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Urban residents are often unevenly vulnerable to extreme weather and climate events due to socio-economic factors and insufficient greenspace. This can be amplified if citizens are not meaningfully consulted in the planning and design decisions, with changes to greenspace having detrimental impacts on local communities, e.g., through green gentrification. These deficiencies can be addressed through inclusive landscape-level collaborative planning and design processes, where residents are fully engaged in the co-creation of urban greenspaces. A promising way to support co-creation efforts is gamifying technology-based interactive decision support systems (DSSs). Gamification, the incorporation of video game elements or play into non-game contexts, has previously been used for DSSs in urban planning and to inform the public about the impacts of climate change. However, this has yet to combine informational goals with design-play functionality in the redesign of urban greenspaces. We conducted a review of state-of-the-art video game DSSs used for urban planning engagement and climate education. Here, we propose that gamified DSSs should incorporate educational elements about climate change alongside the interactive and engaging elements of urban planning games, particularly for real-world scenarios. This cross-disciplinary approach can facilitate improved community engagement in greenspace planning, informing design and management strategies to ensure multiple benefits for people and the environment in climate-vulnerable cities.
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Enhancing the quality and social impacts of urban planning through community-engaged operations research
While inquiry in operations research (OR) modeling of urban planning processes is long-standing, on the whole, the OR discipline has not influenced urban planning practice, teaching and scholarship at a level of other domains such as public policy and information technology. Urban planning presents contemporary challenges that are complex, multi-stakeholder, data-intensive, and ill structured. Could an OR approach which focuses on the complex, emergent nature of cities, the institutional environment in which urban planning strategies are designed and implemented and which puts citizen engagement and a critical approach at the center enable urban planning to better meet these challenges? Based on a review of research and practice in OR and urban planning, we argue that a prospective and prescriptive approach to planning that is inductive in nature and embraces “methodological pluralism” and mixed methods can enable researchers and practitioners develop effective interventions that are equitable and which reflect the concerns of community members and community serving organizations. We discuss recent work in transportation, housing, and community development that illustrates the benefits of embracing an enhanced OR modeling approach both in the framing of the model and in its implementation, while bringing to the fore three cautionary themes. First, a mechanistic application of decision modeling principles rooted in stylized representations of institutions and systems using mathematics and computational methods may not adequately capture the central role that human actors play in developing neighborhoods and communities. Second, as innovations such as the mass adoption of automobiles decades ago led to auto-centric city design show, technological innovations can have unanticipated negative social impacts. Third, the current COVID pandemic shows that approaches based on science and technology alone are inadequate to improving community lives. Therefore, we emphasize the important role of critical approaches, community engagement and diversity, equity, and inclusion in planning approaches that incorporate decision modeling.
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- Award ID(s):
- 1934565
- PAR ID:
- 10547608
- Publisher / Repository:
- SAGE Publications
- Date Published:
- Journal Name:
- Environment and Planning B: Urban Analytics and City Science
- Volume:
- 49
- Issue:
- 4
- ISSN:
- 2399-8083
- Format(s):
- Medium: X Size: p. 1167-1183
- Size(s):
- p. 1167-1183
- Sponsoring Org:
- National Science Foundation
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