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Good Enough Evidence-based Urban Planning: Data and Knowledge in Southern Smart Urbanism

Francesco Tonnarelli & Jonathan Weaver

Information Polity2026https://doi.org/10.1177/15701255261435441article
ABDC B
Weight
0.50

Abstract

This study explores evidence-based urban planning (EBUP) within three secondary cities in the Global South—eThekwini, Khorog, and Bosaso—emphasizing public sector capacity to utilize data in urban management. Amidst the proliferation of data and advanced analytical tools, many local administrations struggle with effective data use due to limited resources, technology, and governance frameworks. This paper examines how urban planners mobilize, integrate, and apply data to create actionable evidence for city planning, considering the socio-political and technological landscapes that influence these processes. By analyzing qualitative data from interviews and case studies, this research highlights the challenges and potential of EBUP to address urban issues in data-scarce environments. The concept of good enough evidence is explored, advocating for practical, adaptable, and locally tailored planning efforts that prioritize immediate urban needs over exhaustive data collection. This approach seeks to balance ambition with practicality, offering a pragmatic pathway for cities facing constraints in resources and capabilities.

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https://doi.org/https://doi.org/10.1177/15701255261435441

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@article{francesco2026,
  title        = {{Good Enough Evidence-based Urban Planning: Data and Knowledge in Southern Smart Urbanism}},
  author       = {Francesco Tonnarelli & Jonathan Weaver},
  journal      = {Information Polity},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1177/15701255261435441},
}

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Good Enough Evidence-based Urban Planning: Data and Knowledge in Southern Smart Urbanism

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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.