 Emergent systems, complexity science, and contested public choice: Housing supply in Monterrey (Mexico)Steven W. Popper (),
Juan Antonio Robledo Lara and
Jonathan Lamb
No 43, Working Paper Series of the School of Government and Public Transformation from School of Government and Public Transformation Abstract: Moving complexity science toward application faces two challenges. Models of adaptive emergence are ill-suited to analytical modes that presume model-based predictability and technical means are insufficient for problems in which normative issues make the problem intractable. Application value will be enhanced within purpose-built frameworks treating such problems’ full dimensionality. We offer an example of such a framing for the “wicked” problem of housing in Monterrey, Mexico. When system transformation is the objective, wicked problems arise in which knowledge, values, and even problem definitions and goals are contested. Solutions are not clear-cut and are themselves emergent processes. Treatment of wicked problems involves deliberations among stakeholders, adaptation, sharing alternative visions, and collaborative problem reframing for effective policy discussions. Ideally, any analytical support should occur within an integrated “deliberation-with-analysis” process. Yet, putting these ideas for decision support into practice faces methodological and practical challenges. The paper lays out both challenges and possible responses. The work on housing policy in greater Monterrey, Mexico, presents an integrated approach to address both aspects of any wicked problem: the technical (non-linear feedback, emergence, self-organization, deep uncertainty) and the value-based (competing interests and assumptions). We employ VSCARP (Visions, Strategic Concepts, Assumptions, and Robust Pathways) among a disparate group of community representatives to conduct participatory foresight that also generates design criteria for model-based quantitative analysis to support further deliberations. A Monterrey-specific urban model, based on the novel ECLIPSE (Endogenous City Landuse and Integrated Policy Experiment) agent-based framework, is designed for complex computational experiments within a robust decision-making (RDM) experimental design. Rather than conducting two consecutive processes linearly, analysis and stakeholder discussions occur simultaneously in a repeating cycle. This allows people to learn together how the system works, what values are vulnerable to shocks or trends, and which short-term actions are consistent with long-term goals across alternative future pathways. The project is a testbed for gathering insight into how complex systems theory, decision making under deep uncertainty (DMDU) concepts, and social science constructs may be applied to a highly contentious, real-world setting—a technology of complexity. Keywords: sistemas adaptativos complejos; problemas perversos; toma de decisiones robusta; prospectiva participativa; modelado basado en agentes; modelado urbano; planificación de políticas; incertidumbre profunda; México; vivienda; toma de decisiones bajo incertidumbre profunda; apoyo a decisiones. (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:gnt:wpaper:43 Access Statistics for this paper More papers in Working Paper Series of the School of Government and Public Transformation from School of Government and Public Transformation Contact information at EDIRC. |
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