Plenty of Planning, Scanty Guidance: Evaluating the Implementation Degree of the General Master Plan in the City of Tampere, Finland

Digitalizing cities has become increasingly complex and difficult to control despite advanced computational tools. The comprehension of emergent, dynamic agent–pattern interaction is limited. Studies show that the implementation of large-scale plans occasionally fails to meet expectations due to unc...

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Bibliographic Details
Published in:Sustainability 2022-11, Vol.14 (22), p.15197
Main Authors: Kuusela, Kaisu, Partanen, Jenni
Format: Article
Language:English
Subjects:
Artificial intelligence
Cities
Computer applications
Decision making
Digitization
Equilibrium
Monitoring instruments
Pattern recognition
Software
Spatial analysis
Sustainability
Urban planning
Urban studies
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Summary:Digitalizing cities has become increasingly complex and difficult to control despite advanced computational tools. The comprehension of emergent, dynamic agent–pattern interaction is limited. Studies show that the implementation of large-scale plans occasionally fails to meet expectations due to uncertainty in urban actor processes and institutions. Theories of complexity and resilience reflecting urban unpredictability and non-equilibrium enable understanding and planning methods for guiding actors. We explored empirically via close reading and spatial analyses the ability of the traditional master planning instrument to steer the actor allocation in Tampere, Finland. The plan apparently failed to appropriately guide the actors, who formed self-organizing patterns colliding with the planning aims enabled by deviations and lower-level planning instruments. The planning mode was either enabling or reactive. We recognized three types of self-organization: single-point attraction, emergent type, and location-based self-organization. Self-organization was the major force behind urban transition. Only certain large-scale projects in the city center somewhat complied with the planning aims, however through negotiations. We proposed planning solutions encouraging and guiding self-organizing patterns by recognizing complexity in strategies, and with loose plans, constant monitoring, correcting, and experimenting in planning. The results participate in building more general knowledge of planning considering self-organizing urban dynamics and provide applications for urban planning.
ISSN:2071-1050
2071-1050
DOI:10.3390/su142215197