Administrative burden in Australian universities: Insights into dimensions and drivers from a nationwide survey

Peter Woelert et al.

Science and Public Policy2025https://doi.org/10.1093/scipol/scaf029article
AJG 2ABDC C
Weight
0.46

What the paper says

Abstract Despite widespread concern about levels of administrative burden within universities, understanding of the associated dimensions and drivers remains limited. Addressing the resulting lacuna, this paper presents a granular analysis of what academic staff within one national university system regard as the key dimensions and specific drivers of the administrative burdens they encounter at work. The data underlying our analyses are drawn from responses to an in-depth survey on administrative workloads from 350 academic staff working at 37 Australian universities. Our findings reveal that while generic administrative responsibilities add administrative burden, such burden is perhaps most acutely felt in the core academic work domains of teaching and research. In terms of perceptions of drivers, we find that two major strategies that universities have pursued to gain efficiencies—administrative centralization and administrative service automation—have resulted in what is widely experienced by academic staff as an intensification of their administrative burden.

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https://doi.org/https://doi.org/10.1093/scipol/scaf029

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@article{peter2025,
  title        = {{Administrative burden in Australian universities: Insights into dimensions and drivers from a nationwide survey}},
  author       = {Peter Woelert et al.},
  journal      = {Science and Public Policy},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1093/scipol/scaf029},
}

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Administrative burden in Australian universities: Insights into dimensions and drivers from a nationwide survey

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Evidence weight

0.46

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.37 × 0.4 = 0.15
M · momentum0.60 × 0.15 = 0.09
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.