Who Govern Innovation Districts? A Grounded Investigation Through the Lens of Jurisdictions

Julie Tian Miao & Daniel de O. Vasconcelos

Urban Affairs Review2026https://doi.org/10.1177/10780874251413124article
ABDC B
Weight
0.50

What the paper says

Innovation districts are hailed as the modern innovation landscapes led by privatized, local coalitions from the bottom-up. This discourse, however, conceals the influences of the multilevel governments and the territorial-power (re)configurations that are persistent and complex. In this article, we developed an Innovation Jurisdiction framework to unpack the different types of governance structures, power compositions, and their use of diverse policy mixes to shape the trajectories of innovation districts. Using the National Employment and Innovation Clusters in metropolitan Melbourne as case studies, we identified the dominance of the general-purpose (Type I) innovation jurisdictions despite the widely claimed local autonomy and power. Melbourne's cases are telling of the governance ambiguity of modern innovation landscapes and how task-specific jurisdictions (Type II) adaptive to place-based innovations are often fragmented and superimposed. Our study on the spatial-functional mismatch of the multi-level governance of innovation districts calls for more nuanced explorations at the intersections between innovation policy, public policy, and urban studies.

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https://doi.org/https://doi.org/10.1177/10780874251413124

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@article{julie2026,
  title        = {{Who Govern Innovation Districts? A Grounded Investigation Through the Lens of Jurisdictions}},
  author       = {Julie Tian Miao & Daniel de O. Vasconcelos},
  journal      = {Urban Affairs Review},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1177/10780874251413124},
}

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Who Govern Innovation Districts? A Grounded Investigation Through the Lens of Jurisdictions

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Evidence weight

0.50

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

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
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.