.

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CAUL-Industry Think Tank Intra-consortium cost allocation: CAUL-SCIP model


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    1. CAUL-Industry Think TankIntra-consortium cost allocation: CAUL-SCIP model Alex Byrne University of Technology, Sydney

    2. SCIP National Site Licence Working Group Criteria • Transparency • Inclusiveness • Fairness • Predictability • Sustainability

    3. Transparency • The data used in the cost allocation model should be drawn from verifiable sources such as • DEST data • CAUL/AARL statistics • The formula should be easily comprehensible

    4. Inclusiveness • The cost allocations determined by the formula should enable the participation of any interested member of the consortium • Institutional characteristics such as size, location, distribution of campuses should not inhibit participation

    5. Fairness • The formula should apply relevant criteria which reflect the value or potential value of the resource to each participant eg • For research • To coursework students

    6. Predictability • Large variations in cost allocation from year to year should be avoided and hence … • Data used should not be volatile

    7. Sustainability • The formula should be robust so that the consortium will be unlikely to collapse if prices rise or a few members leave

    8. Student numbers Research student numbers Research student completions Student ethnic diversity Equity measures Staff numbers Total university income Research income Size of collection Current subscriptions Library budget Number of branches Number of ILLs supplied/requested University Librarian’s discretion Vice-Chancellor’s humility Publishers’ philanthropy Possible criteria

    9. Modifications and adjustments • To include or exclude print • For prior subscription • For different packages • To apply credits • To not exceed previous expenditure • To apply maxima or minima

    10. Formulae - characteristics • Weighted • Flag fall or threshold • Capped • Banded • Equal number in each band • By category of library (eg Go8, ATN, Go5) • At break points in the data

    11. Ten university libraries: Innisfail UT Falls Creek U U Gibraltar U Carcoar U Bega U Ardrossan U Edith Falls Dalby U Jerilderee UT U Herberton Three elements: Vice-Chancellors' Humility Index (HIV) University Librarians' Silent Thoughts (LUST) Publishers' Charity (PC) Three formulae: Model X: 1/2 LUST and 1/2 HIV Model Y: 1/3 LUST and 1/3 PC and 1/3 HIV Model Z: 1/2 LUST and 1/4 HIV and 1/4 PC An example

    12. LUST, HIV and PC

    13. LUST, HIV and PC

    14. Forty universities (including ADFA & Notre Dame) Four elements: RQ Recalculated % for 2000 % Total tertiary Students % Total research population % Total library resources budget Five formulae: Model A: 1/2 RQ and 1/2 eftsu Model B: 1/3 RQ and 1/3 eftsu and 1/3 resources budget Model C: 1/4 RQ and 1/4 research pop 1/4 eftsu and 1/4 resources budget Model D: 1/3 RQ and 1/3 eftsu and 1/3 research pop Model E: 1/2 RQ and 1/4 eftsu and 1/4 resources budget SCIP modelling

    15. SCIP – sorted by Model DModel D: 1/3 RQ and 1/3 eftsu and 1/3 research pop

    16. University of Melbourne University of Sydney University of New South Wales University of Queensland Monash University University of Western Australia University of Adelaide RMIT University Queensland University of Technology University of Western Sydney ANU and La Trobe most volatile in this quartile SCIP –Model D – first quartile

    17. Curtin University of Technology Macquarie University University of Technology, Sydney Griffith University La Trobe University University of South Australia Australian National University University of Newcastle Deakin University Library University of Wollongong RMIT, UWS, UWA and Adelaide can move from this quartile SCIP –Model D – second quartile

    18. Flinders University of South Australia University of Tasmania Charles Sturt University Victoria University of Technology University of New England Murdoch University Edith Cowan University James Cook University of North Queensland Swinburne University of Technology University of Southern Queensland Flinders, CSU and VUT most volatile in this quartile SCIP –Model D – third quartile

    19. Central Queensland University University of Canberra Southern Cross University Australian Catholic University Northern Territory University University of Ballarat Bond University Australian Defence Force Academy University of the Sunshine Coast University of Notre Dame Australia None move from this quartile SCIP –Model D – fourth quartile

    20. SCIP – sorted by Model A

    21. SCIP – sorted by Model A • Model A: 1/2 RQ and 1/2 eftsu • RMIT, UWA and Adelaide go down • CSU and VUT go up

    22. SCIP – sorted by Model B • Model B: 1/3 RQ and 1/3 eftsu and 1/3 resources budget • RMIT goes down • ANU and La Trobe go up

    23. SCIP – sorted by Model C • Model C: 1/4 RQ and 1/4 research pop 1/4 eftsu and 1/4 resources budget • ANU and La Trobe go up

    24. SCIP – sorted by Model E • Model E: 1/2 RQ and 1/4 eftsu and 1/4 resources budget • RMIT goes down • Flinders, ANU and La Trobe go up

    25. Sensitivity analysis • RMIT, ANU, La Trobe are the most sensitive to changes in formulae • CSU, VUT, UWA, Flinders and Adelaide are also affected. • The smaller (fourth quartile) are unaffected. • The largest jockey for position but do not leave the first quartile. • Can also analyse capacity to pay ie cost compared to resources budget – rejected by AVCC.

    26. AVCC formula Elements: Share of • Actual student load (EFTSU) • National total of publications • Total higher degree completions • National competitive grants • Total research income • FTE staff • Existing spend for 2001

    27. Element Weighting 2002 2003 2004 2005 2006 Total EFTSU 10% 7.50% 8.40% 9.20% 10.00% 10.00% Total Research EFTSU 0% 0.00% 0.00% 0.00% 0.00% 0.00% Total Research Publications 10% 7.50% 8.40% 9.20% 10.00% 10.00% HDR Students Completions 0% 0.00% 0.00% 0.00% 0.00% 0.00% Research Income 70% 52.50% 58.80% 64.40% 70.00% 70.00% Staff FTE 10% 7.50% 8.40% 9.20% 10.00% 10.00% Current Expenditure Weighting 25% 16% 8% 0% 0% TOTAL 100% 100% 100% 100% 100% 100% AVCC formula

    28. AVCC formula

    29. University of New South Wales The University of Queensland The University of Melbourne The University of Sydney Monash University The University of Western Australia The University of Adelaide The Australian National University La Trobe University Flinders University The University of Newcastle Curtin University of Technology Queensland University of Technology Griffith University Macquarie University RMIT University Wollongong University of Tasmania University of South Australia Western Sydney AVCC formula - 1st & 2nd quartiles

    30. Uni of Technology, Sydney Murdoch University The University of New England Deakin University James Cook University Victoria University Edith Cowan University Charles Sturt University Swinburne University of Southern Queensland University of Canberra Central Queensland Southern Cross University Northern Territory University Australian Catholic University University of Ballarat Bond University Sunshine Coast AVCC formula - 3rd & 4th quartiles

    31. AVCC formula

    32. AVCC formula

    33. What’s best? • Meets criteria • Can test sensitivity • Acceptance!!!!!!!!!!!!

    34. Thank you!