Luc Jonveaux

Cities face increasingly complex sustainability challenges that demand cross-sector collaboration, yet existing participatory tools rarely integrate internationally recognised sustainability frameworks with systems-based visualisation in a way that supports coordinated action across diverse stakeholders. This paper presents the Placemaking Maptivity, a card-based serious game that operationalises the ISO 37101 cross-analysis matrix—six sustainability purposes against twelve areas of action—as a shared analytical scaffold for participatory neighbourhood planning. Following a Design Science Research approach, this formative artefact-development study iteratively refined the tool through four rounds of beta testing in online, in-person, and mixed-stakeholder international configurations, drawing use cases from the EU-funded REEFLEX, PROBONO, and eFORT projects. Each game mechanic is traced to a defined learning objective using the Learning Mechanics–Game Mechanics (LM-GM) framework. Stakeholder feedback across iterations provides preliminary observations that the Maptivity supports identification of multi-purpose contributions, mapping of interdependencies, and collaborative prioritisation of next steps while highlighting facilitation, timing, and contextual adaptation as critical success factors. Whether the tool improves planning quality, learning outcomes, or decision-making effectiveness compared to alternative approaches remains a question for future, more rigorously designed evaluation studies. We discuss the formative character of these results, set out limitations, and propose a more rigorous summative evaluation protocol to support broader scaling and adoption of the methodology.

Green Building Neighbourhoods (GBNs) foster sustainable, accessible, low‐carbon living through shared energy, green mobility, and social cohesion. Steering a neighbourhood towards GBN status faces hurdles in governance, financing, citizen engagement, technological innovation, and accessible tools. Current rapidly evolving digital technologies, such as BIM and Digital Twins, accelerate this transition by offering real-time tracking and visibility, fostering better coordination among stakeholders and facilitating early issue detection. The emerging advanced decision intelligence and digital decisioning platforms incorporate artificial intelligence (AI), analytics, and large datasets. This integration enables automation, optimisation, and the consistent delivery of data-driven decisions across various ecosystems. We report on the development of a novel Decision Support Platform (DSP) within the EU H2020 PROBONO project. The PROBONO DSP is iteratively tested in six “Living Labs” in Madrid, Dublin, Brussels, Aarhus, Porto, and Prague, each at different life‐cycle stages and seeking to address themes such as energy, emissions, mobility, and health. Key functionality includes digitalizing social values in BIM, large‐scale scenario sampling, thermal‐comfort simulation and monitoring, mobility benchmarking, anomaly detection, and energy‐investment comparison. Deployment in the Living Labs has enhanced information sharing, ideation, and stakeholder discussion through concise overviews and tailored recommendations. Modular integration has enabled emergent features.