Reincarnate is pleased to share the publication of the paper Strategic decision-making in uncertainty: Integrating forward-looking scenario planning and multi-criteria analysis for adaptive reuse projects, published in the Proceedings of the Circular Building Sector Conference 2025, held in Lund, Sweden, 1–3 June 2025.

The paper, authored by Brian van Laar, Angela Greco, Hilde Remøy, and Vincent Gruis from our partner Delft University of Technology, presents a novel decision-support framework for adaptive reuse — integrating forward-looking scenario planning with multi-criteria analysis to guide circular transformation under uncertainty. By combining quantitative methods and participatory approaches, the study provides decision-makers with a structured process to explore long-term reuse pathways, even when facing economic, environmental, and regulatory unknowns.

The research introduces a hybrid methodology that unites three complementary tools:

  • Cross-Impact Balance (CIB) analysis for developing consistent future scenarios;

  • Analytic Hierarchy Process (AHP) for structuring stakeholder-driven priorities;

  • Fuzzy-TOPSIS for ranking adaptive reuse strategies across multiple criteria.

Applied to a hypothetical case study, the framework demonstrates how combining CIB, AHP, and Fuzzy-TOPSIS strengthens the robustness of decision-making by improving scenario coherence and aligning reuse options with stakeholder values. The result is a transparent, data-informed process that helps planners and policymakers identify circular strategies that balance environmental, social, and economic goals.

This contribution supports Reincarnate’s vision of enabling evidence-based, forward-looking decisions for the circular transformation of the built environment — bridging scenario thinking and quantitative evaluation to make adaptive reuse a strategic component of sustainable urban development.

Read the full paper

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This project has received funding from the European Union’s Horizon Europe research and innovation programme under grant agreement N° 101056773.

Funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or European Union’s Horizon Europe research and innovation programme. Neither the European Union nor the granting authority can be held responsible for them.