
doi: 10.1002/eet.2097
AbstractUrban Living Labs are open innovation ecosystems that integrate research and innovation activities within urban communities. However, while solutions co‐created and tested in the Urban Living Labs must be contextualized and tailored to each city's uniqueness, broader impact requires generalization and systematic replication across geographical, institutional, and sectoral boundaries. This article examines nine Living Labs in European coastal cities, identifying several barriers and drivers for mainstreaming and upscaling solutions to increase climate resilience through the Living Lab Integrative Process. Our analysis focuses on three main categories. First, social and cultural aspects highlighted include stakeholder engagement and awareness, communication, and dissemination. Second, we assess institutional and political aspects, such as silos, bureaucracy, and resources. Last, we investigate technical factors as knowledge and experience, technical and internal capacity, data availability and accessibility, climate‐related policies and actions, and long‐term perspective. The results suggest that while some barriers and drivers are common across the cases, providing generalizable patterns, there are also specific differences requiring tailored solutions at the local scale. Nonetheless, the diversity in drivers indicates the potential for sharing knowledge across cases to translate, embed, and scale solutions, enhancing the transition toward climate resilience. Learning and innovation in real‐life contexts are fundamental in the Living Lab approach, and our findings demonstrate that cross‐case learning can enhance an iterative process of contextualizing and generalizing innovative climate solutions.
SDG 13 - Climate Action, SDG 11 - Sustainable Cities and Communities
SDG 13 - Climate Action, SDG 11 - Sustainable Cities and Communities
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 5 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
