Identifying urban transformation dynamics: Functional use of scenario techniques to integrate knowledge from science and practice

Timo von Wirth*, U Wissen Hayek, A Kunze, N Neuenschwander, M Stauffacher, R W Scholz

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

34 Citations (Scopus)
3 Downloads (Pure)


Many urban regions are exposed to rapid growth, leading to vast changes in land use with diverse ecological, socio-economic, and aesthetical impacts. Regional scenarios are suitable for identifying possible urban development patterns. However, one challenge of scenario construction is integrating the knowledge of both science and practice for a better understanding of the complex interactions between impact factors in the urban fabric. The objective of this research is to enhance process design for a collaborative scenario analysis in the context of urban development. The scenarios are constructed for a case study of the Limmattal region, a suburban agglomeration close to Zurich, Switzerland, and we demonstrate a functional structure for science-practice collaboration within the process of scenario building. The types of communication between science and practice are systematically varied, which leads to four consistent scenarios for 2030.Our analyses of regional system dynamics reveal the most important feedback loop among five impact factors within the region, which allows for a better understanding of the systemic interactions in regional transformation. This process design shows the potential to support knowledge integration in research processes involving science and practice, and assists informed planning strategies for urban transformation.

Original languageEnglish
Pages (from-to)115-130
Number of pages16
JournalTechnological Forecasting and Social Change
Early online date27 Sept 2013
Publication statusPublished - Nov 2014
Externally publishedYes

Bibliographical note

Funding Information:
This work is part of the “SUPat — Sustainable Urban Patterns” project, which is funded by the Swiss National Science Foundation's National Research Program (NRP 65) “New Urban Quality” ( ), Research Grant: 406540-130578 . We are grateful to the numerous stakeholders for their active participation, reflections, and valuable input throughout the scenario study. We acknowledge the valuable input given by Olaf Tietje (Systaim) on the analysis of feedback loops and by Adrienne Grêt-Regamey (ETH Zurich, PLUS) and Roman Seidl (ETH Zurich, NSSI) on earlier versions of this work. We would also like to thank the three reviewers for their very constructive comments that significantly helped to improve this paper.

Publisher Copyright:
© 2013 Elsevier Inc.

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